Thèses sur le sujet « SENCER NETWORKS »

Sensor networks have been recognised as one of the most advanced technologies of the 21st century with vast practical applications. The life of a sensor network is mainly determined by its energy consumption. Commercially available sensor nodes are battery driven devices. As most sensor nodes are deployed widely scattered and in isolated areas, replacing battery is not an option. This dissertation focuses on extending the lifespan of sensor networks by reducing energy consumption in design and operation of sensor nodes. The study goes in depth to analyse the state of art technology to achieve energy efficiency in sensor nodes and identify scope for further research in this field. In the architecture of sensor nodes, multipliers are the main blocks for designing an energy efficient processor. Vedic Mathematics provides principles of high speed multiplication. The main reason for power dissipation in multiplier circuit is due to power dissipation of full adder circuit. Low power multipliers have been designed by using low power adders. Motivated by this, a high speed Vedic multiplier has been designed using multiplexer based adder. When compared with existing Vedic multipliers, proposed designs showed significant improvement in reduction of delay and energy consumption. Sensor nodes consume maximum power during data communication. So processing data locally at each node in a sensor network is important for minimizing power consumption. High processing speed and low area designs are in ever growing demand. In order to predict outcomes, based on previous inputs, ALU can be designed with neurons. Processing speed of ALU can be improved by replacing conventional multipliers with Vedic multipliers. This research work suggests implementation of high speed ALU using Vedic neurons. The analysis of the results shows that the proposed design leads to x reduction in the delay and reduction in LUT count (an indicator of area) of the ALU. Use of energy efficient power amplifiers is an essential requirement for sensor nodes, as power amplifiers are responsible for the main power consumption in the transceivers of sensor nodes. Again, wider band width is another important requirement for power amplifiers used in sensor transceivers especially in wireless visual sensor networks and wireless multimedia sensor networks. Reliability of a power amplifier can be increased by designing it at smaller supply voltage. This thesis suggests improvements in design of power amplifier in class E configuration, for transceivers in wireless sensor nodes. In order to achieve wider band width, cascade of common drain followed by common source in class E configuration has been designed; and for more reliable operation with higher efficiency, class E in double cascoded has been implemented. The proposed designs, when simulated in SPICE, higher efficiencies and band widths have been achieved. This research also explored to design a robust solar energy harvesting system to enhance life time of sensor nodes. Proposed solar energy supply system mainly consists of a solar panel, rechargeable battery and a control circuit. To obtain sufficient voltage to charge battery, electrical energy generated through panel is boosted by boost converter. Different sensor nodes are supplied with energy from this system. An inverter is also designed for AC applications. Experimental results show that this compact, self-sufficient system enables outdoor based wireless sensor network nodes to operate successfully for longer periods.

Network programming is one of the most important applications in Wireless Sensor Networks as It provides an efficient way to update program Images running on sensor nodes without physical access to them. Securing these updates, however, remains a challenging and important issue, given the open deployment environment of sensor nodes. Though several security schemes have been proposed to impose the authenticity and Integrity protection on network programming applications, they are either energy Inefficient as they tend to use digital signature or lacks the data confidentiality. In addition, due to the absence of secure memory management in the current sensor hardware, the attacker could inject malicious code into the program flash by exploiting buffer overflow In the memory despite the secure code dissemination. The contribution of this thesis Is to provide two software-based security protocols and one hardware-based remote attestation protocol for network programming application. Our first protocol deploys multiple one-way key chains for a multi-hop sensor network. The scheme Is shown to be lower In computational, power consumption and communication costs yet still able to secure multi??hop propagation of program images. Our second protocol utilizes an Iterative hash structure to the data packets in network programming application, ensuring the data confidentiality and authenticity. In addition, we Integrated confidentiality and DoS-attack-resistance in a multi??hop code dissemination protocol. Our final solution is a hardware-based remote attestation protocol for verification of running codes on sensor nodes. An additional piece of tamper-proof hardware, Trusted Platform Module (TPM), is imposed into the sensor nodes. It secures the sensitive information (e.g., the session key) from attackers and monitors any platform environment changes with the Internal registers. With these features of TPM, the code Injection attack could be detected and removed when the contaminated nodes are challenged in our remote attestation protocol. We implement the first two software-based protocols with Deluge as the reference network programming protocol in TinyOS, evaluate them with the extensive simulation using TOSSIM and validate the simulation results with experiments using Tmote. We implement the remote attestation protocol on Fleck, a sensor platform developed by CSIRO that Integrates an Atmel TPM chip.

Wireless sensor networks (WSNs) have a wide variety of applications in civilian, medical and military applications. However, the nodes in such a network are limited to one type of action: sensing the environment. With increasing requirements for intelligent interaction with the environment, there is a need to not only perceive but also control the monitored environment. This has led to the emergence of a new class of networks, referred to as wireless sensor and actor networks (WSANs), capable of performing both sensing and acting tasks on the environment. The evolution from WSNs, which can be thought of as performing only read operations, to WSANs, which can perform both read and write operations, introduces unique and new challenges that need to be addressed. In this research, the fundamental challenges required for effective operation of WSANs are analyzed from the following three different perspectives: (i) operation correctness, (ii) resource optimality, and (iii) operation performance. The solutions proposed to address the challenges are evaluated with the optimal solution and other competing approaches through analytical and simulation results. The feasibility of the proposed solutions is demonstrated through a testbed implementation.

This paper explores how an all pair shortest path can be obtained in a wireless sensor network when sensors fail. Sensors are randomly deployed in a predefined geographical area, simulating the deployment of sensors from an airplane, and finding shortest path between all the sensors deployed based on distance. A major problem to address in wireless sensor networks is the impact of sensor failures on existing shortest paths in the network. An application is developed to simulate a network and find shortest paths affected by a sensor failure and find alternative shortest path. When a sensor fails, all the shortest paths and all the remaining sensors in the network are checked to see if the sensor failure has any impact on the network. Alternative shortest path is calculated for those paths affected by sensor failures.

This thesis is concerned with the design and analysis of new Bayesian network based mobility algorithms for mobile Wireless Sensor Networks (WSNs). The hypothesis for the work presented herein is that incorporating Artificial Intelligence (Al) at the level of the sensor nodes will improve their performance (coverage, connectivity and lifetime) and result in fault tolerance capabilities, in the face of uncertainty associated with incomplete information regarding the network. Two types of mobility strategy are presented and investigated. Firstly, a new gazing mobility strategy is presented which is biologically inspired from herbivores grazing pastures. As part of the latter strategy, and instead of deploying a large number of static sensor nodes to cover a region of interest, a smaller number of mobile nodes are deployed which migrate around the region to achieve coverage over time. To enable the performance evaluation of this strategy a new coverage measure called Coverage Against Time was created. A new decentralised Bayesian network based grazing mobility algorithm called BNGRAZ is presented which uses evidence derived from neighbouring nodes to predict the probability of performance (coverage and connectivity) changes associated with moving in a particular direction. Evidence is also obtained from a new Coverage Approximation (CA) algorithm which enables each sensor node to approximate the WSN coverage in order to determine areas in need of servicing. The performance of BNGRAZ is compared to a fixed path mobility technique, Random Waypoint (RWP) mobility model, and a new Grazing Reference Point Group Mobility (GRPGM) algorithm developed as part of this work. Secondly, a self-healing strategy which physically relocates sensor nodes to repair coverage holes, due to the failure of sensor nodes, is presented. A new decentralised Bayesian network based mobility algorithm called BayesMob, which uses local neighbour information, was created to coordinate the self-healing motion. The algorithm enables sensor nodes to predict the probability of an increase in coverage given a move in a particular direction to repair coverage holes. In addition, the thesis outlines the development of a WSN simulator. The latter provides a tool for evaluating the performance of mobile WSNs. All mobility strategies and algorithms discussed herein were simulated using the new WSN simulator.

