Dissertations / Theses on the topic 'Networked things'
To see the other types of publications on this topic, follow the link: Networked things.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Networked things.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Zhang, Zhi. "Networked RFID Systems for the Internet of Things." Doctoral thesis, KTH, Elektroniksystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-120056.
Full textAbstract:
The Internet of Things (IoT) utilizes trillions of uniquely identifiable smart objects to connect anything at anytime and anywhere. Radio frequency identification (RFID) techniques are a powerful promising enabler for realizing the IoT. Around how to build hierarchical networked RFID systems for the IoT, this dissertation formulates and addresses problems in three key areas, i.e., communication protocols, simulation approaches, and RFID applications. Communication protocols are essential for designing high-performance networked RFID systems. First, we propose to use time hopping pulse-position modulation (TH-PPM) impulse radio ultra wideband (IR-UWB) for the tag-to-reader link. We analyze different parts of the system delay and propose relevant strategies to shorten the delay. Second, we give the concept of code division multiple access (CDMA) UWB RFID systems. We analyze the asynchronous matched filter receiver and decorrelating receiver for multi-tag detection, and propose a new communication process that fully exploits the multiple-access capability of the two detection schemes. Simulations are widely used to evaluate the performance of wireless networks. We propose a new approach for simulating networked RFID systems with multiple wireless standards within one case in OMNeT++. It is realized by partitioning and modeling the protocol stacks of different standards and designing a multi-radio module. Moreover, we propose a CO-Simulation framework with MATLAB and OMNeT++ (COSMO). COSMO has the ability of self-validation. It combines the strengths of MATLAB and OMNeT++ by compiling prebuilt models in MATLAB to header files and shared libraries and integrating them into OMNeT++. RFID technology gains popularity because it can be used to track and monitor objects in real time. We implement two typical networked RFID applications, i.e., wide area RFID sensor network and item-level indoor RFID localization. We design a two-layered wide area RFID sensor network for fresh food tracking. It adopts GSM/GPRS for the communication between the server and master nodes, and semi IR-UWB for the communication between master nodes and slave nodes. We develop the control platform and implement the all-in-one sensor nodes. For indoor RFID localization, we give insights about the influence of tag interaction on tag antenna radiation pattern and localization accuracy. Two examples, i.e., the k-NN algorithm and the Simplex algorithm, are taken to show how to utilize tag interaction analysis to improve the design of localization algorithms.QC 20130409
2
Shingleton, Duncan James. "Negative space of things : a practice-based research approach to understand the role of objects in the Internet of Things." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33221.
Full textAbstract:
This is a practice-based research thesis situated in the research context of the 'Internet of Things', and critiques contemporary theoretical discourse related to the 21st century turn of connecting everyday objects to the World Wide Web. In the last decade we have seen the 'Internet of Things' articulated predominately through three commercial design fictions, each a response to the shift towards pervasive", "ubiquitous" (Weiser 1991), or "context-ware" (Schilit, 1994) computing; where we inhabit spaces with objects capable of sensing, recording and relaying data about themselves and their environments. Through reflecting upon these existing design fictions, through a new combination of theories and practice-based research that embodies them, this thesis proposes a recovery to understanding the role of objects in the 'Internet of Things', which this author believes has been lost since its conception in the mid 2000s. In 2000, HP Labs presented Cooltown, which addressed what HP identified as the 'convergence of Web technology, wireless networks, and portable client devices provides'. Cooltown's primary discourse was to provide 'new design opportunities for computer/communications systems, through an infrastructure to support "web presence" for people, places and things.' (Anders 1998; Barton & Kindberg 2002). IBM's Smarter Planet followed this in 2008 and shifted importance from the act of connecting objects to understanding the value of data as it flows between these objects in a network (Castells 1996; Sterling 2005; Latour 2005). Finally, Cisco presented The Internet of Everything in 2012 and moved the argument on one stage further, identifying that the importance of connected objects lies in the sum of their communication across silos of networks, where data can provide potential insight from which you can improve services (Bleecker 2006). Despite these design and theoretical fictions, the affordances of the Internet of Things first proposed in the mid 2000s has regressed from data to product, driven largely by unchanged discourse argued by those designers at its conception and also the enticement of being the next Google acquisition; instead of pigeons reporting on the environmental conditions of a city (Da Costa 2006), we have thermostats controllable from your smartphone (www.scottishpower.co.uk/connect). Therefore the aim of this thesis is to re-examine the initial potential of the Internet of Things, which is tested through a series of design interventions as research for art and design, (produced as part of my EPSRC funded doctoral studies on the Tales of Things and Electronic Memory research project and also whilst employed as a research assistant on two EPSRC funded research programmes of work Sixth Sense Transport, and The Connected High Street), to understand how we use data to allow an alternative discourse to emerge in order to recover the role of a networked object, rather than producing prototypical systems.
3
Tsiftes, Nicolas. "Storage-Centric System Architectures for Networked, Resource-Constrained Devices." Doctoral thesis, Uppsala universitet, Datorteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-267628.
Full textAbstract:
The emergence of the Internet of Things (IoT) has increased the demand for networked, resource-constrained devices tremendously. Many of the devices used for IoT applications are designed to be resource-constrained, as they typically must be small, inexpensive, and powered by batteries. In this dissertation, we consider a number of challenges pertaining to these constraints: system support for energy efficiency; flash-based storage systems; programming, testing, and debugging; and safe and secure application execution. The contributions of this dissertation are made through five research papers addressing these challenges. Firstly, to enhance the system support for energy-efficient storage in resource-constrained devices, we present the design, implementation, and evaluation of the Coffee file system and the Antelope DBMS. Coffee provides a sequential write throughput that is over 92% of the attainable flash driver throughput, and has a constant memory footprint for open files. Antelope is the first full-fledged relational DBMS for sensor networks, and it provides two novel indexing algorithms to enable fast and energy-efficient database queries. Secondly, we contribute a framework that extends the functionality and increases the performance of sensornet checkpointing, a debugging and testing technique. Furthermore, we evaluate how different data compression algorithms can be used to decrease the energy consumption and data dissemination time when reprogramming sensor networks. Lastly, we present Velox, a virtual machine for IoT applications. Velox can enforce application-specific resource policies. Through its policy framework and its support for high-level programming languages, Velox helps to secure IoT applications. Our experiments show that Velox monitors applications' resource usage and enforces policies with an energy overhead below 3%. The experimental systems research conducted in this dissertation has had a substantial impact both in the academic community and the open-source software community. Several of the produced software systems and components are included in Contiki, one of the premier open-source operating systems for the IoT and sensor networks, and they are being used both in research projects and commercial products.
4
Magnússon, Sindri. "Bandwidth Limited Distributed Optimization with Applications to Networked Cyberphysical Systems." Doctoral thesis, KTH, Nätverk och systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205682.
Full textAbstract:
The emerging technology of Cyberphysical systems consists of networked computing, sensing, and actuator devices used to monitor, connect, and control physical phenomena. In order to economically and sustainably operate Cyberphysical systems, their devices need to cooperate over a communication network to solve optimization problems. For example, in smart power grids, smart meters cooperatively optimize the grid performance, and in wireless sensor networks a number of sensors cooperate to find optimal estimators of real-world parameters. A challenging aspect in the design of distributed solution algorithms to these optimization problems is that while the technology advances and the networks grow larger, the communication bandwidth available to coordinate the solution remains limited. Motivated by this challenge, this thesis investigates the convergence of distributed solution methods for resource allocation optimization problems, where gradient information is communicated at every iteration, using limited communication. This problem is approached from three different perspectives, each presented in a separate paper. The investigation of the three papers demonstrate promises and limits of solving distributed resource allocation problems using limited communication bandwidth. Future work will consider how even more general problems can be solved using limited communication bandwidth and also study different communication constraints.QC 20170424
5
Sili, Marius. "Progettazione ed implementazione di un'applicazione per la condivisione di stream MIDI." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22142/.
Full textAbstract:
La musica e i metodi attraverso i quali essa viene creata, condivisa e riprodotta hanno sempre avuto importanza per le persone. Nonostante esistano una moltitudine di servizi che permettono lo streaming di prodotti finiti, al giorno d'oggi risulta particolarmente difficile riuscire a suonare e creare brani musicali a distanza, in tempo reale. Non vi è alcun servizio che permetta una gestione semplice e funzionante di tale processo. L'obiettivo della ricerca e del progetto qui presentati è quello di fornire un modo intuitivo in cui un qualsiasi utente provvisto di strumento musicale MIDI e di dispositivi ormai largamente diffusi, come uno smartphone o un tablet, possa effettuare una "Jam Session", cioè una sessione in cui suonare in tempo reale insieme ad altre persone collegate in remoto. I concetti che vengono affrontati sono legati al mondo dell'Internet of Things e della Networked Music Performance. Questa ricerca può portare grandi benefici al processo creativo di brani musicali, alle esibizioni "dal vivo" e alla didattica musicale.
Assieme al progetto, viene descritta una implementazione e uno studio di fattibilità. Si vedrà come il sistema proposto possa essere a tutti gli effetti utilizzato ed eventualmente ampliato in futuro.
6
Karim, Rafid, and Haidara Al-Fakhri. "Smart Door Lock : A first prototype of a networked power lock controller with an NFC interface." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134894.
Full textAbstract:
Most major cell phone manufacturers have been releasing cell phones equipped with Near Field Communication (NFC). At the same time there is also increasing use of mobile payments and user verification with the use of the NFC technology. These trends indicate both the increasing popularity and great potential for increased use of NFC in today’s society. As a result NFC has a huge potential to simplify our everyday tasks, ranging from paying for items to accessing our office or home. In this context we will focus on using NFC together with a Power over Ethernet (PoE) powered circuit board and NFC reader to realize a simple system for granting access to open a locked door. One of the purposes of this realization is to explore what services can be realized when such a system is connected to the home/building network and connected to the Internet. A second purpose is to learn how to use network attached devices, as the concept of the Internet of Things is considered by many to be a driving force in the next generation Internet. This project uses very in expensive and low power hardware, as the number of devices is potentially very large and thus in order to minimize the technology’s impact on the environment we must consider how to minimize the power used – while maintaining the desired user functionality. This bachelor’s thesis project made it possible for a PoE powered circuit board containing a MSP430 microcontroller to work along with a NFC reader, which was connected through the Serial Peripheral Interface (SPI). We hope that the end result of this project will lead to a simpler life by exploiting this increasingly ubiquitous technology. For example, a homeowner could send a one-time key to a repair person who is coming to fix their sink. Similarly a homeowner could send a key to their neighbor which is valid for two weeks so that their neighbor could come into their home to water the plants while they are away on vacation. Another example is lending your apartment key to a friend while you are out of town.Det blir allt vanligare med närfältskommunikation (NFC) i dagens samhälle, mobiltelefons-tillverkarna börjar utveckla nya telefoner med NFC teknik inbyggd, samtidigt som användningen av NFC ökat. Det sker även en utveckling inom mobila betalningar och användar-verifiering med användning av NFC, då NFC förenklar detta. Med detta sagt kommer vi att arbeta med detta i detta kandidatexamens-arbete där vi fokuserar på NFC samt Power over Ethernet som använder MSP430 chippet som kärna. Med dessa enheter kombinerade kommer en enkel rörelse med ett NFC kort över en NFC läsare som sedan skall ge åtkomst till en låst dörr. Detta i större kombination med en Internetuppkoppling kunna ge ägaren möjligheten att kunna skicka ut dörrnycklar till andra användare. I detta kandidatexamensarbete gjorde vi det möjligt för ett PoE kretskort bestående av ett MPS430 mikroprocessor att samarbeta med en NFC läsare genom SPI protokollet. Genom att utveckla detta projekt hoppas vi att vårt slutresultat leder till en enklare delning av nycklar med hjälp av denna teknologi.
7
CUNHA, MARCIO LUIZ COELHO. "CONTEXT DRIVEN THINGS SOCIAL NETWORK." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2010. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=29090@1.
Full textAbstract:
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
A cada dia mais e mais brasileiros possuem um telefone celular de última geração com conexão à internet. Estes novos aparelhos são capazes de ler diferentes tipos de etiquetas usadas para armazenar, recuperar e gerenciar informações, e estão conosco em toda parte para apoiar nossas tarefas diárias. Estes pequenos computadores são conscientes de seu entorno, e propícios à comunicação e colaboração com o mundo real. Devido a sua popularidade, disponibilidade e massa crítica de usuários atingida, novos serviços são desenvolvidos baseados no conceito da computação ubíqua, onde computadores e seres humanos são unificados em torno da noção de ambiente. Estes sistemas pervasivos lidam com questões de interação de contexto e reconhecimento de ambientes, e se adaptam de acordo com as preferências do usuário. Nesta dissertação são descritos o desenvolvimento e testes de usabilidade de uma rede social que é fundamentada nos conceitos da computação ubíqua e Internet das Coisas. Esta rede social, dirigida para o tema da enogastronomia, é acessível por dispositivos móveis e utiliza códigos de duas dimensões colados nas garrafas dos vinhos para através do software e da câmera do celular trazer informações de acordo com o contexto do objeto, lugar e preferência do usuário.
Every day more and more Brazilians have a next generation mobile phone with an internet connection. These new devices are able to read different types of labels used to store, retrieve and manage information; they are with us everywhere to support our daily tasks. These small computers are aware of their surroundings and propitious to communication and collaboration with the real world. Due to their popularity, availability and critical mass of users reached, new services are developed based on the concept of ubiquitous computing, where computers and humans are unified around the concept of environment. These systems deal with issues of pervasive interaction of context, recognition of environments and adapt according to user preferences. This thesis presents a description of the development and usability testing of a social network that is based on the concepts of ubiquitous computing and the Internet of Things. This social network, addressed to the theme of enogastronomy, is accessible by mobile devices and uses twodimensional codes pasted on the bottles of wine for using the software and the phone s camera to bring information in accordance with the context of the object, place and user preference.