Wireless Sensor Networks (WSNs) have been widely studied in the last decade because of the large set of applications that can be potentially enabled by this novel network paradigm, as environmental monitoring, home automation, localization and tracking of mobile users, seamless and ubiquitous data exchange. However, the severe constraints in terms of energy, processing, memory and reliability of the low--cost sensor devices left a number of unresolved problems, open to research. This thesis tackles two of the most interesting problems concerning WSNs, namely localization and traffic management. Accurate sensor localization is crucial for a wide variety of WSN applications and protocols, including monitoring, routing, scheduling, data fusion and so on. Typically, localization algorithms are based on an infrastructure of nodes which are aware of their geographical positions, called beacons. These nodes broadcast their coordinates in order to let the other nodes in the network, referred to as stray nodes, infer their own position by means of some estimation technique. The topic has been widely investigated, both in simulation and, more recently, in experimental testbeds. Nonetheless, the performance obtained by most of the proposed algorithms is still unsatisfactory, in particular in indoor environments. Therefore, further research is needed. In this thesis, the problem has been tackled from different perspectives, in order to gain a deep and clear understanding of the several facets that characterize this interesting domain. As a consequence, we collected a rather wide set of results that apparently may not seem to be strongly correlated, though they all fit within the same research project. As a first step, we compare well known localization algorithms in indoor environments for static networks, based on a Received Signal Strength Indicator (RSSI) ranging estimation technique. Results shed light on the actual potentialities and limits of common localization algorithms in indoor environments in a real testbed. In particular, we observed the strong impact of the shadowing random attenuation of the power of the received signal on the performance of the localization algorithms. Therefore, research has been addressed to the reduction of the shadowing term in the RSSI measures. To this end, we investigated the effect of the carrier frequency and of the antenna anisotropy on the randomness of the shadowing component, again using real measurements collected in different testbeds. Successively, our attention turned to the problem of beacon positioning that we observed may strongly affect the localization performance. We analyzed the optimal beacons placement both using an exhaustive but very complex approach and a heuristic scheme that provides close to optimal solutions while maintaining a linear complexity with the number of beacons. Looking at the localization performance separating the different effects of localization algorithms, channel parameters and beacon positioning, has been important to understand the contribution of each one of these aspects to the localization error and how much is it possible to improve the localization accuracy by means of a single technique, that usually is chosen depending on the particular scenario and available resources. Then nodes mobility has been included into the framework. We first considered an Autonomous Mobile Robot (AMR) that can interact with sensors, but is also capable to self--localize using onboard odometry. Leveraging on the complementarities of WSN and AMR, we considered the Simultaneous Localization and Mapping (SLAM) problem that consists in creating the map of an area without any a priori knowledge of the environment, while localizing the nodes in the WSN by combining the information provided by the WSN and by the AMR odometry. Second, we considered a completely mobile wireless networks in which heterogeneous nodes with different self--localization capabilities can interact one another on an opportunistic basis, exchanging localization information with other nodes that occasionally happen to be in geographical proximity. The performance of this scheme has been analyzed through a mathematical framework. We considered a Maximum Likelihood (ML) approach, a Linear Matrix Inequality (LMI) system and a simple heuristic strategy to define opportunistic localization algorithms. The validity of the mathematical model has been confirmed through experimental measures. We considered two main settings, one in which a node can rely on a single opportunistic interaction and one in which multiple contacts can be set while the node remains in the same position. We analyzed the different techniques, finding that in the first scenario, if the channel is not very noisy and the self--localization of the cooperative node quite accurate, the heuristic algorithm performs very well, in some case slightly better than ML, while the ML approach is very robust and improves localization accuracy even in difficult scenarios. If multiple interactions are available, then the heuristic technique is quite poor and it is better to rely on the LMI technique. Moreover LMI is quite flexible, because it does not require an initial guess of the position by the stray node and it can be used both with and without ranging information. The static scenario analysis was very useful to focus on the mobile localization. The design of the proposed algorithms and scenarios, the simulation parameters and limits, are strictly related to the knowledge of the channel behavior and localization performance gained from the previous studies. The opportunistic idea raises from two main considerations: the limited accuracy of the beacon based RSSI localization in a real scenario and the quite good ranging accuracy of RSSI when limiting the distance. Alongside the main research line concerning localization in WSN, during the Ph.D. we also investigated other research topics, namely traffic management and underwater sensor network, which are not directly related to the previous ones but still of great scientific and educational interest. The most significant achievements obtained in these areas have also been collected in the thesis for two reasons. First, these topics still belong to the context of wireless sensor networks, sharing some basic characteristics such as the assumptions of simplicity and energy constraints. Second, the excursion on different but correlated fields may potentially open new perspectives to well known problems, thus contributing to the innovation and the progress of the research. As mentioned, the second problem addressed in this thesis regards the traffic management in WSN. Usually all the nodes in a WSN send packets to a common node, called sink. This traffic pattern, under a certain load, can lead to congestion problems, causing packet losses, high delays and waste of energy. The proposed solutions in literature usually aim at detecting the occurence of congestion by involving in this task many nodes, sometimes the entire network. We propose a different protocol, called Efficient Packet Converge Casting (EPC$^2$), that mitigates the congestion at the sink involving only a fixed number of nodes, namely the sink's neighbors. Another scenario we look into was that of underwater wireless sensor networks (UWSNs), which enable a number of applications as for radio WSNs, fostering interest in this research field. Similarly to radio networks, the energy efficiency remains a main issue. Nodes are powered by battery and it is very important to extend the network lifetime as much as possible. The different characteristics of the environment in which nodes are deployed raise new research challenges that require novel protocol design. We addressed the energy efficiency problem in UWSN with two different approaches. First, we investigated the effect of duty--cycle and node density on the energy consumption of the network, assuming that nodes can use different power levels to transmit. Second, we proposed a channel management scheme to optimize the energy consumption, considering the strong relationship between distance, frequency and channel attenuation. Both solutions are very simple and suitable for the low--complexity underwater sensor devices and do not need any central unit to coordinate, but they work asyncronously and distributely.
Negli ultimi anni, le reti wireless di sensori (WSN) sono state molto studiate a causa delle numerose applicazioni in cui possono essere usate, come il monitoraggio ambientale, la domotica, la localizzazione e il tracking di utenti mobili. Le forti limitazioni dei nodi sensori in termini di energia, processamento, memoria e affidabilita', lasciano ancora aperti molti problemi per la ricerca. Questa tesi affronta due problemi molto importanti relativi alle reti wireless di sensori: la localizzazione e la gestione del traffico. Un'accurata localizzazione dei sensori e' importante per molte applicazioni per WSN, come monitoraggio, routing, scheduling, data fusion e molte altre. Tipicamente, gli algoritmi di localizzazione si basano su una infrastruttra di nodi, detti nodi ancora che conoscono la loro posizione geografica. Questi nodi trasmettono in broadcast le loro coordinate agli altri nodi della rete, che da queste informazioni ricavano la loro posizione tramite tecniche di stima. L'argomento e' stato largamente studiato, sia con simulazioni sia, piu' recentemente, con testbed sperimentali. Ciononostante, l'accuratezza ottenuta dalla maggior parte degli algoritmi proposti e' ancora insufficiente, soprattutto in ambienti interni. E' quindi necessario cercare nuove metodologie e nuovi approcci. In questa tesi, il problema e' stato affrontato da diversi punti di vista, in modo da capire in maniera piu' chiara e accurata i diversi aspetti che lo caratterizzano. Come conseguenza, abbiamo raccolto una vasta quantita' di dati che potrebbero apparire come non molto legati uno all'altro, ma che in realta' rientrano tutti nello stesso progetto di ricerca. Come primo passo, abbiamo confrontato algoritmi di localizzazione proposti in letteratura in uno scenario indoor e con nodi statici, stimando la distanza tra i nodi utilizzando la potenza del segnale ricevuto (RSSI). I risultati ci hanno permesso di capire le potenzialita' e i limiti dei piu' diffusi algoritmi di localizzazione in ambiente indoor e in un testbed reale. In particolare, abbiamo osservato il grande impatto che ha sulle prestazioni di localizzazione l'aleatorieta', data dal termine di shadowing, della misura di potenza ricevuta. Abbiamo quindi cercato delle strategie per ridurre la varianza di questo termine aleatorio. A questo scopo, abbiamo studiato l'effetto della frequenza della portante, utilizzando una stima della potenza ricevuta multi--canale, e l'impatto dell'anisotropia dell'antenna sulle oscillazioni dei valori di potenza ricevuta. Entrambi glil studi sono stati fatti con misure reali raccolte in diversi testbed. Successivamente, abbiamo analizzato il problema del posizionamento dei nodi ancora, dopo aver osservato l'incidenza che questo ha sull'accuratezza della localizzazione. Abbiamo confrontato il posizionamento ottimo dei nodi ancora usando sia una tecnica esaustiva, ma computazionalmente molto complessa, sia uno schema euristico che raggiunge prestazioni molto vicine all'ottimo pur mantenendo una complessita' lineare con il numero di ancore. Guardare alle prestazioni di localizzazione separando i diversi effetti degli algoritmi, dei parametri di canale e del posizionamento dei nodi ancora e' stato importante per capire il contributo dei diversi aspetti all'interno dell'errore di localizzazione e quanto sia possibile migliorare la precisione della localizzazione ottimizzando uno di questi aspetti, che solitamente viene scelto in base allo scenario e alle risorse disponibili. Quindi, abbiamo incluso nel nostro scenario anche nodi mobili. All'inizio abbiamo considerato un robot mobile (AMR) che poteva interagire con i sensori, ma anche capace di localizzarsi grazie all'odometria. Facendo leva sulla complementarieta' della rete di sensori e del robot mobile, abbiamo studiato e implementato un algoritmo di localizzazione e mappatura simultanea (SLAM), problema che consiste nel creare la mappa di un'area senza nessuna conoscenza a priori dell'ambiente e in contemporanea localizzare i nodi sensore confrontando le informazioni provenienti dai sensori e quelle ricavate dall'odometria del robot. Poi abbiamo considerato uno scenario piu' generale composto da nodi mobili ed eterogenei, con diverse capacita' di autolocalizzazione, che possono interagire uno con l'altro in modo opportunistico, scambiandosi informazioni di localizzazione con altri nodi che occasionalmente si trovano in prossimita'. Le prestazioni di questo schema sono state analizzate in un modello matematico. Abbiamo studiato un approccio a Massima Verosimiglianza (ML), uno basato su Linear Matrix Inequalities (LMI) e una semplice strategia euristica per definire gli algoritmi di localizzazione opportunistica. La validita' del modello matematico e' stata confermata attraverso misure sperimentali. Abbiamo considerato due scenari principali, uno in cui un nodo puo' contare su una sola interazione opportunistica e uno dove possono essere fatti contatti multipli mentre il nodo resta nella stessa posizione. Abbiamo analizzato le diverse tecniche, trovando che nel primo caso, se le informazioni di autolocalizzazione del nodo cooperatore e di ranging sono buone, l'algoritmo euristico ha buone prestazioni, a volte addirittura meglio della Massima Verosimiglianza, che invece e' estremamente robusto e riesce a migliorare la stima di localizzazione anche in scenari molto difficili. Se invece sono disponibili numerose interazioni, allora l'algoritmo euristico porta prestazioni scarse ed e' meglio utilizzare la tecnica LMI, specialmente utilizzando l'informazione di ranging. Inoltre l'LMI non richiede una conoscenza della posizione iniziale del nodo incognito. Lo scenario statico e' stato molto utile per studiare in maniera efficace la localizzazione mobile. La scelta degli algoritmi proposti e dello scenario, i parametri di simulazione e i limiti, sono strettamente legati a quello che abbiamo studiato riguardo al canale wireless e alle prestazioni di localizzazione nei lavori precedenti. L'idea dello scenario opportunistico infatti e' venuta a partire da due considerazioni: la limitata precisione della localizzazione con ancore basata su RSSI in uno scenario reale e la buona precisione nella stima di distanza con RSSI quando la distanza e' limitata. Affianco al principale filone di ricerca riguardante la localizzazione nelle WSN, durante il dottorato di ricerca abbiamo approfondito anche altri argomenti, come la gestione del traffico e le reti di sensori sottomarine, che non sono direttamente collegate con il tema principale, ma sono comunque di grande interesse scientifico. I risultati piu' significativi ottenuti in questi temi sono stati inseriti all'interno della tesi per due motivi. Innanzitutto, questi argomenti appartengono al contesto delle reti di sensori wireless, condividendo alcune caratteristiche di base quali l'assunzione di semplicita' e le limitazioni energetiche. Inoltre, il trattare campi diversi ma correlati, puo' aprire nuove prospettive a problemi noti, contribuendo cosi' all'innovazione della ricerca. Il secondo problema affrontato in questa tesi e' stato la gestione del traffico in reti di sensori wireless. Spesso, i nodi di una rete di sensori mandano i pacchetti ad un nodo comune, chiamato sink. Questo modello di traffico, quando il carico cresce, puo' portare a problemi di congestione, causando perdita di pacchetti, ritardi e spreco di energia. Le soluzioni proposte in letteratura solitamente cercando di individuare l'inizio di una congestione, utilizzando in questo compito molti nodi, talvolta l'intera rete. Il protocollo proposto, chiamato Efficient Packet Converge Casting (EPC$^2$), mitiga la congestione al sink, ma coinvolgnedo solo un numero fissato di nodi, i vicini del sink. Un altro scenario che abbiamo analizzato in questa tesi, sono state le reti sottomarine di sensori che, come nel caso delle reti radio, possono essere utilizzato per molteplici applicazioni e quindi hanno ricevuto molta attenzione dal mondo della ricerca. Similmente alle reti radio, l'efficienza energetica e' un problema molto sentito. I nodi sono alimentati a batteria ed e' molto importante incrementare la vita della rete il piu' possibile. La profonda diversita' dell'ambiente in cui i nodi sono disposti crea nuove sfide per la ricerca che richiedono la progettazione di nuovi protocolli. Abbiamo affrontato il problema dell'efficienza energetica in reti sottomarine con due diversi approcci. Abbiamo studiato l'effetto del duty--cycle and della densita' dei nodi sul consumo energetico della rete, assumendo che i nodi potessero usare diversi livelli di potenza in trasmissione. Quindi abbiamo proposto uno schema di utilizzazione della banda disponibile per ottimizzare il consumo energetico, facendo leva sulla forte relazione tra distanza, frequenza e attenuazione del canale. Entrambe le soluzioni sono molto semplici e adatte ai dispositivi sottomarini che hanno forti limitazioni. Inoltre non richiedono una unita' centrale per essere coordinate, ma operano in modo asincrono e distribuito.

In this study, we considered a heterogeneous, clustered WSN, which consists of two types of nodes (clusterheads and sensor nodes) deployed randomly over a sensing field. We investigated two cases based on how clusterheads can reach the sink: direct and multi-hop communication cases. Network dimensioning problems in randomly deployed WSNs are among the most challenging ones as the attributes of these networks are mostly non-deterministic. We focused on a number of network dimensioning problems based on the connected coverage concept, which is the degree of coverage achieved by only the connected devices. To evaluate connected coverage, we introduced the term cluster size, which is the expected value of the area covered by a clusterhead together with sensor nodes connected to it. We derived formulas for the cluster size and validated them by computer simulations. By using the cluster size formulas, we proposed a method to dimension a WSN for given targeted connected coverage. Furthermore, we formulated cost optimization problems for direct and multi-hop communication cases. These formulations utilize not only cluster size formulas but also the well-connectivity concept. We suggested some search heuristics to solve these optimization problems. Additionally, we justified that, in practical cases, node heterogeneity can provide lower cost solutions. We also investigated the lifetime of WSNs and for mulated a cost optimization problem with connected coverage and lifetime constraints. By solving this optimization problem, one can determine the number of nodes of each type and the initial energies of each type of node that leads to lowest cost solution while satisfying the minimum connected coverage and minimum lifetime requirements.