8
Iova, Oana-Teodora. "Standards optimization and network lifetime maximization for wireless sensor networks in the Internet of things." Thesis, Strasbourg, 2014. http://www.theses.fr/2014STRAD022/document.
Full textAbstract:
De nouveaux protocoles ont été standardisés afin d'intégrer les réseaux de capteurs sans fil (WSN) dans l'Internet. Parmi eux, RPL pour la couche routage et IEEE 802.15.4 pour la couche MAC. L'objectif de cette thèse est d'améliorer ces protocoles en prenant compte des contraintes énergétiques des dispositifs du WSN. Tout d'abord, nous avons conçu une nouvelle méthode de diffusion dans la norme IEEE 802.15.4, afin d'assurer une livraison fiable des paquets de contrôle des couches supérieures. Ensuite, nous avons fourni une évaluation exhaustive de RPL, en soulignant un problème d'instabilité qui génère une surcharge d'énergie importante. Compte tenu que la durée de vie des WSN est très limitée, nous avons aussi proposé une nouvelle métrique de routage qui identifie les goulets d'étranglement énergétiques afin de maximiser la durée de vie du réseau. Enfin, en couplant cette mesure avec une version multiparent de RPL, nous avons résolu le problème d'instabilité souligné précédemmentNew protocols have been standardized in order to integrate Wireless Sensor Networks (WSN) in the Internet. Among them, the IEEE 802.15.4 MAC layer protocol, and RPL, the IPv6 Routing Protocol for Low-power and Lossy Networks. The goal of this thesis is to improve these protocols, considering the energy constraints of the devices that compose the WSN. First, we proposed a new MAC layer broadcast mechanism in IEEE 802.15.4, to ensure a reliable delivery of the control packets from the upper layers (especially from RPL). Then, we provided an exhaustive evaluation of RPL and highlighted an instability problem. This instability generates a large overhead, consuming a lot of energy. Since the lifetime of WSN is very limited, we proposed a new routing metric that identifies the energy bottlenecks and maximizes the lifetime of the network. Finally, by coupling this metric with a multipath version of RPL, we are able to solve the instability problem previously highlighted
9
Carlquist, Johan. "Evaluating the use of ICN for Internet of things." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-343368.
Full textAbstract:
The market of IOT devices continues to grow at a rapid speed as well as constrained wireless sensor networks. Today, the main network paradigm is host centric where a users have to specify which host they want to receive their data from. Information-centric networking is a new paradigm for the future internet, which is based on named data instead of named hosts. With ICN, a user needs to send a request for a perticular data in order to retrieve it. When sent, any participant in the network, router or server, containing the data will respond to the request. In order to achieve low latency between data creation and its consumption, as well as being able to follow data which is sequentially produced at a fixed rate, an algortihm was developed. This algortihm calculates and determines when to send the next interest message towards the sensor. It uses a ‘one time subscription’ approach to send its interest message in advance of the creation of the data, thereby enabling a low latency from data creation to consumption. The result of this algorithm shows that a consumer can retrieve the data with minimum latency from its creation by the sensor over an extended period of time, without using a publish/subscribe system such as MQTT or similar which pushes their data towards their consumers. The performance evaluation carried out which analysed the Content Centric Network application on the sensor shows that the application has little impact on the overall round trip time in the network. Based on the results, this thesis concluded that the ICN paradigm, together with a ’one-time subscription’ model, can be a suitable option for communication within the IoT domain where consumers ask for sequentially produced data.
10
GUCCIARDO, Michele. "Challenges and opportunities in emerging high-density wireless networks." Doctoral thesis, Università degli Studi di Palermo, 2020. http://hdl.handle.net/10447/396244.
Full text
11
Cobârzan, Cosmin. "Internet of highly mobile things." Thesis, Strasbourg, 2015. http://www.theses.fr/2015STRAD037/document.
Full textAbstract:
La mobilité devienne un partie intégrante de l’Internet des Object d’aujourd’hui, comme beaucoup d’applications (monitorage des animaux sauvage, suivi des cible dans le champs de bataille) sont impossible de mettre en œuvre juste avec des nœuds statiques. L’objective de cette thèse est de définir une nouvelle architecture de communication articule autour de la mobilité dans les réseaux avec pertes et à bas puissance (Low Power and Lossy Networks - LLNs) (réseaux des capteurs sans fils). Tout d’abord, nous avons analysé théoriquement l’auto configuration des adresses IPv6, fait avec toutes les optimisations disponibles dans Neighbor Discovery Optimization for IPv6 over 6LoWPAN. Cette étape est cruciale pour des protocoles qui donnent de support pour la mobilité dans des réseaux IP, comme MIPv6. Les résultats obtenues – taille des paquets trop grande et consumations énergétique importante pour les routeurs qui tournent Neighbor Discovery – n’ont amener a utiliser le IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). RPL est développe d’el debout pour les LLN. Notre deuxième contribution sont améliorer les opérations du RPL pour mieux supporter les nœuds mobiles. Enfin, nous avons développe une mécanisme inter-couche – Mobility Triggered-RPL – qui profite des actions dans le protocole avec préambule X-Machiavel à la couche accès au medium dans le protocole RPL à la couche routageMobility is becoming an integrating part of todays Internet of Things, as many applications such as wildlife monitoring or target tracking in the battlefield cannot be done only with the help of static nodes. The goal of this thesis is to provide new communication architecture articulated around providing mobility support in Low Power and Lossy Networks (LLNs). First we analyzed from a theoretical point of view the IPv6 address auto-configuration with all optimizations made in Neighbor Discovery Optimization for IPv6 over 6LoWPAN. This step is of crucial importance for protocols that offer mobility support in IP networks, such as MIPv6. Our findings, increased message size that leads to fragmentation and high energy consumption for routers that are involved in Neighbor Discovery message exchange, have lead us to use the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) in order to provide mobility support. RPL is build from ground up with respect to LLN requirements. Our second contribution enhanced RPL operations to support mobility management. Finally, we proposed a cross-layer protocol – Mobility Triggered-RPL – that leverages actions from the X-Machiavel preamble sampling MAC protocol into RPL
12
Hassan, Basma Mostafa. "Monitoring the Internet of Things (IoT) Networks." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS100.
Full textAbstract:
Les réseaux « Internet des Objets » se composent de plusieurs millions d’objets qui possèdent une adresse IP et qui peuvent connecter sur Internet. En général, ces objets sont supposé d’être autonomes et peuvent résoudre des tâches; mesurer, traiter et fournir des informations pour les systèmes connectés et pour les utilisateurs. Aussi, ces réseaux sont vulnérables (c.-à-d. : les éléments peuvent être mobiles et la topologie du réseau peut changer dynamiquement), les changements peuvent influencer le (bon) fonctionnement du réseau. De plus, ils peuvent être alimentés par des batteries de durée de vie limitée, ce que nécessite la réduction de leur consommation.Ce travail de thèse aborde un sujet important dans le domaine de l’Internet des Objets, qui consiste à savoir comment assurer la robustesse et le fonctionnement tolérant aux pannes du réseau pour répondre aux exigences des missions critiques. Avec le large déploiement des services IdO, ce problème est deventé ou de détection de pannes et de sécurité industriel où l’état des objets communicants doit être constamment vérifié pour le rétablissement rapide en cas de problème particulièrement crucial pour les applications telles que le monitorage intelligent de sames de communication inattendus. On cherche alors de minimiser le coût du monitorage et l’utilisation de l’énergie, et aussi les charges additionnelles sur les réseaux.Nous avons proposé un algorithme qui vise à réaliser un placement distribué des moniteurs avec une complexité minimale pour le calcul. L’algorithme proposé fonctionne avec RPL. L’objectif principal est d’augmenter la robustesse dans les réseaux IdO ciblant les applications critiques en temps réel via le monitorage des liaisons dans les DODAGs construits par RPL. Dans notre première contribution, le problème est modélisé comme un problème de couverture minimale des sommets (VCP) sur le DODAG. Nous avons développé un algorithme à temps polynomial qui transforme le DODAG en une décomposition arborescente (Nice-Tree Decomposition) avec une largeur arborescente (treewidth) d’unité. Cette stratégie profite de la spécificité des DODAG et a abouti à une réduction significative de la complexité de la résolution du VCP sur les DODAG. Elle peut être résolue en temps polynomial.La deuxième proposition est un modèle approché pour l’optimisation de l’ordonnancement du rôle de monitorage des nœuds dans les réseaux IdO, afin de maximiser la durée de vie des dispositifs embarqués à ressources limitées, tout en minimisant le coût global du monitorage de réseau. Le monitorage de réseau est très coûteux, en particulier pour les réseaux à ressources limitées tels que l’IdO. Par conséquent, le monitorage doit être économe en énergie et avec des frais généraux minimaux sur la performance normale du réseau. Notre travail correspondant contient une proposition d’un modèle mathématique en trois phases pour assurer l’exigence d’une couverture des moniteurs tout en minimisant la consommation d’énergie de monitorage et les frais de communication.Notre modèle proposé décompose le problème abordé en trois problèmes d’optimisation bien connus, il s’agit du problème de couverture de sommets, problème d’affectation généralisé multi-objectives et problème de voyageur de commerce.Dans cette troisième partie, une approche exacte est proposée pour résoudre le problème décrit dans (Contribution 2). Comme nous avons vu, la décomposition en trois phases ne donne pas la solution exacte. Nous avons donc proposé une formulation exacte du problème qui consiste en un problème de l'affectation minimum des tâches de surveillance avec un fonctionnement de surveillance cyclique. Pour cela, nous avons formulé un programme en nombres entiers binaires. L'ordonnancement optimal garantit la couverture du graphe pour la surveillance avec une consommation d'énergie minimaleBy connecting billions of things to the Internet, IoT created a plethora of applications that touch every aspect of human life. Time-sensitive, mission-critical services, require robust connectivity and strict reliability constraints. On the other hand, the IoT relies mainly on Low-power Lossy Networks, which are unreliable by nature due to their limited resources, hard duty cycles, dynamic topologies, and uncertain radio connectivity. Faults in LLNs are common rather than rare events, therefore, maintaining continuous availability of devices and reliability of communication, are critical factors to guarantee a constant, reliable flow of application data.After a comprehensive literature review, and up to our knowledge, it is clear that there is a call for a new approach to monitoring the unreliable nodes and links in an optimized, energy-efficient, proactive manner, and complete interoperability with IoT protocols. To target this research gap, our contributions address the correct assignment (placement) of the monitoring nodes. This problem is known as the minimum assignment problem, which is NP-hard. We target scalable monitoring by mapping the assignment problem into the well-studied MVC problem, also NP-hard. We proposed an algorithm to convert the DODAG into a nice-tree decomposition with its parameter (treewidth) restricted to the value one. As a result of these propositions, the monitor placement becomes only Fixed-Parameter Tractable, and can also be polynomial-time solvable.To prolong network longevity, the monitoring role should be distributed and balanced between the entire set of nodes. To that end, assuming periodical functioning, we propose in a second contribution to schedule between several subsets of nodes; each is covering the entire network. A three-phase centralized computation of the scheduling was proposed. The proposition decomposes the monitoring problem and maps it into three well-known sub-problems, for which approximation algorithms already exist in the literature. Thus, the computational complexity can be reduced.However, the one major limitation of the proposed three-phase decomposition is that it is not an exact solution. We provide the exact solution to the minimum monitor assignment problem with a duty-cycled monitoring approach, by formulating a Binary Integer Program (BIP). Experimentation is designed using network instances of different topologies and sizes. Results demonstrate the effectiveness of the proposed model in realizing full monitoring coverage with minimum energy consumption and communication overhead while balancing the monitoring role between nodes.The final contribution targeted the dynamic distributed monitoring placement and scheduling. The dynamic feature of the model ensures real-time adaptation of the monitoring schedule to the frequent instabilities of networks, and the distributed feature aims at reducing the communication overhead
13
Armide, Misikir, and Herbert Ecker. "Combining the Good Things from Vehicle Networks and High-Performance Networks." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-657.
Full textAbstract:
The aim of this Master’s thesis is to develop a solution for combining speed and performance of switched Ethernet with the real time capability and determinism of sophisticated in- vehicle networks. After thorough research in vehicle network standards, their demands and features, the
Flexible Time Division Multiple Access (FTDMA) protocol of FlexRay was chosen to be applied on a switched Ethernet architecture since it can accommodate both hard real time tasks and soft real time tasks. To provide hard real time capability, what this paper focuses on, a media access method was developed by creating static TDMA schedules for each node’s sending and receiving
port according to a certain traffic assumption. To validate the developed media access algorithm several examples with different traffic assumptions and architectures were generated and
investigated based on their sending and receiving utilization. A second method for validating and thus proving the functionality of the algorithm was by simulation. Therefore the Matlab Simulink
media library extension TRUE TIME was used to simulate a simple example with 100% sending and receiving utilization for each node.
14
KALYONCU, Samet. "Wireless Solutions and Authentication Mechanisms for Contiki Based Internet of Things Networks." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-27158.