There are many works related to wireless sensor networks (WSNs) where authors present new protocols with better or enhanced features, others just compare their performance or present an application, but this work tries to provide a different perspective. Why don¿t we see the network as a whole and split it into groups to give better network performance regardless of the routing protocol? For this reason, in this thesis we demonstrate through simulations that node¿s grouping feature in WSN improves the network¿s behavior. We propose the creation of a group-based architecture, where nodes have the same functionality within the network. Each group has a head node, which defines the area in which the nodes of such group are located. Each node has a unique node identifier (nodeID). First group¿s node makes a group identifier (groupID). New nodes will know their groupID and nodeID of their neighbors. End nodes are, physically, the nodes that define a group. When there is an event on a node, this event is sent to all nodes in its group in order to take an appropriate action. End nodes have connections to other end nodes of neighboring groups and they will be used to send data to other groups or to receive information from other groups and to distribute it within their group. Links between end nodes of different groups are established mainly depending on their position, but if there are multiple possibilities, neighbor nodes could be selected based on their ability ¿, being ¿ a choice parameter taking into account several network and nodes parameters. In order to set group¿s boundaries, we can consider two options, namely: i) limiting the group¿s diameter of a maximum number of hops, and ii) establishing boundaries of covered area. In order to improve the proposed group-based architecture, we add collaboration between groups. A collaborative group-based network gives better performance to the group and to the whole system, thereby avoiding unnecessary message forwarding and additional overheads while saving energy. Grouping nodes also diminishes the average network delay while allowing scaling the network considerably. In order to offer an optimized monitoring process, and in order to offer the best reply in particular environments, group-based collaborative systems are needed. They will simplify the monitoring needs while offering direct control. Finally, we propose a marine application where a variant of this groupbased architecture could be applied and deployed.
García Pineda, M. (2013). A group-based architecture and protocol for wireless sensor networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/27599
TESIS
Premiado

In this thesis, a novel anti-sensor network paradigm is introduced against wireless sensor networks (WSN). Anti-sensor network (ASN) aims to destroy application reliability by adaptively and anonymously introducing adequate level of artificial distortion into the communication of the event features transported from the sensor nodes (SN) to the sink. ASN is composed of anti-sensor nodes (aSN) randomly distributed over the sensor network field. aSNs pretend to be SNs tomaintain anonymity and so improve resiliency against attack detection and prevention mechanisms. Performance evaluations via mathematical analysis and simulation experiments show that ASN can effectively reduce the application reliability of WSN.

Wireless Sensor Networks (WSNs) are the commonly applied information technologies of modern networking and computing platforms for application-specific systems. Today’s network computing applications are faced with high demand of reliable and powerful network functionalities. Hence, efficient network performance is central to the entire ecosystem, more especially where human life is a concern. However, effective management of WSNs remains a challenge due to problems supplemental to them. As a result, WSNs application systems such as in monitored environments, surveillance, aeronautics, medicine, processing and control, tend to suffer in terms of capacity to support compute intensive services due to limitations experienced on them. A recent technology shift proposes Software Defined Networking (SDN) for improving computing networks as well as enhancing network resource management, especially for life guarding systems. As an optimization strategy, a software-oriented approach for WSNs, known as Software Defined Wireless Sensor Network (SDWSN) is implemented to evolve, enhance and provide computing capacity to these resource constrained technologies. Software developmental strategies are applied with the focus to ensure efficient network management, introduce network flexibility and advance network innovation towards the maximum operation potential for WSNs application systems. The need to develop WSNs application systems which are powerful and scalable has grown tremendously due to their simplicity in implementation and application. Their nature of design serves as a potential direction for the much anticipated and resource abundant IoT networks. Information systems such as data analytics, shared computing resources, control systems, big data support, visualizations, system audits, artificial intelligence (AI), etc. are a necessity to everyday life of consumers. Such systems can greatly benefit from the SDN programmability strategy, in terms of improving how data is mined, analysed and committed to other parts of the system for greater functionality. This work proposes and implements SDN strategies for enhancing WSNs application systems especially for life critical systems. It also highlights implementation considerations for designing powerful WSNs application systems by focusing on system critical aspects that should not be disregarded when planning to improve core network functionalities. Due to their inherent challenges, WSN application systems lack robustness, reliability and scalability to support high computing demands. Anticipated systems must have greater capabilities to ubiquitously support many applications with flexible resources that can be easily accessed. To achieve this, such systems must incorporate powerful strategies for efficient data aggregation, query computations, communication and information presentation. The notion of applying machine learning methods to WSN systems is fairly new, though carries the potential to enhance WSN application technologies. This technological direction seeks to bring intelligent functionalities to WSN systems given the characteristics of wireless sensor nodes in terms of cooperative data transmission. With these technological aspects, a technical study is therefore conducted with a focus on WSN application systems as to how SDN strategies coupled with machine learning methods, can contribute with viable solutions on monitoring application systems to support and provide various applications and services with greater performance. To realize this, this work further proposes and implements machine learning (ML) methods coupled with SDN strategies to; enhance sensor data aggregation, introduce network flexibility, improve resource management, query processing and sensor information presentation. Hence, this work directly contributes to SDWSN strategies for monitoring application systems.
Thesis (PhD)--University of Pretoria, 2018.
National Research Foundation (NRF)
Telkom Centre of Excellence
Electrical, Electronic and Computer Engineering
PhD
Unrestricted

Monitoring the structural health of civil infrastructures with wireless sensor networks aids in detecting failures early, but faces power challenges in ensuring reasonable network lifetimes. Recharging select nodes with Unmanned Aerial Vehicles (UAVs) provides a solution that currently can recharge a single node; however, questions arise on the effectiveness of a limited recharging system, the appropriate node to recharge, and the best sink selection algorithm for improving network lifetime given a limited recharging system. This paper simulates such a network in order to answer those questions. This thesis first determines whether or not recharging with a UAV is an effective method of delivering limited power to the network. It then determines the best way to deliver that power. Finally, this thesis explores five different sink positioning algorithms to find which optimize the network lifetime by load-balancing the energy in the network, all in combination with the added capability of a UAV.

This dissertation presents methods of extending the network lifetime of multi-hop wireless sensor networks (WSNs) through routing that uses cooperative transmission (CT), referred to as cooperative routing. CT can have a signal-to-noise ratio (SNR) advantage over non-CT schemes through cooperative diversity and simple aggregation of transmit power, and one of its abilities is to extend the communication range of a wireless device using this SNR advantage. In this research, we use the range-extension ability of CT as a tool to mitigate the energy-hole problem of multi-hop WSNs and extend the network lifetime. The main contributions of this research are (i) an analytical model for a cooperative routing protocol with a deployment method, (ii) cooperative routing protocols that can extend the network lifetime, and (iii) formulating the lifetime-optimization problem for cooperative routing. The analytical model developed in this research theoretically proves that, in a situation where non-CT routing cannot avoid the energy-hole problem, our CT method can solve the problem. PROTECT, a CT method based on the analytical model, provides a very simple way of doing cooperative routing and can improve the lifetime of non-CT networks significantly. REACT, a cooperative routing protocol that uses the energy information of nodes, overcomes some of the limitations of PROTECT and can be applied to any existing non-CT routing protocol to improve the network lifetime. Using REACT and analytical approaches, we also show that cooperative routing can be beneficial in multi-hop energy-harvesting WSNs. By formulating and solving the lifetime-optimization problem of cooperative routing, which requires a much more sophisticated formulation than that of non-CT routing, we explore the optimal lifetime bounds and behaviors of cooperative routing. Finally, we study and design online cooperative routing methods that can perform close to the optimal cooperative routing.

The unique characteristics of sensor networks pose numerous challenges that have to be overcome to enable their efficient use. In particular, sensor networks are energy constrained because of their reliance on battery power. They can be composed of a large number of unreliable nodes. These characteristics render node collaboration essential to the accomplishment of the network task and justify the development of new algorithms to provide services such as routing, fault tolerance and naming. This work increases the knowledge on the growing field of sensor network algorithms by contributing a new evaluation tool and two new algorithms. A new sensor network simulator that can be used to evaluate sensor network algorithms is discussed. It incorporates models for the different functional units composing a sensor node and characterizes the energy consumption of each. It is designed in a modular and efficient way favoring the ease of use and extension. It allows the user to choose from different implementations of energy models, accuracy models and types of sensors. The second contribution of this thesis is a distributed algorithm to solve the unique ID assignment problem in sensor networks. Our solution starts by assigning long unique IDs and organizing nodes in a tree structure. This tree structure is used to compute the size of the network. Then, unique IDs are assigned using the minimum length. Globally unique IDs are useful in providing many network functions, e.g. node maintenance and security. Theoretical and simulation analysis of the ID assignment algorithm demonstrate that a high percentage of nodes are assigned unique IDs at the termination of the algorithm when the algorithm parameters are set properly. Furthermore, the algorithm terminates in a short time that scales well with the network size. The third contribution of this thesis is a general fault-tolerant event detection scheme that allows nodes to detect erroneous local decisions based on the local decisions reported by their neighbors. It can handle cases where nodes have different and dynamic accuracy levels. We prove analytically that the derived fault-tolerant estimator is optimal under the maximum a posteriori criterion. An equivalent weighted voting scheme is derived.

The development of miniaturized radio and sensing technologies have enabled the deployment of large quantities of wireless sensors capable of forming multi-hop networks. Emerging applications of this technology such as surveillance and disaster monitoring have throughput and efficiency requirements not met by current routing algorithms. These requirements are also shared by ad-hoc networks. Early routing protocols for these wireless networks were based on algorithms designed for wired networks. Geographic routing (routing based on position), was proposed. These algorithms perform poorly since they do not account for the fading and interference effects of wireless channels. Recent protocols that have attempted to account for the wireless channel focus on single-hop situations and are not readily extensible to multi-hop networks. In this thesis we present a framework for routing based on a distributed routing decision and provide several example protocols. This framework provides a cross-layer design where the routing decision is decided through silent negotiation between candidate relays. We investigate the performance and parameters of this framework. We then present an example protocol using this framework which provides low-overhead opportunistic routing using cooperative diversity. This protocol uses the intrinsic characteristics of the wireless channel to achieve diversity while still maintaining relatively low overhead. An adaptation of the protocol for heterogeneous networks equipped with multiple antennas has also been discussed and evaluated through simulations. We also investigate another protocol based on this framework using the product of the instantaneous packet reception rate and the marginal progress towards the destination as a routing metric, offering enhanced throughput.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California
There are a number of telemetry applications where it would be helpful to have networks of sensors that could autonomously discover their connectivity, and dynamically reconfigure themselves during use. A number of research groups have developed wireless ad-hoc sensor network systems. This paper reviews the state-of-the-art in wireless ad-hoc networks, examining the features, assumptions, limitations and unique attributes of some of the more popular solutions to this problem.