Full textAbstract:
Internet of Things, is a new expression described as the future of the internet, promises a new world surrounded by tiny smart objects interacting with the environment, communicating with each other, and controlled over internet. Investigating which low power wireless solution and authentication mechanism fits best for IoT networks, and applying these technologies on simulator and real hardware is the main task of this project. Bluetooth Low Energy, ANT, 6LoWPAN and ZigBee are investigated low power wireless technologies which might be used to create an IoT network. Yet, BLTE and ANT have narrower application areas compared to the others, therefore ZigBee and 6LoWPAN technologies are investigated in depth and compared as the 2 promising solutions for implementation and integration of Internet of things concept. SPINS, TinySec, TinyECC, SenSec, MiniSec, ContikiSec and AES CCM are the main security frameworks especially designed for wireless sensor networks providing confidentiality, authentication and integrity. These frameworks were described and compared to find out most suitable authentication mechanism for IoT networks. Contiki OS is used as the operating system of nodes during the implementation of network both on simulator Cooja and real hardware. ZigBee and 6LoWPAN were compared considering interoperability, packet overhead, security and availability. As a result 6LoWPAN came forward due to providing high interoperability and slightly less packet overhead features. ZigBee devices require extra hardware to operate with different technologies. Among the discussed security frameworks, ContikiSec and AES CCM were highlighted because of flexibility, providing different levels of security. Resource limited characteristic and diversity of IoT applications make flexibility a very useful feature while implementing a security framework. Experiments committed to implement a working IoT network were not hundred percent successful. 6LoWPAN was successfully implemented but implementation of the security framework was failed due to compatibility issues between the sensor and the router node. Firmware of the sensor node is not designed to provide any kind of security, therefore security features of the router node is also disabled.
15
THEKKE, KANAPRAM DIVYA. "Ego things: Networks Of Self-Aware Intelligent Objects." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1048455.
Full textAbstract:
There is an increasing demand for developing intelligence and awareness in artificial agents in recent days to improve autonomy, robustness, and scalability, and it has been investigated in various research fields such as machine learning, robotics, software engineering, etc. Moreover, it is crucial to model such an agent's interaction with the surrounding environment and other agents to represent collaborative tasks. In this thesis, we have proposed several approaches to developing multi-modal self-awareness in agents and multi-modal collective awareness (CA) for multiple networked intelligent agents by focusing on the functionality to detect abnormal situations.
The first part of the thesis is proposed a novel approach to build self-awareness in dynamic agents to detect abnormalities based on multi-sensory data and feature selection. By considering several sensory data features, learned multiple inference models and facilitated obtaining the most distinct features for predicting future instances and detecting possible abnormalities. The proposed method can select the optimal set features to be shared in networking operations such that state prediction, decision-making, and abnormality detection processes are favored.
In the second part, proposed different approaches for developing collective awareness in an agent's network. Each agent of a network is considered an Internet of Things (IoT) node equipped with machine learning capabilities. The collective awareness aims to provide the network with updated causal knowledge of the state of execution of actions of each node performing a joint task, with particular attention to anomalies that can arise. Data-driven dynamic Bayesian models learned from multi-sensory data recorded during the normal realization of a joint task (agent network experience) are used for distributed state estimation of agents and detection of abnormalities. Moreover, the effects of networking protocols and communications in the estimation of state and abnormalities are analyzed.
Finally, the abnormality estimation is performed at the model's different abstraction levels and explained the models' interpretability. In this work, interpretability is the capability to use anomaly data to modify the model to make inferences accurately in the future.
16
Okumura, Brandon M. "IoTA: Internet of Things Assistant." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1769.
Full textAbstract:
The Internet of Things is the networking of electronic devices, or “Things”, that enables them to collect and share data, as well as interact with their physical surround- ings. Analyzing this collected data allows us to make smarter economic decisions. These interconnected networks are usually driven by low-powered micro-controllers or cheap CPUs that are designed to function optimally with very little hardware. As scale and computational requirements increase, these micro-controllers are unable to grow without being physically replaced.
This thesis proposes a system, IoTA, that assists the Internet of Things by pro- viding a shared computational resource for endpoint devices. This solution extends the functionality of endpoint devices without the need of physical replacement. The IoTA system is designed to be easily integrable to any existing IoT network.
This system presents a model that allows for seamless processing of jobs submitted by endpoint devices while keeping scalability and flexibility in mind. Additionally, IoTA is built on top of existing IoT protocols. Evaluation shows there is a significant performance benefit in processing computationally heavy algorithms on the IoTA system as compared to processing them locally on the endpoint devices themselves.
17
Ramos, Alex Lacerda. "Network security metrics for the Internet of things." Universidade de Fortaleza, 2018. http://dspace.unifor.br/handle/tede/108423.
Full textAbstract:
Made available in DSpace on 2019-03-30T00:02:10Z (GMT). No. of bitstreams: 0
Previous issue date: 2018-11-26Recent advances in networking technologies, such as the IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) standard, have allowed to interconnect wireless sensor networks (WSNs) to the Internet, thus forming the Internet of Things (IoT). Despite the availability of different message security mechanisms, sensor networks are still vulnerable to several types of attack. To identify such attacks, an Intrusion Detection System (IDS) can be deployed. However, IDSs can generate several false positives and false negatives. Moreover, the alerts raised by IDSs provide no information regarding the impact an attack has on the security of a sensor network. As a consequence, it becomes difficult for WSN administrators and users to take proper responsive actions when attacks occur. To address these issues, this thesis proposes three security metrics. The first metric, called Trust Probability, quantifies by how much an IDS output could be trusted (to be correct). Such metric can help administrators decide which alerts deserve careful attention or which alerts might be safely ignored. Since this type of metric provides a measure of IDS effectiveness, it can also be used to compare different IDSs as well as to fine-tune a given IDS. The second metric, named Damage Level, quantifies the severity of an attack. This metric, when combined with the Trust Probability metric, enables the administrator to correctly prioritize and respond to alerts by evaluating them in terms of accuracy and attack impact. Finally, the third metric, namely Data Security Level, quantifies the degree to which sensor data can be trusted when the sensor is under attack. The security situational awareness provided by this metric helps WSN users make better decisions about the use of the gathered sensor data. Experimental results show that the proposed metrics can accurately quantify security level with low performance overhead and power consumption. Keywords: Network Security Metrics, Quantitative Security Analysis, Security Situational Awareness, Internet of Things, Wireless Sensor Networks.
Recentes avanços nas tecnologias de rede, tais como o padrão IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN), permitiram a interconexão de redes de sensores sem fio (RSSF) à Internet, formando assim a Internet das Coisas (Internet of Things -- IoT). Apesar da disponibilidade de diferentes mecanismos de segurança de mensagens, as redes de sensores ainda são vulneráveis a vários tipos de ataques. Para identificar esses ataques, um Sistema de Detecção de Intrusão (Intrusion Detection System -- IDS) pode ser implantado. No entanto, os IDSs podem gerar vários falsos positivos e falsos negativos. Além disso, os alertas gerados pelos IDSs não fornecem nenhuma informação sobre o impacto de um ataque sobre a segurança de uma RSSF. Consequentemente, torna-se difícil para os administradores e usuários da rede tomarem as devidas ações responsivas quando ataques ocorrerem. Para tratar estas questões, esta tese propõe três métricas de segurança. A primeira delas, chamada Trust Probability, quantifica o quão confiável (correto) é um output de um IDS. Essa métrica pode ajudar os administradores a decidir quais alertas merecem mais atenção ou quais podem ser ignorados com segurança. Já que essa métrica fornece uma medida da efetividade de um IDS, ela também pode ser usada para comparar diferentes IDSs, bem como para otimizar um dado IDS. A segunda métrica, denominada Damage Level, quantifica a gravidade de um ataque. Esta métrica, quando combinada com a Trust Probability, permite ao administrador priorizar e responder corretamente a alertas, avaliando-os em termos de precisão e impacto de ataque. Por fim, a terceira métrica, chamada de Data Security Level, quantifica quão confiáveis os dados dos sensores são quando a rede está sob ataque. Conhecer a informação fornecida por esta métrica ajuda os usuários a tomar melhores decisões sobre o uso dos dados coletados pelos sensores. Os resultados experimentais mostram que as métricas propostas podem quantificar com precisão o nível de segurança da rede, com baixo consumo de energia e sobrecarga de desempenho. Palavras-chave:Métricas de Segurança de Rede, Análise Quantitativa de Segurança, Consciência Situacional de Segurança, Internet das Coisas, Redes de Sensores sem Fio.
18
Azari, Amin. "Energy Efficient Machine-Type Communications over Cellular Networks : A Battery Lifetime-Aware Cellular Network Design Framework." Licentiate thesis, KTH, Kommunikationssystem, CoS, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-194416.
Full textAbstract:
Internet of Things (IoT) refers to the interconnection of uniquely identifiable smart devices which enables them to participate more actively in everyday life. Among large-scale applications, machine-type communications (MTC) supported by cellular networks will be one of the most important enablers for the success of IoT. The existing cellular infrastructure has been optimized for serving a small number of long-lived human-oriented communications (HoC) sessions, originated from smartphones whose batteries are charged in a daily basis. As a consequence, serving a massive number of non-rechargeable machine-type devices demanding a long battery lifetime is a big challenge for cellular networks. The present work is devoted to energy consumption modeling, battery lifetime analysis, and lifetime-aware network design for massive MTC services over cellular networks. At first, we present a realistic model for energy consumption of machine devices in cellular connectivity, which is employed subsequently in deriving the key performance indicator, i.e. network battery lifetime. Then, we develop an efficient mathematical foundation and algorithmic framework for lifetime-aware clustering design for serving a massive number of machine devices. Also, by extending the developed framework to non-clustered MTC, lifetime-aware uplink scheduling and power control solutions are derived. Finally, by investigating the delay, energy consumption, spectral efficiency, and battery lifetime tradeoffs in serving coexistence of HoC and MTC traffic, we explore the ways in which energy saving for the access network and quality of service for HoC traffic can be traded to prolong battery lifetime for machine devices. The numerical and simulation results show that the proposed solutions can provide substantial network lifetime improvement and network maintenance cost reduction in comparison with the existing approaches.QC 20161103
19
Bhebhe, Mbongeni. "Performance of narrow band internet of things (NBIoT) networks." Master's thesis, Faculty of Engineering and the Built Environment, 2019. http://hdl.handle.net/11427/31533.
Full textAbstract:
Narrow Band Internet of Things (NBIoT) is a Low Power Wide Area Network (LPWAN) technology that has been standardised by 3GPP in Release 13 to work in cellular networks [15]. The main characteristics of NBIoT are its extended coverage compared to other cellular technologies such as LTE; its high capacity is due to its narrow channel bandwidth of 180 KHz, which also supports the possibility of these devices having a long battery life of up to 10 years, as well as low device complexity - all of which result in low device costs [2]. NBIoT can be deployed in one of three different options, namely: a) standalone, b) in-band and c) guard band deployment mode. These characteristics of NBIoT makes it very useful in the IoT industry, allowing the technology to be used in a wide range of applications, such as health, smart cities, farming, wireless sensor networks and many more [1] [25]. NBIoT can be used to realise the maximum possible spectral efficiency, thereby increasing the capacity of the network. Penetration of NBIoT in the market has dominated other LPWANs like Sigfox and LoRA, with NBIoT having a technology share of close to 50 percent [31]. This study is aimed at exploring the deployment options of NBIoT and determining how network operators can realise the greatest value for their investment by efficiently utilising their allocated spectrum. The main target is to derive the best parameter combination for deployment of the NBIoT network with acceptable error rates in both the uplink and the downlink. Different characteristics of NBIoT were discussed in this study, and the performance of the various approaches investigated to determine their efficiency in relation to the needs of the IoT industry. The error rates of NBIoT, when used in an existing LTE network, were the main focus of this study. Software simulations were used to compare the different parameter settings to see which options provide the best efficiency and cost trade-offs for structuring an NBIoT network. The results of the tests done in this study showed that the error rates are lower for standalone deployment mode than for in-band mode, which is mainly due to less interference in standalone mode than in in-band mode. The results also show that data transmitted in smaller Transport Block Size (TBS) in the Down Link (DL) has less errors than if it’s transmitted in larger blocks. The results also show that the error rate gets lower as the number of subframe repetition increases in the downlink, which is mainly due to the redundancy in sending the same data multiple times. However in the uplink, the results show that the error rates are comparable when the signal has poor quality.
20
Besson, Lilian. "Multi-Players Bandit Algorithms for Internet of Things Networks." Thesis, CentraleSupélec, 2019. http://www.theses.fr/2019CSUP0005.
Full textAbstract:
Dans cette thèse de doctorat, nous étudions les réseaux sans fil et les appareils reconfigurables qui peuvent accéder à des réseaux de type radio intelligente, dans des bandes non licenciées et sans supervision centrale. Nous considérons notamment des réseaux actuels ou futurs de l’Internet des Objets (IoT), avec l’objectif d’augmenter la durée de vie de la batterie des appareils, en les équipant d’algorithmes d’apprentissage machine peu coûteux mais efficaces, qui leur permettent d’améliorer automatiquement l’efficacité de leurs communications sans fil. Nous proposons deux modèles de réseaux IoT, et nous montrons empiriquement, par des simulations numériques et une validation expérimentale réaliste, le gain que peuvent apporter nos méthodes, qui se reposent sur l’apprentissage par renforcement. Les différents problèmes d’accès au réseau sont modélisés avec des Bandits Multi-Bras (MAB), mais l’analyse de la convergence d’un grand nombre d’appareils jouant à un jeu collaboratif sans communication ni aucune coordination reste délicate, lorsque les appareils suivent tous un modèle d’activation aléatoire. Le reste de ce manuscrit étudie donc deux modèles restreints, d’abord des banditsmulti-joueurs dans des problèmes stationnaires, puis des bandits mono-joueur non stationnaires. Nous détaillons également une autre contribution, la bibliothèque Python open-source SMPyBandits, qui permet des simulations numériques de problèmes MAB, qui couvre les modèles étudiés et d’autresIn this PhD thesis, we study wireless networks and reconfigurable end-devices that can access Cognitive Radio networks, in unlicensed bands and without central control. We focus on Internet of Things networks (IoT), with the objective of extending the devices’ battery life, by equipping them with low-cost but efficient machine learning algorithms, in order to let them automatically improve the efficiency of their wireless communications. We propose different models of IoT networks, and we show empirically on both numerical simulations and real-world validation the possible gain of our methods, that use Reinforcement Learning. The different network access problems are modeled as Multi-Armed Bandits (MAB), but we found that analyzing the realistic models was intractable, because proving the convergence of many IoT devices playing a collaborative game, without communication nor coordination is hard, when they all follow random activation patterns. The rest of this manuscript thus studies two restricted models, first multi-players bandits in stationary problems, then non-stationary single-player bandits. We also detail another contribution, SMPyBandits, our open-source Python library for numerical MAB simulations, that covers all the studied models and more
21
Tuyishimire, Emmanuel. "Internet of Things: Least Interference Beaconing Algorithms." Thesis, University of Cape Town, 2014. http://pubs.cs.uct.ac.za/archive/00000997/.