Recently, wireless sensor network (WSN) has become a promising technologywith a wide range of applications such as supply chain monitoringand environment surveillance. It is typically composed of multiple tiny devicesequipped with limited sensing, computing and wireless communicationcapabilities. Design of such networks presents several technique challengeswhile dealing with various requirements and diverse constraints. Performanceanalysis techniques are required to provide insight on design parametersand system behaviors.

Based on network calculus, we present a deterministic analysis methodfor evaluating the worst-case delay and buffer cost of sensor networks. Tothis end, three general traffic flow operators are proposed and their delayand buffer bounds are derived. These operators can be used in combinationto model any complex traffic flowing scenarios. Furthermore, the methodintegrates a variable duty cycle to allow the sensor nodes to operate at lowrates thus saving power. In an attempt to balance traffic load and improveresource utilization and performance, traffic splitting mechanisms areintroduced for mesh sensor networks. Based on network calculus, the delayand buffer bounds are derived in non-splitting and splitting scenarios.In addition, analysis of traffic splitting mechanisms are extended to sensornetworks with general topologies. To provide reliable data delivery in sensornetworks, retransmission has been adopted as one of the most popularschemes. We propose an analytical method to evaluate the maximum datatransmission delay and energy consumption of two types of retransmissionschemes: hop-by-hop retransmission and end-to-end retransmission.

We perform a case study of using sensor networks for a fresh food trackingsystem. Several experiments are carried out in the Omnet++ simulationenvironment. In order to validate the tightness of the two bounds obtainedby the analysis method, the simulation results and analytical results arecompared in the chain and mesh scenarios with various input traffic loads.From the results, we show that the analytic bounds are correct and tight.Therefore, network calculus is useful and accurate for performance analysisof wireless sensor network.

Ipack VINN Excellence Center

Wireless sensor networks are ad hoc networks of tiny battery powered sensor nodes that can organize themselves to form self-organized networks and collect information regarding temperature, light, and pressure in an area. Though the applications of sensor networks are very promising, sensor nodes are limited in their capability due to many factors. The main limitation of these battery powered nodes is energy. Sensor networks are expected to work for long periods of time once deployed and it becomes important to conserve the battery life of the nodes to extend network lifetime. This work examines non-uniform grid-based routing protocol as an effort to minimize energy consumption in the network and extend network lifetime. The entire test area is divided into non-uniformly shaped grids. Fixed source and sink nodes with unlimited energy are placed in the network. Sensor nodes with full battery life are deployed uniformly and randomly in the field. The source node floods the network with only the coordinator node active in each grid and the other nodes sleeping. The sink node traces the same route back to the source node through the same coordinators. This process continues till a coordinator node runs out of energy, when new coordinator nodes are elected to participate in routing. Thus the network stays alive till the link between the source and sink nodes is lost, i.e., the network is partitioned. This work explores the efficiency of the non-uniform grid-based routing protocol for different node densities and the non-uniform grid structure that best extends network lifetime.

The ways that people use libraries have changed drastically over the past few decades. Proliferation of computers and the internet have led to the purpose of libraries expanding from being only places where information is stored, to spaces where people teach, learn, create, and collaborate. Due to this, the ways that people occupy the space in a library have also changed. To keep up with these changes and improve patron experience, institutions collect data to determine how their spaces are being used. This thesis involves the development a system that collects, stores, and analyzes data relevant to occupancy to learn how a space is being utilized. Data is collected from a temperature and humidity sensor, passive Infrared sensor, and an Infrared thermal sensor array to observe people as they occupy and move through a space. Algorithms were developed to analyze the collected sensor data to determine how many people are occupying a space or the directions that people are moving through a space. The algorithms demonstrate the ability to track multiple people moving through a space as well as count the number of people in a space with an RMSE of roughly 0.39 people.

As the primary military operating environment shifts from the traditional battlefields to a more diverse urban environment, the use of remote wireless sensors is increasing. Traditional development and procurement methods are not capable of meeting the changing requirements and time constraints of commanders. To minimize the time to develop and deploy new systems, commercial solutions must be examined. The focus of this thesis is on the integration of Commercial Off-the-Shelf (COTS) components into a wireless multimedia sensor network. Because components from multiple vendors were utilized, different operating systems and transmission protocols had to be integrated across the network. The network must be capable of providing a varying Quality of Service (QoS) level depending on the active sensors in the network. To ensure the QoS level is met, an adaptive QoS algorithm was implemented in the wireless IEEE 802.11 router which monitored and measured the outgoing transmission interface; from which, it determined the latency and transmission jitter. Based on the results, the program can adjust the bandwidth as necessary. Finally, a user interface is developed that allows end users to monitor the network. The performance of the network is based on the end-to-end throughput, latency and jitter exhibited by the network.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2005.
Thesis Advisor(s): Alexander Bordetsky. Includes bibliographical references (p. 49-50). Also available online.

In the past research, smart sensor devices have become mature enough for large, distributed networks of such sensors to start to be deployed. Such networks can include tens or hundreds of independent nodes that can perform their functions without human interactions such as recharging of batteries, the configuration of network routes and others. Each of the sensors in the wireless sensor network is considered as microsystem, which consists of memory, processor, transducers and low bandwidth as well as a low range radio transceiver. This study investigates an adaptive sampling strategy for WSS aimed at reducing the number of data samples by sensing data only when a significant change in these processes is detected. This detection strategy is based on an extension to Holt's Method and statistical model. To investigate this strategy, the water consumption in a household is used as a case study. A query distribution approach is proposed, which is presented in detail in chapter 5. Our developed wireless sensor query engine is programmed on Sensinode testbed cc2430. The implemented model used on the wireless sensor platform and the architecture of the model is presented in chapters six, seven, and eight. This thesis presents a contribution by designing the experimental simulation setup and by developing the required database interface GUI sensing system, which enables the end user to send the inquiries to the sensor s network whenever needed, the On-Demand Query Sensing system ODQS is enhanced with a probabilistic model for the purpose of sensing only when the system is insufficient to answer the user queries. Moreover, a dynamic aggregation methodology is integrated so as to make the system more adaptive to query message costs. Dynamic on-demand approach for aggregated queries is implemented, based in a wireless sensor network by integrating the dynamic programming technique for the most optimal query decision, the optimality factor in our experiment is the query cost. In-network query processing of wireless sensor networks is discussed in detail in order to develop a more energy efficient approach to query processing. Initially, a survey of the research on existing WSN query processing approaches is presented. Building on this background, novel primary achievements includes an adaptive sampling mechanism and a dynamic query optimiser. These new approaches are extremely helpful when existing statistics are not sufficient to generate an optimal plan. There are two distinct aspects in query processing optimisation; query dynamic adaptive plans, which focus on improving the initial execution of a query, and dynamic adaptive statistics, which provide the best query execution plan to improve subsequent executions of the aggregation of on-demand queries requested by multiple end-users. In-network query processing is attractive to researchers developing user-friendly sensing systems. Since the sensors are a limited resource and battery powered devices, more robust features are recommended to limit the communication access to the sensor nodes in order to maximise the sensor lifetime. For this reason, a new architecture that combines a probability modelling technique with dynamic programming (DP) query processing to optimise the communication cost of queries is proposed. In this thesis, a dynamic technique to enhance the query engine for the interactive sensing system interface is developed. The probability technique is responsible for reducing communication costs for each query executed outside the wireless sensor networks. As remote sensors have limited resources and rely on battery power, control strategies should limit communication access to sensor nodes to maximise battery life. We propose an energy-efficient data acquisition system to extend the battery life of nodes in wireless sensor networks. The system considers a graph-based network structure, evaluates multiple query execution plans, and selects the best plan with the lowest cost obtained from an energy consumption model. Also, a genetic algorithm is used to analyse the performance of the approach. Experimental testing are provided to demonstrate the proposed on-demand sensing system capabilities to successfully predict the query answer injected by the on-demand sensing system end-user based-on a sensor network architecture and input query statement attributes and the query engine ability to determine the best and close to the optimal execution plan, given specific constraints of these query attributes . As a result of the above, the thesis contributes to the state-of-art in a network distributed wireless sensor network query design, implementation, analysis, evaluation, performance and optimisation.

Thesis (M.S.)--University of Missouri-Columbia, 2005.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (July 17, 2006) Includes bibliographical references.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California
Sensor networks can demand large amounts of bandwidth if the raw sensor data is transferred to a central location. Feature recognition and sensor fusion algorithms can reduce this bandwidth. Unfortunately the designers of the system, having not yet seen the data which will be collected, may not know which algorithms should be used at the time the system is first installed. This paper describes a flexible architecture which allows the deployment of data reduction algorithms throughout the network while the system is in service. The network of sensors approach not only allows for signal processing to be pushed closer to the sensor, but helps accommodate extensions to the system in a very efficient and structured manner.

Wireless sensor networks are composed of sensor nodes, which can monitor an environment and observe events of interest. These networks are applied in various fields including but not limited to environmental, industrial and habitat monitoring. In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to find sensor node's positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. I do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. I show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes share linearity. The more the non-linearity, the better the localization. The localization for our network design proves better when I place anchor nodes at right angles.

Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, tactical surveillance, and mine reconnaissance. The enabling technology for these applications is acoustic wireless networking. UnderWater Acoustic Sensor Networks (UW-ASNs) consist of sensors and Autonomous Underwater Vehicles (AUVs) deployed to perform collaborative monitoring tasks. The objective of this research is to explore fundamental key aspects of underwater acoustic communications, propose communication architectures for UW-ASNs, and develop efficient sensor communication protocols tailored for the underwater environment. Specifically, different deployment strategies for UW-ASNs are studied, and statistical deployment analysis for different architectures is provided. Moreover, a model characterizing the underwater acoustic channel utilization efficiency is introduced. The model allows setting the optimal packet size for underwater communications. Two distributed routing algorithms are proposed for delay-insensitive and delay-sensitive applications. The proposed routing solutions allow each node to select its next hop, with the objective of minimizing the energy consumption taking the different application requirements into account. In addition, a resilient routing solution to guarantee survivability of the network to node and link failures in long-term monitoring missions is developed. Moreover, a distributed Medium Access Control (MAC) protocol for UW-ASNs is proposed. It is a transmitter-based code division multiple access scheme that incorporates a novel closed-loop distributed algorithm to set the optimal transmit power and code length. It aims at achieving high network throughput, low channel access delay, and low energy consumption. Finally, an efficient cross-layer communication solution tailored for multimedia traffic (i.e., video and audio streams, still images, and scalar sensor data) is introduced.

Wireless sensor network is an intelligent network system which has the self-monitoring functionality. It consists of many low-cost, low-power and small-sized sensor nodes that can communicate with each other to perform sensing and data processing. Acting as an important role in the system, network coverage usually has a huge effect on the system’s lifetime.In this thesis, particle swarm algorithm was used as a method to optimize the coverage in the coverage of wireless sensor network. A network coverage optimization strategy based on particle swarm optimization was proposed and MATLAB was used as a tool to apply the algorithm. The model used in this thesis is the probability sensing model and the coverage type is area coverage. Effectiveness of the algorithm is proved by simulation. The simulation of the algorithm suggests the optimal deployment can be determined if a certain parameter which in this thesis is the sensing range is given.

Approved for public release, distribution is unlimited
The objective of this research is to analyze the network performance and sensor functionality, efficacy and usability of IEEE 802.x wireless MESH networks within a DoD Tactical network environment. Multiple sensor configurations operating with wireless MESH network technologies will be researched and analyzed for performance in expeditionary environment situations. Specifically, this thesis will attempt establish the foundation for the development of wireless MESH "network health" models by examining the performance of sensors operating within a MESH network and define which network performance metrics equate to good quality of service. This research will experiment with different application, sensor, and network configurations of currently available COTS components, such as, voice, video and data hardware. This thesis will lay the groundwork for wireless network MESH predictability, which will enable the optimal use of sensors within a tactical network environment.
Lieutenant Commander, United States Navy