Full textAbstract:
The emerging sensor networking applications are predicting the deployment of sensor devices in thousands of computing elements into multi-technology and multi-protocol platforms. Access to information will be available not only anytime and anywhere, but also using anything in a first-mile of the Internet referred to as the internet-of-things (IoT).
The management of such a large-scale and heterogeneous network, would benefit from some of the traditional IP-based network management techniques such as load and energy balancing, which can be re-factored to achieve efficient routing of sensor network traffic.
Research has shown that minimizing the path interference on nodes was necessary to improve traffic engineering in connection oriented networks. The same principle has been applied in past research in the context of the IoT to reveal that the least interference beaconing protocol (LIBP); a protocol derived
from the least interference beaconing algorithm (LIBA) outperforms the Collection Tree Protocol (CTP) and Tiny OS Beaconing (ToB) protocol, in terms of energy efficiency and lifetime of the sensor network. However for the purpose of efficiency and accuracy, it is relevant, useful and critical to revisit or re-examine the LIBA algorithm in terms of correctness and investigate potential avenues for improvement.
The main contributions of this research work are threefold. Firstly, we build upon formal methods to verify the correctness of the main principles underlying the LIBA, in terms of energy efficiency and interference minimization. The interference is here defined at each node by the number of routing paths carrying the sensor readings from the motes to the sink of the network that traverse the node. Our findings reveal the limitations in LIBA. Secondly, building upon these limitations, we propose two improvements to the algorithm: an algorithm called LIBA+ that improves the algorithm performance by keeping track of the energy usage of the sensor nodes, and a multi-sink version of the algorithm called LIBAMN that extends the algorithm to account for multiple sinks or gateways. These enhancements present preventive mechanisms to include in IoT platforms in order to improve traffic engineering, the security of network protocols and network stability. Lastly, we present analytical results, which reveal that the LIBA algorithm can be improved by more than 84% in terms of energy balancing. These results reveal that formal methods remain essential in the evaluation and performance improvement of wireless sensor network algorithms and protocols.
22
Djamaa, B. "Pervasive service discovery in low-power and lossy networks." Thesis, Cranfield University, 2016. http://dspace.lib.cranfield.ac.uk/handle/1826/10670.
Full textAbstract:
Pervasive Service Discovery (SD) in Low-power and Lossy Networks (LLNs) is expected to play a major role in realising the Internet of Things (IoT) vision. Such a vision aims to expand the current Internet to interconnect billions of miniature smart objects that sense and act on our surroundings in a way that will revolutionise the future. The pervasiveness and heterogeneity of such low-power devices requires robust, automatic, interoperable and scalable deployment and operability solutions. At the same time, the limitations of such constrained devices impose strict challenges regarding complexity, energy consumption, time-efficiency and mobility.
This research contributes new lightweight solutions to facilitate automatic deployment and operability of LLNs. It mainly tackles the aforementioned challenges through the proposition of novel component-based, automatic and efficient SD solutions that ensure extensibility and adaptability to various LLN environments. Building upon such architecture, a first fully-distributed, hybrid pushpull SD solution dubbed EADP (Extensible Adaptable Discovery Protocol) is proposed based on the well-known Trickle algorithm. Motivated by EADPs’ achievements, new methods to optimise Trickle are introduced. Such methods allow Trickle to encompass a wide range of algorithms and extend its usage to new application domains. One of the new applications is concretized in the TrickleSD protocol aiming to build automatic, reliable, scalable, and time-efficient SD. To optimise the energy efficiency of TrickleSD, two mechanisms improving broadcast communication in LLNs are proposed. Finally, interoperable standards-based SD in the IoT is demonstrated, and methods combining zero-configuration operations with infrastructure-based solutions are proposed.
Experimental evaluations of the above contributions reveal that it is possible to achieve automatic, cost-effective, time-efficient, lightweight, and interoperable SD in LLNs. These achievements open novel perspectives for zero-configuration capabilities in the IoT and promise to bring the ‘things’ to all people everywhere.
23
Shahid, Mustafizur Rahman. "Deep learning for Internet of Things (IoT) network security." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAS003.
Full textAbstract:
L’internet des objets (IoT) introduit de nouveaux défis pour la sécurité des réseaux. La plupart des objets IoT sont vulnérables en raison d'un manque de sensibilisation à la sécurité des fabricants d'appareils et des utilisateurs. En conséquence, ces objets sont devenus des cibles privilégiées pour les développeurs de malware qui veulent les transformer en bots. Contrairement à un ordinateur de bureau, un objet IoT est conçu pour accomplir des tâches spécifiques. Son comportement réseau est donc très stable et prévisible, ce qui le rend bien adapté aux techniques d'analyse de données. Ainsi, la première partie de cette thèse tire profit des algorithmes de deep learning pour développer des outils de surveillance des réseaux IoT. Deux types d'outils sont explorés: les systèmes de reconnaissance de type d’objets IoT et les systèmes de détection d'intrusion réseau IoT. Pour la reconnaissance des types d’objets IoT, des algorithmes d'apprentissage supervisé sont entrainés pour classifier le trafic réseau et déterminer à quel objet IoT le trafic appartient. Le système de détection d'intrusion consiste en un ensemble d'autoencoders, chacun étant entrainé pour un type d’objet IoT différent. Les autoencoders apprennent le profil du comportement réseau légitime et détectent tout écart par rapport à celui-ci. Les résultats expérimentaux en utilisant des données réseau produites par une maison connectée montrent que les modèles proposés atteignent des performances élevées. Malgré des résultats préliminaires prometteurs, l’entraînement et l'évaluation des modèles basés sur le machine learning nécessitent une quantité importante de données réseau IoT. Or, très peu de jeux de données de trafic réseau IoT sont accessibles au public. Le déploiement physique de milliers d’objets IoT réels peut être très coûteux et peut poser problème quant au respect de la vie privée. Ainsi, dans la deuxième partie de cette thèse, nous proposons d'exploiter des GAN (Generative Adversarial Networks) pour générer des flux bidirectionnels qui ressemblent à ceux produits par un véritable objet IoT. Un flux bidirectionnel est représenté par la séquence des tailles de paquets ainsi que de la durée du flux. Par conséquent, en plus de générer des caractéristiques au niveau des paquets, tel que la taille de chaque paquet, notre générateur apprend implicitement à se conformer aux caractéristiques au niveau du flux, comme le nombre total de paquets et d'octets dans un flux ou sa durée totale. Des résultats expérimentaux utilisant des données produites par un haut-parleur intelligent montrent que notre méthode permet de générer des flux bidirectionnels synthétiques réalistes et de haute qualitéThe growing Internet of Things (IoT) introduces new security challenges for network activity monitoring. Most IoT devices are vulnerable because of a lack of security awareness from device manufacturers and end users. As a consequence, they have become prime targets for malware developers who want to turn them into bots. Contrary to general-purpose devices, an IoT device is designed to perform very specific tasks. Hence, its networking behavior is very stable and predictable making it well suited for data analysis techniques. Therefore, the first part of this thesis focuses on leveraging recent advances in the field of deep learning to develop network monitoring tools for the IoT. Two types of network monitoring tools are explored: IoT device type recognition systems and IoT network Intrusion Detection Systems (NIDS). For IoT device type recognition, supervised machine learning algorithms are trained to perform network traffic classification and determine what IoT device the traffic belongs to. The IoT NIDS consists of a set of autoencoders, each trained for a different IoT device type. The autoencoders learn the legitimate networking behavior profile and detect any deviation from it. Experiments using network traffic data produced by a smart home show that the proposed models achieve high performance.Despite yielding promising results, training and testing machine learning based network monitoring systems requires tremendous amount of IoT network traffic data. But, very few IoT network traffic datasets are publicly available. Physically operating thousands of real IoT devices can be very costly and can rise privacy concerns. In the second part of this thesis, we propose to leverage Generative Adversarial Networks (GAN) to generate bidirectional flows that look like they were produced by a real IoT device. A bidirectional flow consists of the sequence of the sizes of individual packets along with a duration. Hence, in addition to generating packet-level features which are the sizes of individual packets, our developed generator implicitly learns to comply with flow-level characteristics, such as the total number of packets and bytes in a bidirectional flow or the total duration of the flow. Experimental results using data produced by a smart speaker show that our method allows us to generate high quality and realistic looking synthetic bidirectional flows
24
Putchala, Manoj Kumar. "Deep Learning Approach for Intrusion Detection System (IDS) in the Internet of Things (IoT) Network using Gated Recurrent Neural Networks (GRU)." Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1503680452498351.
Full text
25
Abade, Pedro António Carvalho. "VR-Banway: deploying a body area network gateway on single-board computers and mesh networks." Master's thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23569.
Full textAbstract:
Mestrado em Engenharia de Computadores e TelemáticaInternet of Things (IoT) is a generic category of ICT architectures that includes the use of sensor-based, communication-enabled systems. A common architectural element in IoT is the sensors gateway that collects data from nearby sensors and relays them to higher-order remote services. The VR2Market project, in which this work is integrated, uses two implementations of the gateway, based on Android smartphones and RPI boards. With the new proposed IoT-inspired computing module, it is possible to migrate gateways to a smaller, more efficient hardware, while retaining the high-level programming abstraction. In this work, we propose and implement a new version of the gateway, named VR-Banway, using the Intel Edison compute module, taking into consideration the integration with additional service layers in VR2Market system, especially with respect to the required Ad hoc networks support. VR-Banway proved to be a solution capable of replacing the existing gateway component in the VR2Market system. The new approach uses a smaller module, reduces power consumption and is more portable. VR-Banway has been used in the context of firefighters monitoring, but is ready to be deployed in other domains.
A Internet of Things (IoT) é uma categoria genérica das arquiteturas de TIC que inclui o uso de sistemas baseados em sensores e comunicações. Um elemento comum das arquiteturas IoT é o agregador que recolhe dados de sensores nas proximidades e reencaminha-os para serviços remotos de mais alto nível. O projeto VR2Market, no qual este trabalho está integrado, usa duas implementações do agregador de dados, implementados em Android e RPI. Com o novo módulo proposto, inspirado na IoT, é possível migrar os agregadores de dados para dispositivos mais pequenos e mais eficientes mantendo a abstração de programação de alto nível. Neste trabalho, propomos e implementamos uma nova versão do agregador de dados, chamado VR-Banway, usando o módulo computacional Intel Edison, tendo em consideração a integração de novas camadas de serviços no VR2Market, especialmente no que diz respeito ao suporte de redes Ad hoc. VR-Banway provou ser uma solução capaz de substituir o componente de agregador de dados existente no sistema VR2Market. A nova abordagem usa um módulo mais pequeno, reduz o consumo de energia e é mais portátil. VR-Banway foi usado no contexto de monitorização de bombeiros, mas está preparado para ser implementado noutros domínios.
26
Seekins, Ryan N. (Ryan Nicholas). "The Internet of things applied to command and control networks." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106263.
Full textAbstract:
Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2016.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 92-96).
The number of people and things connected to the Internet continue growing at an exponential rate. This record setting growth along with the reduction in small sensor costs and machine learning enabled a concept called the Internet of Things (IoT) to thrive. With numerous applications in both commercial and government spaces, the IoT has the ability to transform any organizations network capabilities. The Air Force has a unique set of requirements centered on cyberspace superiority and the ability to command and control people and things. This paper leverages the traditional systems engineering "'V" model as a framework to develop and analyze a concept for an Air Force command and control network. Methods and tools such as stakeholder analysis, hierarchical control structures and object-process diagrams are used to develop the concept of operations, system architecture, and the preliminary design. The programs technology readiness is also assessed before outlining key milestones and deliverables required for transitioning the program forward in the acquisition life-cycle.
by Ryan N. Seekins.
S.M. in Engineering and Management
27
Bragg, Graeme McLachlan. "Standards-based Internet of Things sub-GHz environmental sensor networks." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/415864/.
Full textAbstract:
In recent years there has been shift in the use of wireless sensor networks from standalone systems that use bespoke methods of communication and data transfer to systems that use Internet standards and can interact more directly with the Internet. This has allowed wireless sensor networks to become a key enabler of the Internet of Things; however, the same is not true for environmental sensor networks as the focus of most existing research into Internet of Things wireless sensor networks has been on 2.4 GHz designs for indoor, urban and agricultural applications. In these applications, power, Internet connectivity and physical access are less of a challenge when compared to a typical environmental sensor network. Environmental sensor networks are used for monitoring natural processes and are generally deployed in harsh, remote environments where these factors are more of a concern. Sub-GHz radios are commonly used for communication due to their increased range and desirable propagation characteristics. Unlike wireless sensor networks, environmental sensor networks have been slow to adopt Internet standards and have continued to rely on bespoke methods of communication and data transfer, keeping their usability low. This has impeded the adoption of environmental sensor networks for earth sciences research. This thesis investigates whether the Internet standards that have helped to make wireless sensor network an important part of the Internet of Things can be applied to sub-GHz environmental sensor networks. It is demonstrated that 6LoWPAN can successfully be used with an 868 MHz network in a series of real-world deployments in the Highlands of Scotland that collected usable earth science data and facilitated research in other fields. Additionally, the suitability of these standards for real-world networks is assessed in terms of energy, throughput and latency performance and compared to a theoretical 2.4 GHz network. An publicly available open source Contiki radio driver for the CC1120 was developed as part of this work. Additionally, timing parameters for using ContikiMAC with 868 MHz radios were determines and shared with researchers at other institutions, facilitating further research into sub-GHz IoT ESNs by other researchers.
28
Ramezani, Parisa. "Extending Wireless Powered Communication Networks for Future Internet of Things." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/16850.
Full textAbstract:
Energy limitation has always been a major concern for long-term operation of wireless networks. With today's exponential growth of wireless technologies and the rapid movement towards the so-called Internet of Things (IoT), the need for a reliable energy supply is more tangible than ever. Recently, energy harvesting has gained considerable attention in research communities as a sustainable solution for prolonging the lifetime of wireless networks. Beside conventional energy harvesting sources such as solar, wind, vibration, etc. harvesting energy from radio frequency (RF) signals has drawn significant research interest in recent years as a promising way to overcome the energy bottleneck. Lately, the integration of RF energy transfer with wireless communication networks has led to the emergence of an interesting research area, namely, wireless powered communication network (WPCN), where network users are powered by a hybrid access point (HAP) which transfers wireless energy to the users in addition to serving the functionalities of a conventional access point. The primary aim of this thesis is to extend the baseline model of WPCN to a dual-hop WPCN (DH-WPCN) in which a number of energy-limited relays are in charge of assisting the information exchange between energy-stable users and the HAP. Unlike most of the existing research in this area which has merely focused on designing methods and protocols for uplink communication, we study both uplink and downlink information transmission in the DH-WPCN. We investigate sum-throughput maximization problems in both directions and propose algorithms for optimizing the values of the related parameters. We also tackle the doubly near-far problem which occurs due to unequal distance of the relays from the HAP by proposing a fairness enhancement algorithm which guarantees throughput fairness among all users.
29
Galanis, Ioannis. "RESOURCE MANAGEMENT IN EDGE COMPUTING FOR INTERNET OF THINGS APPLICATIONS." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1871.
Full textAbstract:
The Internet of Things (IoT) computing paradigm has connected smart objects “things” and has brought new services at the proximity of the user. Edge Computing, a natural evolution of the traditional IoT, has been proposed to deal with the ever-increasing (i) number of IoT devices and (ii) the amount of data traffic that is produced by the IoT endpoints. EC promises to significantly reduce the unwanted latency that is imposed by the multi-hop communication delays and suggests that instead of uploading all the data to the remote cloud for further processing, it is beneficial to perform computation at the “edge” of the network, close to where the data is produced. However, bringing computation at the edge level has created numerous challenges as edge devices struggle to keep up with the growing application requirements (e.g. Neural Networks, or video-based analytics). In this thesis, we adopt the EC paradigm and we aim at addressing the open challenges. Our goal is to bridge the performance gap that is caused by the increased requirements of the IoT applications with respect to the IoT platform capabilities and provide latency- and energy-efficient computation at the edge level. Our first step is to study the performance of IoT applications that are based on Deep Neural Networks (DNNs). The exploding need to deploy DNN-based applications on resource-constrained edge devices has created several challenges, mainly due to the complex nature of DNNs. DNNs are becoming deeper and wider in order to fulfill users expectations for high accuracy, while they also become power hungry. For instance, executing a DNN on an edge device can drain the battery within minutes. Our solution to make DNNs more energy and inference friendly is to propose hardware-aware method that re-designs a given DNN architecture. Instead of proxy metrics, we measure the DNN performance on real edge devices and we capture their energy and inference time. Our method manages to find alternative DNN architectures that consume up to 78.82% less energy and are up to35.71% faster than the reference networks. In order to achieve end-to-end optimal performance, we also need to manage theedge device resources that will execute a DNN-based application. Due to their unique characteristics, we distinguish the edge devices into two categories: (i) a neuromorphic platform that is designed to execute Spiking Neural Networks (SNNs), and (ii) a general-purpose edge device that is suitable to host a DNN. For the first category, we train a traditional DNN and then we convert it to a spiking representation. We target the SpiNNaker neuromorphic platform and we develop a novel technique that efficiently configures the platform-dependent parameters, in order to achieve the highest possible SNN accuracy.Experimental results show that our technique is 2.5× faster than an exhaustive approach and can reach up to 0.8% higher accuracy compared to a CPU-based simulation method. Regarding the general-purpose edge devices, we show that a DNN-unaware platform can result in sub-optimal DNN performance in terms of power and inference time. Our approachconfigures the frequency of the device components (GPU, CPU, Memory) and manages to achieve average of 33.4% and up to 66.3% inference time improvements and an average of 42.8% and up to 61.5% power savings compared to the predefined configuration of an edge device. The last part of this thesis is the offloading optimization between the edge devicesand the gateway. The offloaded tasks create contention effects on gateway, which can lead to application slowdown. Our proposed solution configures (i) the number of application stages that are executed on each edge device, and (ii) the achieved utility in terms of Quality of Service (QoS) on each edge device. Our technique manages to (i) maximize theoverall QoS, and (ii) simultaneously satisfy network constraints (bandwidth) and user expectations (execution time). In case of multi-gateway deployments, we tackled the problem of unequal workload distribution. In particular, we propose a workload-aware management scheme that performs intra- and inter-gateway optimizations. The intra-gateway mechanism provides a balanced execution environment for the applications, and it achieves up to 95% performance deviation improvement, compared to un-optimized systems. The presented inter-gateway method manages to balance the workload among multiple gateways and is able to achieve a global performance threshold.
30
Yelasani, kailash kumar yadav. "ECONOMIZED SENSOR DATA PROCESSING WITH VEHICLE PLATOONING." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/theses/2305.
Full textAbstract:
We present platooning as a special case of crowd-sensing framework. After offering a policy that governs platooning, we review common scenarios and components surrounding platooning. We present a prototype that illustrates efficiency of road usage and vehicle travel time derived from platooning. We have argued that beyond the commonly reported benefits of platooning, there are substantial savings in acquisition and processing of sensory data sharing the road. Our results show that data transmission can be reduced to low of 3% compared to normal data transmission using a platoon formation with sensor sharing.
31
Lee, Gilsoo. "Online Optimization for Edge Computing under Uncertainty in Wireless Networks." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/97909.
Full textAbstract:
Edge computing is an emerging technology that can overcome the limitations of centralized cloud computing by enabling distributed, low-latency computation at a network edge. Particularly, in edge computing, some of the cloud's functionalities such as storage, processing, and computing are migrated to end-user devices called edge nodes so as to reduce the round-trip delay needed to reach the cloud data center. Despite the major benefits and practical applications of using edge computing, one must address many technical challenges that include edge network formation, computational task allocation, and radio resource allocation, while considering the uncertainties innate in edge nodes, such as incomplete future information on their wireless channel gains and computing capabilities. The goal of this dissertation is to develop foundational science for the deployment, performance analysis, and low-complexity optimization of edge computing under the aforementioned uncertainties. First, the problems of edge network formation and task distribution are jointly investigated while considering a hybrid edge-cloud architecture under uncertainty on the arrivals of computing tasks. In particular, a novel online framework is proposed to form an edge network, distribute the computational tasks, and update a target competitive ratio defined as the ratio between the latency achieved by the proposed online algorithm and the optimal latency. The results show that the proposed framework achieves the target competitive ratio that is affected by the wireless data rate and computing speeds of edge nodes. Next, a new notion of ephemeral edge computing is proposed in which edge computing must occur under a stringent requirement on the total computing time period available for the computing process. To maximize the number of computed tasks in ephemeral edge networks under the uncertainty on future task arrivals, a novel online framework is proposed to enable a source edge node to offload computing tasks from sensors and allocate them to neighboring edge nodes for distributed task computing, within the limited total time period. Then, edge computing is applied for mobile blockchain and online caching systems, respectively. First, a mobile blockchain framework is designed to use edge devices as mobile miners, and the performance is analyzed in terms of the probability of forking event and energy consumption. Second, an online computational caching framework is designed to minimize the edge network latency. The proposed caching framework enables each edge node to store intermediate computation results (IRs) from previous computations and download IRs from neighboring nodes under uncertainty on future computation. Subsequently, online optimization is extended to investigate other edge networking applications. In particular, the problem of online ON/OFF scheduling of self-powered small cell base stations is studied, in the presence of energy harvesting uncertainty with the goal of minimizing the operational costs that consist of energy consumption and transmission delay of a network. Such a framework can enable the self-powered base stations to be functioned as energy-efficient edge nodes. Also, the problem of radio resource allocation is studied when a base station is assisted by self-powered reconfigurable intelligent surfaces (RIS). To this end, a deep reinforcement learning approach is proposed to jointly optimize the transmit power, phase shifting, and RIS reflector's ON/OFF states under the uncertainties on the downlink wireless channel information and the harvested energy at the RIS. Finally, the online problem of dynamic channel allocation is studied for full-duplex device-to-device (D2D) networks so that D2D users can share their data with a low communication latency when users dynamically arrive on the network. In conclusion, the analytical foundations and frameworks presented in this dissertation will provide key guidelines for effective design of edge computing in wireless networks.Doctor of Philosophy
Smart cities will rely on an Internet of Things (IoT) system that interconnects cars, drones, sensors, home appliances, and other digital devices. Modern IoT systems are inherently designed to process real-time information such as temperature, humidity, or even car navigational data, at any time and location. A unique challenge in the design of such an IoT is the need to process large volumes of data over a wireless network that consists of heterogeneous IoT devices such as smartphones, vehicles, home access points, robots, and drones. These devices must perform local (on-device or so-called edge) processing of their data without relying on a remote cloud. This vision of a smart city seen as a mobile computing platform gives rise to the emerging concept of edge computing using which smartphones, sensors, vehicles, and drones can exchange and process data locally on their own devices. Edge computing allows overcoming the limitations of centralized cloud computation by enabling distributed, low-latency computation at the network edge. Despite the promising opportunities of edge computing as an enabler for smart city services such as autonomous vehicles, drones, or smart homes, one must address many challenges related to managing time-varying resources such as energy and storage, in a dynamic way. For instance, managing communication, energy, and computing resources in an IoT requires handling many uncertain factors such as the intermittent availability of wireless connectivity and the fact that the devices do not know a priori what type of tasks they need to process. The goal of this dissertation is to address the fundamental challenges in edge computing under uncertainty in an IoT. In particular, this dissertation introduces novel mathematical algorithms and frameworks that exploit ideas from the fields of online optimization, machine learning, and wireless communication to enable future IoT services such as smart factories, virtual reality, and autonomous systems. In this dissertation, holistic frameworks are developed by designing, analyzing, and optimizing wireless communications systems with an emphasize on emerging IoT applications. To this end, various mathematical frameworks and efficient algorithms are proposed by drawing on tools from wireless communications, online optimization, and machine learning to yield key innovations. The results show that the developed solutions can enable an IoT to operate efficiently in presence of uncertainty stemming from time-varying dynamics such as mobility of vehicles or changes in the wireless networking environment. As such, the outcomes of this research can be used as a building block for the large deployment of smart city technologies that heavily rely on the IoT.
32
Alm, Anton. "Internet of Things mesh network : Using the Thread networking protocol." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-70809.
Full textAbstract:
This thesis summarizes my project in setting up a Thread network. The idea of this project was presented by the company ÅF in Karlstad, Sweden. ÅF wishes to upgrade their current demonstrator for IoT. The current demonstrator includes Azure Cloud component, Raspberry Pi, Bluetooth and Arduino components. The upgrade includes implementing Thread technology together with Thread verified hardware from Nordic semiconductor and the Raspberry Pi Foundation. Thread is an IoT mesh networking protocol that was released year 2014. Compared to Bluetooth it offers IP communication (including IPv6) combined with higher reliability, performance and security. The process of installing, compiling and configuring the Thread network is explained. The result is an operational thread network that has sensor devices sending data to an HTTP web server, where the data is stored and monitored. Though, there are many improvements and functions that can be implemented to make this demonstrator more appealing.
33
Koutsoumpakis, Iakovos. "An Internet of Things network for proximity based distributed processing." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-267865.
Full textAbstract:
The Internet of Things, the interconnection of all computing devices, is a concept that has become very popular nowadays and many companies try to achieve a leading role in shaping its future. Billions of devices are already connected to IoT cloud networks and this number is expected to rapidly increase in the near future. Devices in an IoT cloud network can be producers or consumers of data, while some can be processors. As data often needs processing in order to be transformed from lower to higher conceptual value, before being delivered to the consumers, this processing has to be done in an efficient manner. Ideally processing should take place in the proximity of data producers as opposed to having to transfer large volumes of data over the network in order to reach the processor. For this problem to be solved, scheduling algorithms require additional information that quantifies the "distance" between the different nodes in an IoT cloud network. Consequently, the main focus of this work is the development and the evaluation of an efficient mechanism that uses a heuristic technique to estimate this information, the latency between nodes, greatly reducing to linear the running time complexity that, if every device had to contact every other to calculate it, would be O(n^2).
34
Ngqakaza, Lutando. "Multi-Layered Security in the Internet of the Things." Thesis, University of Cape Town, 2014. http://pubs.cs.uct.ac.za/archive/00000998/.