With the coming growth in Internet of Things (IoT) applications, we can expect environ-ments with many independent networks operating in nearby locations. Wireless Sensor Networks (WSN), which have become popular during the last few years, are the main type of networks used in IoT. The IEEE 802.15.4 protocol designed for low-rate wireless personal area networks has been widely adopted for this kind of network. Together with ZigBee, this protocol is gaining increasing interest from the industry, as they are con-sidered a universal solution for low-cost, low-power, wireless connected monitoring and control devices. Internetwork interference issues in IEEE 802.15.4 networks can be a ma-jor problem because of the extensive use of wireless channels. In this thesis, an in-depth simulation study of the internetwork interferences is performed using Castalia, a widely used network simulator. We focus on the beacon collision problem, as it has been proved to be the main cause of performance degradation for coexisting networks. We carry out a prestudy of the main node simulation parameters to setup the different scenarios. Then, we evaluate how the overlap of the active periods and the location of the nodes affect the network performance. We continue with a network coexistence analysis to study the inter-action of two networks of two nodes and their performance regarding the beacon reception rate. We show that there are significantly different operation regions, depending on the network location. Following this, a probabilistic analysis is carried out in order to obtain an average beacon reception rate depending on the size of the area considered. Finally, we discuss available beacon collisions avoidance methods, taking into account the detailed simulation results. Our conclusions have theoretical and practical implications for the design of wireless sensor networks, and for the evaluation of beacon collisions avoidance schemes.
Med den kommande tillväxten i sakernas Internet (IoT) applikationer är miljöer med många oberoende nätverk som verkar på närliggande ställen väntat. Trådlösa sensornätverk (WSN), som har blivit populära under de senaste åren, är den vanligaste typen av nät som används i sakernas Internet. IEEE 802.15.4 protokollen, konstruerad för låghastighet trådlösa personlig area nätverk, har fått stor spridning för WSNs. Tillsammans med ZigBee, får de en snabb ökat intresse från industrin, eftersom de betraktas som en universallösning för låg kostnad låg energi trådlös anslutning för övervaknings- och kontrollinstrument. Internätverk interferens i IEEE 802.15.4 nätverk kan vara ett stort problem på grund av den omfattande användningen av trådlösa kanaler. I denna avhandling är en djupgående simulation studie utfört med hjälp av Castalia, ett utbrett använt nätverk simulator. Vi fokuserar på beacon kollisionsproblem, eftersom det har visat sig vara den främsta orsaken till prestandaförsämring för samexisterande nätverk. Vi utför en förstudie av den viktigaste simulation parametrarna för att bestemma de olika scenarierna. Sedan utvärderar vi hur överlappningen av de aktiva perioderna och placeringen av noderna påverkar nätverkets prestanda. Vi fortsätter med en nätverksamexistens analys för att studera interaktionen mellan två nätverk av två noder, och deras prestanda avseende beacon mottagnings kvot. Vi visar att det finns betydligt olika operationsområdena, beroende på nätverksens placering. Därefter är en sannolikhetsanalys utfört för att erhålla en genomsnittlig beacon mottagnings kvot, beroende på storleken på betraktade områden. Slutligen diskuterar vi tillgängliga metoder för att undvika beacon kollision, med hänsyn till de detaljerade simuleringsresultaten. Våra slutsatser har teoretiska och praktiska kon-sekvenser för utformningen av trådlösa sensornätverk, och för utvärderingen a metoder för att undvika beacon kollision.

In this thesis we present LaSLAT, a sensor network algorithm thatsimultaneously localizes sensors, calibrates sensing hardware, andtracks unconstrained moving targets using only range measurementsbetween the sensors and the target. LaSLAT is based on a Bayesian filter, which updates a probabilitydistribution over the quantities of interest as measurementsarrive. The algorithm is distributable, and requires only a constantamount of space with respect to the number of measurementsincorporated. LaSLAT is easy to adapt to new types of hardware and newphysical environments due to its use of intuitive probabilitydistributions: one adaptation demonstrated in this thesis uses amixture measurement model to detect and compensate for bad acousticrange measurements due to echoes.We also present results from a centralized Java implementation ofLaSLAT on both two- and three-dimensional sensor networks in whichranges are obtained using the Cricket ranging system. LaSLAT is ableto localize sensors to within several centimeters of their groundtruth positions while recovering a range measurement bias for eachsensor and the complete trajectory of the mobile.

Wireless sensor networks have become increasingly popular in many applications such as environment monitoring and law enforcement. Data aggregation is a method used to reduce network traffic but cannot be used together with conventional encryption schemes because it is not secure and introduces extra overhead. Homomorphic encryption is an encryption scheme that allows data processing on encrypted data as opposed to plaintext. It has the benefit that each intermediate node does not have to decrypt each packet, but the resulting cyphertext is usually much larger than the original plaintext. This could negatively affect system performance because the energy consumption of each node is directly proportional to the amount of data it transmits. This study investigates the benefits and drawback of using homomorphic encryption in the aggregation process particularly in the context of scalable networks. It was found that conventional encryption outperforms the homomorphic encryption for smaller networks, but as the network size grows, homomorphic encryption starts outperforming conventional encryption. It was also found that the homomorphic encryption scheme does significantly reduce the performance of plaintext aggregation. This performance reduction will however be acceptable for most applications where security is a concern.
Draadlose sensornetwerke raak toenemend meer gewild vir heelwat verskillende toepassings, soos byvoorbeeld opgewingsmonitering en wetstoepassing. Data-aggregasie is n metode wat gebruik word om netwerkverkeer te verminder, maar kan nie gebruik word saam met konvensionele enkripsie-skemas nie, omdat dit nie veilig is nie en oorhoofse koste verhoog. Homomorfiese enkripsie is n enkripsie-skema wat dataverwerking toelaat op geënkripteerde in teenstelling met gewone-teks. Dit het die voordeel dat elke intermediêre nie nodig het om elke pakkie te dekripteer nie, maar die resulterende kodeteks is gewoonlik heelwat groter as die gewone-teks. Dit kan die stelselgedrag negatief beÏnvloed omdat die energieverbruik van elke node eweredig is aan die hoeveelheid data wat dit versend. Hierdie studie ondersoek die voor- en nadele van homomorfiese enkripsie in die aggregasieproses, veral in die konteks van skaleerbare netwerke. Daar is gevind dat konvensionele enkripsie beter vaar as homomorfies enkripsie in kleiner netwerke. Die omgekeerde is waar vir groter netwerke. Dit is ook gevind dat homomorfiese enkripsie gewone-teks-aggregasie negatief beÏnvloed, maar dit word as aanvaarbaar beskou vir toepassings waar sekuriteit belangrik is.
Dissertation (MEng)--University of Pretoria, 2015.
Electrical, Electronic and Computer Engineering
Meng
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An energy-aware on-demand Bluetooth scatternet formation and routing protocol taking into account network architecture and traffic pattern is proposed. The scatternet formation protocol is able to cope with multiple sources initiating traffic simultaneously as well as prolong network lifetime. A modified Inquiry scheme using extended ID packet is introduced for fast device discovery and power efficient propagation of route request messages with low delay. A mechanism employing POLL packets in Page processes is proposed to transfer scatternet formation and route reply information without extra overhead. In addition, the energy aware forwarding nodes selection scheme is based on local information and results in more uniform network resource utilization and improved network lifetime. Simulation results show that this protocol can provide scatternet formation with reasonable delay and with good load balance which results in prolonged network lifetime for Bluetooth-based wireless sensor networks. In this research, a metric-based scatternet formation algorithm for the Bluetooth-based sensor motes is presented. It optimizes the Bluetooth network formation from the hop distance and link quality perspectives. In addition, a smart repair mechanism is proposed to deal with link/node failure and recover the network connectivity promptly with low overhead. The experiments with the Intel Mote platform demonstrate the effectiveness of the optimizations. This research also investigates the scalability of ad hoc routing protocols in very large-scale wireless ad hoc networks. A comprehensive simulation study is conducted of the performance of an on-demand routing protocol on a very large-scale, with as many as 50,000 nodes in the network. The scalability analysis is addressed based on various network sizes, node density, traffic load, and mobility. The reasons for packet loss are analyzed and categorized at each network layer. Based on the observations, we observe the effect of the parameter selection and try to exhaust the scalability boundary of the on-demand routing protocol for wireless ad hoc networks.