Full textAbstract:
It is well discussed and understood that there is still a need for suitable security for the Internet of Things. It is however still not clear how existing or emerging security paradigms can be effectively applied to a network of constrained nodes in a lossy communications environment. This thesis provides a survey into what routing protocols can be used with network security in mind. What will also be discussed, is an implementation, that in conjunction which a robust routing protocol, can provide security for a network of constrained devices with a certain level of confidence. The implementation and design involves including communications encryption and centralized non-cryptographic methods for securing the network. This thesis basically explores the use of multiple security mechanisms in an Internet of Things environment by using Contiki OS as the platform of choice for simulations and testing.
35
Arbiza, Lucas Mendes Ribeiro. "SDN no contexto de IoT : refatoração de middleware para monitoramento de pacientes crônicos baseada em software-defined networking." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/134368.
Full textAbstract:
Algumas palavras e definições comumente utilizadas quando se está falando de Software-Defined Networking, como programabilidade, flexibilidade, ou gerenciamento centralizado, parecem muito apropriadas ao contexto de um outro paradigma de rede: Internet of Things. Em redes domésticas já não é incomum a existência de dispositivos projetados para segurança, climatização, iluminação, monitoramento de saúde e algumas formas de automação que diferem entre si em diversos aspectos, como no modo de operar e de se comunicar. Lidar com este tipo de cenário, que pode diferir bastante daquilo que estamos acostumados na gerência de redes e serviços, fazendo uso dos recursos tradicionais como ferramentas e protocolos bem estabelecidos, pode ser difícil e, em alguns casos, inviável. Com o objetivo de possibilitar o monitoramento remoto de pacientes com doenças crônicas através de dispositivos de healthcare disponíveis no mercado, uma proposta de middleware foi desenvolvida em um projeto de pesquisa para contornar as limitações relacionadas à interoperabilidade, coleta de dados, gerência, segurança e privacidade encontradas nos dispositivos utilizados. O middleware foi projetado com o intuito de executar em access points instalados na casa dos pacientes. Contudo, as limitações de hardware e software do access point utilizado refletem no desenvolvimento, pois restringem o uso de linguagens de programação e recursos que poderiam agilizar e facilitar a implementação dos módulos e dos mecanismos necessários. Os contratempos encontrados no desenvolvimento motivaram a busca por alternativas, o que resultou na refatoração do middleware através de Software-Defined Networking, baseando-se em trabalhos que exploram o uso desse paradigma em redes domésticas. O objetivo deste trabalho é verificar a viabilidade da utilização de Software-Defined Networking no contexto de Internet of Things, mais especificamente, aplicado ao serviço de monitoramento de pacientes da proposta anterior e explorar os possíveis benefícios resultantes. Com a refatoração, a maior parte da carga de serviços da rede e do monitoramento foi distribuída entre servidores remotos dedicados, com isso os desenvolvedores podem ir além das restrições do access point e fazer uso de recursos antes não disponíveis, o que potencializa um processo de desenvolvimento mais ágil e com funcionalidades mais complexas, ampliando as possibilidades do serviço. Adicionalmente, a utilização de Software-Defined Networking proporcionou a entrega de mais de um serviço através de um único access point, escalabilidade e autonomia no gerenciamento das redes e dos dispositivos e na implantação de serviços, fazendo uso de recursos do protocolo OpenFlow, e a cooperação entre dispositivos e serviços a fim de se criar uma representação digital mais ampla do ambiente monitorado.Some words and definitions usually employed when talking about Software-Defined Networking such as programmability, frexibility, or centralized management sound very appropriate to the context of another network paradigm: Internet of Things. The presence of devices designed for security, air conditioning, lighting, health monitoring and some other automation resources have become common in home networks; those devices may be different in many ways, such as the way they operate and communicate, between others. Dealing with this kind of scenario may differ in many ways from what we are familiar regarding networking and services management; the use of traditional management tools and protocols may be hard or even unfeasible. Aiming to enable the health monitoring of patients with chronical illnesses through using off-the-shelf healthcare devices a middleware proposal was developed in a research project to circumvent interoperability, data collecting, management, security and privacy issues found in employed devices. The middleware was designed to run on access points in the homes of the patients. Although hardware and software limitations of the used access points reflect on the development process, because they restrict the use of programming languages and resources that could be employed to expedite the implementation of necessary modules and features. Development related mishaps have motivated the search for alternatives resulting in the middleware refactoring through Software-Defined Networking, based on previous works where that paradigm is used in home networks. This work aims to verify the feasability of the employment of Software- Defined Networking in the Internet of Things context, and its resulting benefits; specifically in the health monitoring of chronic patients service from the previous proposal. After refactoring most of the network and services load was distributed among remote dedicated servers allowing developers to go beyond the limitations imposed by access points constraints, and to make use of resources not available before enabling agility to the development process; it also enables the development of more complex features expanding services possibilities. Additionally Software-Defined Networking employment provides benefits such as the delivering of more than only one service through the same access point; scalability and autonomy to the network and devices monitoring, as to the service deployment through the use of OpenFlow resources; and devices and services cooperation enabling the built of a wider digital representation of the monitored environment.
36
Ljungblad, Robert. "Blockchain in an Internet-of-Things Network Based on User Participation." Thesis, Luleå tekniska universitet, Datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-75041.
Full textAbstract:
The internet-of-things is the relatively new and rapidly growing concept of connecting everyday devices to the internet. Every day more and more devices are added to the internet-of-things and it is not showing any signs of slowing down. In addition, advancements in new technologies such as blockchains, artificial intelligence, virtual reality and machine learning are made practically every day. However, there are still much to learn about these technologies. This thesis explores the possibilities of blockchain technology by applying it to an internet-of-things network based on user participation. More specifically, it is applied to a use case derived from Luleå Kommun’s wishes to easier keep track of how full the city’s trash cans are. The goal of the thesis is to learn more about how blockchains can help an internet-of-things network as well as what issues can arise. The method takes an exploratory approach to the problem by partaking in a workshop with Luleå Kommun and by performing a literature study. It also takes a qualitative approach by creating a proof-of-concept solution to experience the technology firsthand. The final proof-of-concept as well as issues that arose during the project are analysed with the help of information gathered and experience gained throughout the project. It is concluded that blockchain technology can help communication in an internet-of-things network based on user participation. However, there is still a lot more to learn and uncover in future research.Internet-of-things är ett relativt nytt men snabbt växande koncept som handlar om att koppla upp vardagliga saker till internet. Varje dag kopplas mer och mer enheter upp och det visar inga tecken på att sakta ner. Det görs även framsteg inom andra nya teknologier som blockkedjor, artificiell intelligens, virtuell verklighet och maskininlärning i stort sett varje dag. Dock finns det fortfarande mycket att lära sig om dessa teknologier. Denna rapport utforskar blockkedjeteknologins möjligheter genom att applicera det på ett internet-of-things-nätverk baserat på användarmedverkan. Mer specifikt, det är applicerat på ett användningsfall grundat i Luleå Kommuns önskan att lättare hålla koll på hur fulla deras soptunnor i och runtom staden är. Målet med denna rapport är att lära sig mer om hur blockkedjor kan stödja ett internet-of-things-nätverk och utforska vilka problem som kan uppstå. Metoden tar en explorativ ansats till problemet genom att delta i en workshop tillsammans med Luleå Kommun och genomföra en litteraturstudie. Dessutom tas en kvalitativ ansats genom att skapa en prototyplösning för att få förstahandserfarenhet av teknologin. Den slutliga prototypen och problemen som uppstod under projektets gång är analyserade med hjälp av information och erfarenhet som samlats genom hela projektet. Sammanfattningsvis kan blockkedjeteknologi hjälpa till kommunikationen i ett internet-of-things-nätverk baserat på användarmedverkan. Dock finns det fortfarande mycket att lära sig om denna teknologi i framtida forskning.
37
Sharma, Aakanksha. "Machine learning-based optimal load balancing in software-defined networks." Thesis, Federation University Australia, 2022. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/188228.
Full textAbstract:
The global advancement of the Internet of Things (IoT) has poised the existing network traffic for explosive growth. The prediction in the literature shows that in the future, trillions of smart devices will connect to transfer useful information. Accommodating such proliferation of devices in the existing network infrastructure, referred to as the traditional network, is a significant challenge due to the absence of centralized control, making it tedious to implement the device management and network protocol updates. In addition, due to their inherently distributed features, applying machine learning mechanisms in traditional networks is demanding. Consequently, it leads to an imbalanced load in the network that affects the overall network Quality of Service (QoS). Expanding the existing infrastructure and manual traffic control methods are inadequate to cope with the exponential growth of IoT devices. Therefore, an intelligent system is necessary for future networks that can efficiently organize, manage, maintain, and optimize the growing networks. Software-defined network (SDN) has a holistic view of the network and is highly suitable for handling dynamic loads in the traditional network with a minimal update in the network infrastructure. However, the standard SDN architecture control plane has been designed for a single controller or multiple distributed controllers that faces severe bottleneck issues. Our initial research created a reference model for the traditional network, using the standard SDN (SDN) in a network simulator called NetSim. Based on the network traffic, the reference models consisted of light, modest and heavy networks depending on the number of connected IoT devices. Furthermore, the research was enhanced with a priority scheduling and congestion control algorithm in the standard SDN, named extended SDN (eSDN), which minimized the network congestion and performed better than the existing SDN. However, enhancement was suitable only for the small-scale network because, in a large-scale network, the eSDN does not support dynamic controller mapping in the network. Often, the same controller gets overloaded, leading to a single point of failure. Our exhaustive literature review shows that the majority of proposed solutions are based on static controller deployment without considering flow fluctuations and traffic bursts that lead to a lack of load balancing among controllers in real-time, eventually increasing the network latency. Often, the switch experiences a traffic burst, and consequently, the corresponding controller might overload. Therefore, to maintain the Quality of Service (QoS) in the network, it becomes imperative for the static controller to neutralize the on-the-fly traffic burst. Addressing the above-mentioned issues demands research critical to improving the QoS in load balancing, latency minimisation, and network reliability for next- generation networks. Our novel dynamic controller mapping algorithm with multiple- controller placement in the SDN is critical in solving the identified issues. In the dynamic controller approach (dSDN), the controllers are mapped dynamically as the load fluctuates. If any controller reaches its maximum threshold, the rest of the traffic will be diverted to another controller, significantly reducing delay and enhancing the overall performance. Our technique considers the latency and load fluctuation in the network and manages the situations where static mapping is ineffective in dealing with the dynamic flow variation. In addition, our novel approach adds more intelligence to the network with a Temporal Deep Q Learning (tDQN) approach for dynamic controller mapping when the flow fluctuates. In this technique, a multi-objective optimization problem for flow fluctuation is formulated to dynamically divert the traffic to the best-suited controller. The formulated technique is placed as an agent in the network controller to take care of all the routing decisions, which can solve the dynamic flow mapping and latency optimization without increasing the number of optimally placed controllers. Extensive simulation results show that the novel approach proposed in this thesis solves dynamic flow mapping by maintaining a balanced load among controllers and outperforms the existing traditional networks and SDN with priority scheduling and congestion control. Compared to traditional networks, tDQN provides a 47.48% increase in throughput, a 99.10% reduction in delay and a 97.98% reduction in jitter for heavy network traffic. The thesis also presents a few future research directions as possible extensions of the current work for further enhancement.Doctor of Philosophy
38
Ainchwar, Arpit. "Determination of Cycle Time Constraints in Case of Link Failure in Closed Loop Control in Internet of Things." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/36906.
Full textAbstract:
In today’s era of the Internet of Things, it is crucial to study the real-time dependencies of the web, its failures and time delays. Today, smart grids, sensible homes, wise water networks, intelligent transportation, infrastructure systems that connect our world over are developing fast. The shared vision of such systems is typically associated with one single conception Internet of Things (IoT), where through the deployment of sensors, the entire physical infrastructure is firmly fastened with information and communication technologies; where intelligent observation and management is achieved via the usage of networked embedded devices.
The performance of a real-time control depends not only on the reliability of the hardware and software used but also on the time delay in estimating the output, because of the effects of computing time delay on the control system performance. For a given fixed sampling interval, the delay and loss issues are the consequences of computing time delay. The delay problem occurs when the computing time delay is non-zero but smaller than the sampling interval, while the loss problem occurs when the computing time delay is greater than, or equal to, the sampling interval, i.e., loss of the control output. These two queries are analyzed as a means of evaluating real-time control systems. First, a general analysis of the effects of computing time delay is presented along with necessary conditions for system stability. In this thesis, we will focus on the experimental study of the closed loop control system in the internet of things to determine the cycle time constraints in case of link failure.
39
Jedda, Ahmed. "Distributed Algorithms for Networks Formation in a Scalable Internet of Things." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30979.
Full textAbstract:
The Internet of Things (IoT) is a vision that aims at inter-connecting every physical identifiable object (or, a thing) via a global networking infrastructure (e.g., the legacy Internet). Several architectures are proposed to realize this vision; many of which agree that the IoT shall be considered as a global network of networks. These networks are used to manage wireless sensors, Radio Frequency IDentification (RFID) tags, RFID readers and other types of electronic devices and integrate them into the IoT. A major requirement of the IoT architectures is scalability, which is the capability of delivering high performance even if the input size (e.g., number of the IoT objects) is large. This thesis studies and proposes solutions to meet this requirement, and specifically focuses on the scalability issues found in the networks of the IoT. The thesis proposes several network formation algorithms to achieve these objectives, where a network formation algorithm is an algorithm that, if applied to a certain network, optimizes it to perform its tasks in a more efficient manner by virtually deleting some of its nodes and/or edges.
The thesis focuses on three types of networks found in the IoT: 1) RFID readers coverage networks; whose main task is to cover (i.e., identify, monitor, track, sense) IoT objects located in a given area, 2) readers inter-communications networks; whose main task is to guarantee that their nodes are able to inter-communicate with each other and hence use their resources more efficiently (the thesis specifically considers inter-communication networks of readers using Bluetooth for communications), and 3) Object Name Systems (ONS) which are networks of several inter-connected database servers (i.e., distributed database) whose main task is to resolve an object identifier into an Internet address to enable inter-communication via the Internet. These networks are chosen for several reasons. For example, the technologies and concepts found in these networks are among the major enablers of the IoT. Furthermore, these networks solve tasks that are central to any IoT architecture. Particularly, the thesis a) studies the data and readers redundancy problem found in RFID readers coverage networks and introduces decentralized RFID coverage and readers collisions avoidance algorithms to solve it, b) contributes to the problem of forming multihop inter-communications networks of Bluetooth-equipped readers by proposing decentralized time-efficient Bluetooth Scatternet Formation algorithms, and c) introduces a geographic-aware ONS architecture based on Peer-To-Peer (P2P) computing to overcome weaknesses found in existing ONS architectures.
40
VACCARI, IVAN. "Security aspects about Internet of Things networks, devices and communication protocols." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1047169.
Full textAbstract:
Nowadays, the Internet of Things (IoT) is a consolidated paradigm increasingly present in our lives, from simple devices to more complex systems, such as health sensor or vehicular networks. Today, there are 20 billions on IoT devices connected in the world and the number will exponentially increase in the next years cite{hung2017leading}. From a practical point of view, the Internet of Things incorporates processing skills (also called "intelligence") and connection in the most varied devices. This involves the possibility of collecting data through these objects and analyzing them, greater automation and remote control, an analysis on how to improve the use and prevent malfunctions of the objects themselves, thus increasing the quality of their use over time. Among the many definitions on IoT, ENISA cite{enisa2017baseline} considers the IoT a "cyber-physical ecosystem of interconnected sensors and actuators, which allow intelligent decision-making".
In summary, we could say, to extrapolate the concept, that we are dealing with objects (things) connected through a planetary communication network (Internet), capable of detecting, processing and transmitting information. In practice, the "thing" is in fact a computer, more or less powerful in relation to the functions for which it was designed: to detect the consumption of electricity, to allow the increasingly pushed automation governed by the control units of our cars, to automate our homes with home automation solutions, to digitize industrial plants or medical systems, to name just a few classes of IoT systems.
The spread of the IoT and the birth of new application areas will draw significant advantages from the developments expected in the coming years on some enabling technologies, including the implementation of 5G/6G networks, which will lead to a significant increase in transmission speed and a contextual reduction of latency times in the use of devices, and the application of Artificial Intelligence (AI) and Machine Learning (ML) technologies, to exploit the amount of data generated by IoT devices for decision-making purposes, increasing the level of "intelligence” in the services enabled by the IoT devices themselves, benefiting in particular the applications in real time.
The IoT can also consist of solutions identified as "embedded systems" in which sensors and actuators are incorporated into a single system that integrates network functions with the ability to collect and process information, which can operate standalone or interconnected with computers which act as information gathering centers: in this sense, IoT devices can be used by end users (consumers) and businesses (IoT devices can also be used in industrial plants, to create the so-called industry 4.0), with all the advantages that automation allows, but also with significant potential security and compliance problems. Just think of the need to ensure the operational continuity of medical devices and critical industrial plants and the privacy implications for devices that process personal health data or that collect information designed to profile the purchase of goods and services. Data and information are at the heart of the IoT, feeding a continuous cycle of detection (environmental data and device status), a decision-making process and the resulting actions. Moreover, communications security is a critical and important aspect, since the processed data/information are considered sensitive due to the possible application of IoT (e.g. medical, critical infrastructures, etc.).
Security and the evolution of ICT technologies take on a decisive importance in the IoT world. The IoT device must ensure compliance with the basic CIA principles of security (confidentiality, availability and integrity). Vulnerabilities of an IoT system emerge from its components, including but not limited to sensor networks, wireless networks and the Internet. These vulnerabilities can result in a variety of cyber-security threats, from attacks on a physical device to communication protocols and services that access IoT device data. Since IoT devices are the basic building block of an IoT system, along with various device-level vulnerabilities, they have made such devices and protocols an attractive target for adversaries.
With regard to security, it is important to emphasize that one of the so-called "deadly sins of the IoT" is to use the corporate network to collect information generated by unsafe IoT devices: malicious people are always around and can exploit IoT vulnerabilities to bring attacks on computer systems and networks. Based on these considerations, cyber-security aspects about IoT networks, devices and communication protocols are an interesting research topic to investigate to ensure security about this technology.
In order to improve security about Internet of Things networks, devices and communication protocols, I decided to investigate these cyber-security aspects during my Ph.D. research activities. The main goals of this work is to identify possible vulnerabilities on IoT devices and networks, to develop innovative cyber-threats to able to exploit these vulnerabilities or by using IoT devices as attack vector and, finally, to implement innovative protection and mitigation systems from the innovative cyber-threats. I applied this approach to three communication protocols: ZigBee, Wi-Fi (in particular to a commercial constrain module called ESP8266) and Message Queue Telemetry Transport(MQTT). Regarding the ZigBee communication protocol, I performed security tests against well-known cyber-attacks (such as jamming, brute force, sniffing, flooding denial of service and replay attack) where the results obtained show how vulnerable the protocol is to these attacks. By focusing on Wi-Fi and on the ESP8266 module, I identified a vulnerability against replay attacks where I proposed a protection schema based on a shared key mechanism. Moreover, I adopted the ESP8266 module to perform two cyber-attacks: a slow denial of service attack against an Apache2 server and a captive portal attack used to steal sensitive information. Both the attacks are success. Finally. I studied the MQTT protocol where I identified a vulnerability on the KeepAlive parameter inside the protocol. By exploiting this vulnerability, I implemented two innovative slow denial of service attack able to saturate the connections available on the central node (called broker) to avoid legitimate connections. On this topic, I also developed an innovative dataset based on MQTT communication that simulates smart-space indoor environment. With the dataset, I implemented a machine learning detection system in order to identify possible cyber-attacks against an MQTT network. Finally on MQTT, I exploited the communication protocol to implement a tunneling system to steal sensitive information in a private network with a related machine learning detection system performed with hyperparameters optimization to improve accuracy and statistics metrics.
41
Park, Taehyeun. "Distributed Wireless Resource Management in the Internet of Things." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99055.
Full textAbstract:
The Internet of Things (IoT) is a promising networking technology that will interconnect a plethora of heterogeneous wireless devices. To support the connectivity across a massive-scale IoT, the scarce wireless communication resources must be appropriately allocated among the IoT devices, while considering the technical challenges that arise from the unique properties of the IoT, such as device heterogeneity, strict communication requirements, and limited device capabilities in terms of computation and memory. The primary goal of this dissertation is to develop novel resource management frameworks using which resource-constrained IoT devices can operate autonomously in a dynamic environment. First, a comprehensive overview on the use of various learning techniques for wireless resource management in an IoT is provided, and potential applications for each learning framework are proposed. Moreover, to capture the heterogeneity among IoT devices, a framework based on cognitive hierarchy theory is discussed, and its implementation with learning techniques of different complexities for IoT devices with varying capabilities is analyzed. Next, the problem of dynamic, distributed resource allocation in an IoT is studied when there are heterogeneous messages. Particularly, a novel finite memory multi-state sequential learning is proposed to enable diverse IoT devices to reallocate the limited communication resources in a self-organizing manner to satisfy the delay requirement of critical messages, while minimally affecting the delay-tolerant messages. The proposed learning framework is shown to be effective for the IoT devices with limited memory and observation capabilities to learn the number of critical messages. The results show that the performance of learning framework depends on memory size and observation capability of IoT devices and that the learning framework can realize low delay transmission in a massive IoT. Subsequently, the problem of one-to-one association between resource blocks and IoT devices is studied, when the IoT devices have partial information. The one-to-one association is formulated as Kolkata Paise Restaurant (KPR) game in which an IoT device tries to choose a resource block with highest gain, while avoiding duplicate selection. Moreover, a Nash equilibrium (NE) of IoT KPR game is shown to coincide with socially optimal solution. A proposed learning framework for IoT KPR game is shown to significantly increase the number of resource blocks used to successful transmit compared to a baseline. The KPR game is then extended to consider age of information (AoI), which is a metric to quantify the freshness of information in the perspective of destination. Moreover, to capture heterogeneity in an IoT, non-linear AoI is introduced. To minimize AoI, centralized and distributed approaches for the resource allocation are proposed to enable the sharing of limited communication resources, while delivering messages to the destination in a timely manner. Moreover, the proposed distributed resource allocation scheme is shown to converge to an NE and to significantly lower the average AoI compared to a baseline. Finally, the problem of dynamically partitioning the transmit power levels in non-orthogonal multiple access is studied when there are heterogeneous messages. In particular, an optimization problem is formulated to determine the number of power levels for different message types, and an estimation framework is proposed to enable the network base station to adjust power level partitioning to satisfy the performance requirements. The proposed framework is shown to effectively increase the transmission success probability compared to a baseline. Furthermore, an optimization problem is formulated to increase sum-rate and reliability by adjusting target received powers. Under different fading channels, the optimal target received powers are analyzed, and a tradeoff between reliability and sum-rate is shown. In conclusion, the theoretical and performance analysis of the frameworks proposed in this dissertation will prove essential for implementing an appropriate distributed resource allocation mechanisms for dynamic, heterogeneous IoT environments.Doctor of Philosophy
The Internet of Things (IoT), which is a network of smart devices such as smart phones, wearable devices, smart appliances, and environment sensors, will transform many aspects of our society with numerous innovative IoT applications. Those IoT applications include interactive education, remote healthcare, smart grids, home automation, intelligent transportation, industrial monitoring, and smart agriculture. With the increasing complexity and scale of an IoT, it becomes more difficult to quickly manage the IoT devices through a cloud, and a centralized management approach may not be viable for certain IoT scenarios. Therefore, distributed solutions are needed for enabling IoT devices to fulfill their services and maintain seamless connectivity. Here, IoT device management refers to the fact that the system needs to decide which devices access the network and using which resources (e.g., frequencies). For distributed management of an IoT, the unique challenge is to allocate scarce communication resources to many IoT devices appropriately. With distributed resource management, diverse IoT devices can share the limited communication resources in a self-organizing manner. Distributed resource management overcomes the limitations of centralized resource management by satisfying strict service requirements in a massive, complex IoT. Despite the advantages and the opportunities of distributed resource management, it is necessary to address the challenges related to an IoT, such as analyzing intricate interaction of heterogeneous devices, designing viable frameworks for constrained devices, and quickly adapting to a dynamic IoT. Furthermore, distributed resource management must enable IoT devices to communicate with high reliability and low delay. In this regard, this dissertation investigates these critical IoT challenges and introduces novel distributed resource management frameworks for an IoT. In particular, the proposed frameworks are tailored to realistic IoT scenarios and consider different performance metrics. To this end, mathematical frameworks and effective algorithms are developed by significantly extending tools from wireless communication, game theory, and machine learning. The results show that the proposed distributed wireless resource management frameworks can optimize key performance metrics and meet strict communication requirements while coping with device heterogeneity, massive scale, dynamic environment, and scarce wireless resources in an IoT.
42
Крамаренко, Є. С. "Iнтелектуальна мережа Internet of Things." Master's thesis, Сумський державний університет, 2019. http://essuir.sumdu.edu.ua/handle/123456789/76473.
Full textAbstract:
Зпроектовано інтелектуальну мережу «розумного будинку» у симуляторі Cisco Packet
Tracer_7, яка базується на роботі дротової та бездротової мереж, де усі пристрої звязані зі
шлюзом. Доступ контролю та моніторингу забезпечено з планшету та смартфону через зручний
веб-інтерфейс. Для налаштування пожежної безпеки було розроблено програму для
мікроконтролера на мові JavaScript. Візуальне програмування було використано для забезпечення
системи комфорту. Розроблена схема при тестуванні показала високі результати, що говорить про
доступність та зрозумілість взаємодії із можливостями симулятора. Вона дає змогу отримати
наочне уявлення про функціонування розгалудженої системи «розумного будинку» та навчитися
формулювати правила роботи окремих елементів на базі отриманих показників датчиків і
сенсорів.
43
Xu, Ran. "Federated Sensor Network architectural design for the Internet of Things (IoT)." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/13453.
Full textAbstract:
An information technology that can combine the physical world and virtual world is desired. The Internet of Things (IoT) is a concept system that uses Radio Frequency Identification (RFID), WSN and barcode scanners to sense and to detect physical objects and events. This information is shared with people on the Internet. With the announcement of the Smarter Planet concept by IBM, the problem of how to share this data was raised. However, the original design of WSN aims to provide environment monitoring and control within a small scale local network. It cannot meet the demands of the IoT because there is a lack of multi-connection functionality with other WSNs and upper level applications. As various standards of WSNs provide information for different purposes, a hybrid system that gives a complete answer by combining all of them could be promising for future IoT applications. This thesis is on the subject of `Federated Sensor Network' design and architectural development for the Internet of Things. A Federated Sensor Network (FSN) is a system that integrates WSNs and the Internet. Currently, methods of integrating WSNs and the Internet can follow one of three main directions: a Front-End Proxy solution, a Gateway solution or a TCP/IP Overlay solution. Architectures based on the ideas from all three directions are presented in this thesis; this forms a comprehensive body of research on possible Federated Sensor Network architecture designs. In addition, a fully compatible technology for the sensor network application, namely the Sensor Model Language (SensorML), has been reviewed and embedded into our FSN systems. The IoT as a new concept is also comprehensively described and the major technical issues discussed. Finally, a case study of the IoT in logistic management for emergency response is given. Proposed FSN architectures based on the Gateway solution are demonstrated through hardware implementation and lab tests. A demonstration of the 6LoWPAN enabled federated sensor network based on the TCP/IP Overlay solution presents a good result for the iNET localization and tracking project. All the tests of the designs have verified feasibility and achieve the target of the IoT concept.
44
Hsu, Alexander Sirui. "Automatic Internet of Things Device Category Identification using Traffic Rates." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/88421.
Full textAbstract:
Due to the ever increasing supply of new Internet of Things (IoT) devices being added onto a network, it is vital secure the devices from incoming cyber threats. The manufacturing process of creating and developing a new IoT device allows many new companies to come out with their own device. These devices also increase the network risk because many IoT devices are created without proper security implementation. Utilizing traffic patterns as a method of device type detection will allow behavior identification using only Internet Protocol (IP) header information. The network traffic captured from 20 IoT devices belonging to 4 distinct types (IP camera, on/off switch, motion sensor, and temperature sensor) are generalized and used to identify new devices previously unseen on the network. Our results indicate some categories have patterns that are easier to generalize, while other categories are harder but we are still able recognize some unique characteristics. We also are able to deploy this in a test production network and adapted previous methods to handle streaming traffic and an additional noise categorization capable of identify non-IoT devices. The performance of our model is varied between classes, signifying that much future work has to be done to increase the classification score and overall usefulness.Master of Science
IoT (Internet of Things) devices are an exploding field, with many devices being created, manufactured, and utilized per year. With the rise of so many internet capable devices, there is a risk that the devices may have vulnerabilities and exploits able to allow unauthorized users to access. While a problem for a consumer network, this is an increased problem in an enterprise network, since much of the information on the network is sensitive and should be kept confidential and private. While a ban of IoT devices on a network is able to solve this problem, with the rise of machine learning able to characterize and recognize patterns, a smarter approach can be created to distinguish when and which types of IoT devices enter the network. Previous attempts to identify IoT devices used signature schemes specific to a single device, but this paper aims to generalize traffic behaviors and identifying a device category rather than a specific IoT device to ensure future new devices can also be recognized. With device category identification in place on an internet network, smarter approaches can be implemented to ensure the devices remain secure while still able to be used.
45
Krishna, Ashwin. "Composing and connecting devices in animal telemetry network." Kansas State University, 2016. http://hdl.handle.net/2097/32882.
Full textAbstract:
Master of ScienceDepartment of Computing and Information Sciences
Venkatesh P. Ranganath
As the Internet of Things (IoT) continues to grow, the need for services that span multiple application domains will continue to increase to realise the numerous possibilities enabled by IoT. Today, however, heterogeneity among devices leads to interoperability issues while building a system of systems and often give rise to closed ecosystems. The issues with interoperability are driven by the inability of devices and apps from different vendors to communicate with each other. The interoperability problem forces the users to stick to one particular vendor, leading to vendor lock-in. To achieve interoperability, the users have to do the heavy lifting (at times impossible) of connecting heterogeneous devices. As we slowly move towards system-of-systems and IoT, there is a real need to support heterogeneity and interoperability. A recent effort in Santos Lab developed Medical Device Coordination Framework (MDCF), which was a step to address these issues in the space of human medical systems. Subsequently, we have been wondering if a similar solution can be employed in the area of animal science. In this effort, by borrowing observations from MDCF and knowledge from on-field experience, we have created a demonstration showcasing how a combination of precise component descriptions (via DSL) and communication patterns can be used in software development and deployment to overcome barriers due to heterogeneity, interoperability and to enable an open ecosystem of apps and devices in the space of animal telemetry.
46
Al-Kashoash, Hayder Ahmed Abdulmohsin. "Congestion control for 6LoWPAN wireless sensor networks : toward the Internet of Things." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/18210/.
Full textAbstract:
The Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. Due to power, bandwidth, memory and processing resources limitation, heavy network traffic in 6LoWPAN networks causes congestion which significantly degrades network performance and impacts on the quality of service (QoS) aspects. This thesis addresses the congestion control issue in 6LoWPAN networks. In addition, the related literature is examined to define the set of current issues and to define the set of objectives based upon this. An analytical model of congestion for 6LoWPAN networks is proposed using Markov chain and queuing theory. The derived model calculates the buffer loss probability and the number of received packets at the final destination in the presence of congestion. Simulation results show that the analytical modelling of congestion has a good agreement with simulation. Next, the impact of congestion on 6LoWPAN networks is explored through simulations and real experiments where an extensive analysis is carried out with different scenarios and parameters. Analysis results show that when congestion occurs, the majority of packets are lost due to buffer overflow as compared to channel loss. Therefore, it is important to consider buffer occupancy in protocol design to improve network performance. Based on the analysis conclusion, a new IPv6 Routing Protocol for Low-Power and Lossy Network (RPL) routing metric called Buffer Occupancy is proposed that reduces the number of lost packets due to buffer overflow when congestion occurs. Also, a new RPL objective function called Congestion-Aware Objective Function (CA-OF) is presented. The proposed objective function works efficiently and improves the network performance by selecting less congested paths. However, sometimes the non-congested paths are not available and adapting the sending rates of source nodes is important to mitigate the congestion. Accordingly, the congestion problem is formulated as a non-cooperative game framework where the nodes (players) behave uncooperatively and demand high data rate in a selfish way. Based on this framework, a novel and simple congestion control mechanism called Game Theory based Congestion Control Framework (GTCCF) is proposed to adapt the sending rates of nodes and therefore, congestion can be solved. The existence and uniqueness of Nash equilibrium in the designed game is proved and the optimal game solution is computed by using Lagrange multipliers and Karush-Kuhn-Tucker (KKT) conditions. GTCCF is aware of node priorities and application priorities to support the IoT application requirements. On the other hand, combining and utilizing the resource control strategy (i.e. finding non-congested paths) and the traffic control strategy (i.e. adapting sending rate of nodes) into a hybrid scheme is important to efficiently utilize the network resources. Based on this, a novel congestion control algorithm called Optimization based Hybrid Congestion Alleviation (OHCA) is proposed. The proposed algorithm combines traffic control and resource control strategies into a hybrid solution by using the Network Utility Maximization (NUM) framework and a multi-attribute optimization methodology respectively. Also, the proposed algorithm is aware of node priorities and application priorities to support the IoT application requirements.
47
Aloisi, Alessandro. "Integrating wireless sensor networks and internet of things: A coap-based approach." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/8034/.
Full textAbstract:
L'obiettivo su cui è stata basata questa Tesi di
Laurea è stato quello di integrare la tecnologia delle Wireless Sensor Networks (WSN) al contesto dell'Internet delle cose (IoT). Per poter raggiungere questo obiettivo, il primo passo è stato quello di approfondire il concetto dell'Internet delle cose, in modo tale da comprendere se effettivamente fosse stato possibile applicarlo anche alle WSNs. Quindi è stata analizzata l'architettura delle WSNs e successivamente è stata fatta una ricerca per capire quali fossero stati i vari tipi di sistemi operativi e protocolli di comunicazione supportati da queste reti. Infine sono state studiate alcune IoT software platforms. Il secondo passo è stato quindi di implementare uno stack software che abilitasse la comunicazione tra WSNs e una IoT platform. Come protocollo applicativo da utilizzare per la comunicazione con le WSNs è stato usato CoAP. Lo sviluppo di questo stack ha consentito di estendere la piattaforma SensibleThings e il linguaggio di programmazione utilizzato è stato Java. Come terzo passo è stata effettuata una ricerca per comprendere a quale scenario di applicazione reale, lo stack software progettato potesse essere applicato. Successivamente, al fine di testare il corretto funzionamento dello stack CoAP, è stata sviluppata una proof of concept application che simulasse un sistema per la rilevazione di incendi.
Questo scenario era caratterizzato da due WSNs che inviavano la temperatura rilevata da sensori termici ad un terzo nodo che fungeva da control center, il cui compito era quello di capire se i valori ricevuti erano al di sopra di una certa soglia e quindi attivare un allarme. Infine, l'ultimo passo di questo lavoro
di tesi è stato quello di valutare le performance del sistema sviluppato. I parametri usati per effettuare queste valutazioni sono stati: tempi di durata delle richieste CoAP, overhead introdotto dallo stack CoAP alla piattaforma Sensible Things e la scalabilità di un particolare componente dello stack. I risultati di questi test hanno mostrato che la soluzione sviluppata in questa tesi ha introdotto un overheadmolto limitato alla piattaforma preesistente e inoltre che non tutte le richieste hanno la stessa durata, in quanto essa dipende dal tipo della richiesta inviata verso una WSN. Tuttavia, le performance del sistema potrebbero essere ulteriormente migliorate, ad esempio sviluppando un algoritmo che consenta la gestione concorrente di richieste CoAP multiple inviate da uno stesso nodo. Inoltre, poichè in questo lavoro di tesi non è stato considerato il problema della sicurezza, una possibile estensione al lavoro svolto potrebbe essere quello di implementare delle politiche per una comunicazione sicura tra Sensible Things e le WSNs.
48
Andersson, Matthew Anders. "Making good things happen: optimism and the range of personal social networks." Thesis, University of Iowa, 2010. https://ir.uiowa.edu/etd/775.
Full textAbstract:
Using the 2004 General Social Survey, I illuminate how dispositional optimism as a form of emotional capital enhances personal network range while also contributing to public goods through the formation of heterophilous ties. Network size and diversity are conceptualized as outcomes of optimistic functioning, which is marked by sociability, positive emotion, and problem-focused coping. I find that optimism is linked to substantial leverage in overall, non-kin, and extended network sizes on par with several years of education. Moreover, optimism yields more types of network heterophily than does educational attainment. I discuss limitations of the current study while also identifying future directions for research on emotional capital in the creation of social capital.
49
Quan, Yongyun. "Topology-based Device Self-identification in Wireless Mesh Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-261147.
Full textAbstract:
In the context of the Internet of Things (IoT), commissioning is the process of securely adding a new device to a network. It covers many different tasks, including the physical deployment of devices and configuration of parameters. It is network installers who need to manually commission each device one by one with the help of commissioning tools. In practice, the first task for a network installer is to identify each device correctly before configuring it with proper parameters. Individually identifying each device, especially in a large network, is a very time-consuming process. This is also known as the identification problem. This project is going to address the problem.A novel device identification approach is presented in the thesis, and there is no human intervention involved in the identification process. Devices are trying to identify themselves based on predefined rules and given information. The approach is therefore called device self-identification, and it is implemented in two different algorithms. One is the centralized device selfidentification, and the other is the distributed device self-identification. In short, only one device participates in the device identification process in the centralized approach, and in the distributed counterpart, every device is part of the identification process.The results of the implementations show the potential of the new way to identify devices in IoT. Devices in both the centralized approach and the distributed approach are able to identify themselves given necessary information about the network. A detailed discussion regarding the two proposed algorithms and the network information is presented in the thesis.I samband med Internet of Things (IoT) är igångkörning processen att säkert lägga till en ny enhet i ett nätverk. Den täcker många olika uppgifter, inklusive fysisk distribution av enheter och konfigurering av parametrar. Det är nätverksinstallatörer som måste manuellt beställa varje enhet en efter en med hjälp av installationsverktyg. I praktiken är den första uppgiften för en nätverksinstallatör att korrekt identifiera varje enhet innan den konfigureras med lämpliga parametrar. Att identifiera varje enhet speciellt i ett stort nätverk är en mycket tidskrävande process. Detta är också känt som identifieringsproblemet. Detta projekt kommer att ta itu med problemet.En nyhetsidentifieringsmetod presenteras i avhandlingen och det finns ingen mänsklig intervention involverad i identifieringsprocessen. Enheter försöker identifiera sig baserat på fördefinierade regler och information. Tillvägagångssättet kallas därför enhetens självidentifiering och det implementeras i två olika algoritmer, en är centraliserad enhetens självidentifiering och den andra är distribuerad enhetens självidentifiering. Kort sagt, endast en enhet deltar i enhetsidentifieringsprocessen i centraliserat tillvägagångssätt, och i distribuerad motsvarighet är varje enhet en del av identifieringsprocessen.Resultaten av implementationerna visar potentialen för det nya sättet att identifiera enheter i IoT. Enheter i både centraliserat tillvägagångssätt och distribuerat tillvägagångssätt kan identifiera sig med den information som krävs för nätverket. En detaljerad diskussion om de två föreslagna algoritmerna och nätverksinformationen presenteras i avhandlingen.
50
Corino, Gianni. "Internet of props : a performative ontology and design framework for the Internet of Things." Thesis, University of Plymouth, 2017. http://hdl.handle.net/10026.1/9511.
Full textAbstract:
Set in the relatively new and fast developing field of investigation known as Internet of Things (IoT), this research starts by looking at the lack of critical and conceptual reflection on the area. With a main research question that challenges the underlying concepts of the IoT, the study develops a performative design framework to critique the field of investigation. The main corpus consists of: 1. speculative inquiry into the ontological dualisms of ‘objects’ and ‘things’ and the emerging social dimension of humans and non-humans; 2. the identification of an ontological-performative model based on the idea of Props; 3. the entanglement of theory and practice to construct a performative design framework, called the Internet of Props, which includes: an enabling platform (Smarter Planet Lab) and a set of design strategies (Transactional Props) to demonstrate and evaluate this model and framework; 4. a combined-evaluation conversational analysis methodology that assesses the performativity of the setting and the Props, through linguistic and socio-behavioural studies. Inspired by the concepts of ontological theatre, the entanglement of humans and non-humans, and the Internet of People; the IoT is imagined and performed in a theory-driven, practice-based investigation of the Internet of Props, which aims to bring new theoretical and practical knowledge for the future of the IoT.