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Статті в журналах з теми "Edge Networking"
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Adams, Robert. "Data Networking: A Competitive Edge." Industrial Management & Data Systems 86, no. 5/6 (May 1986): 13–15. http://dx.doi.org/10.1108/eb057441.
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Gudhka, Drashti. "Computer Network." International Journal for Research in Applied Science and Engineering Technology 12, no. 1 (January 31, 2024): 78–87. http://dx.doi.org/10.22214/ijraset.2024.57862.
Повний текст джерелаАнотація:
Abstract: This paper presents a comprehensive overview of computer networking, covering fundamental concepts and modern advancements. It explores core networking principles, including models, architectures, and essential layers. Emphasising contemporary trends, it delves into topics like network security (Zero Trust Architecture, AI/ML), Software-Defined Networking (SDN), IoT security challenges, 5G and Mobile Edge Computing (MEC), network performance optimisation, Big Data analytics, and eco-friendly networking strategies. Aimed at students, researchers, and professionals, this overview serves as a valuable resource for understanding both foundational principles and cutting-edge developments in networking.
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Xin, Jing, and Jia Pin Xu. "Based on Edge Node Network Service Recognition Research." Applied Mechanics and Materials 55-57 (May 2011): 1473–78. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.1473.
Повний текст джерелаАнотація:
At present, the recognition ability of the service recognition technique is limited to single installation. It leads to recognition error easily and it's dangerous for the Next Generation Networks which depend on service recognition and control. This paper is based on TCP/IP architecture. With the studying of the present service recognition techniques, a model of networking service recognition system based on edge node is designed. And using the modeling recognition method, the information exchange among recognition nodes, and the second recognition, dynamic recognition of networking service flow is implemented. The testing result of the networking service recognition system model is that, at different protocol types and different ports, the recognition rate is from 99.39% to 99.89%, which indicates that the networking service recognition system based on edge nodes can meet the service recognition requirements of the Next Generation Networks.
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Domet, Jack J., T. M. Rajkumar Domet, and David Yen. "MULTIMEDIA NETWORKING A Leading-Edge Communication Technology." Information Systems Management 11, no. 4 (January 1994): 39–45. http://dx.doi.org/10.1080/07399019408964669.
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Shiwen Mao, Y. T. Hou, and Min-You Wu. "Exploiting edge capability for wireless sensor networking." IEEE Wireless Communications 15, no. 4 (August 2008): 67–73. http://dx.doi.org/10.1109/mwc.2008.4599223.
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Prieto, Javier, and Ramón J. Durán Barroso. "Emerging Technologies in Edge Computing and Networking." Sensors 24, no. 4 (February 17, 2024): 1271. http://dx.doi.org/10.3390/s24041271.
Повний текст джерелаАнотація:
The global evolution of the Internet is experiencing a notable and inevitable change towards a convergent scenario known as the Internet of Things (IoT), where a large number of devices with heterogeneous characteristics and requirements have to be interconnected to serve different verticals, such as smart cities, intelligent transportation systems, smart grids, (ITS) or e-health [...]
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Wang, Dan, Fangming Liu, Wei Bao, Lin Wang, Jiangchuan Liu, Yuanyuan Yang, and Weisong Shi. "Editorial of CCF transactions on networking: special issue on edge computing and networking." CCF Transactions on Networking 2, no. 1 (May 3, 2019): 1–3. http://dx.doi.org/10.1007/s42045-019-00017-7.
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Mastorakis, Spyridon, Abderrahmen Mtibaa, Jonathan Lee, and Satyajayant Misra. "ICedge: When Edge Computing Meets Information-Centric Networking." IEEE Internet of Things Journal 7, no. 5 (May 2020): 4203–17. http://dx.doi.org/10.1109/jiot.2020.2966924.
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Wei, Hung-Yu, Tao Zhang, T. Russell Hsing, and Doug Zuckerman. "Future Trends in Fog/Edge Computing and Networking." IEEE Communications Magazine 61, no. 12 (December 2023): 38–39. http://dx.doi.org/10.1109/mcom.2023.10375689.
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Ros, Seyha, Prohim Tam, Inseok Song, Seungwoo Kang, and Seokhoon Kim. "A survey on state-of-the-art experimental simulations for privacy-preserving federated learning in intelligent networking." Electronic Research Archive 32, no. 2 (2024): 1333–64. http://dx.doi.org/10.3934/era.2024062.
Повний текст джерелаАнотація:
<abstract> <p>Federated learning (FL) provides a collaborative framework that enables intelligent networking devices to train a shared model without the need to share local data. FL has been applied in communication networks, which offers the dual advantage of preserving user privacy and reducing communication overhead. Networking systems and FL are highly complementary. Networking environments provide critical support for data acquisition, edge computing capabilities, round communication/connectivity, and scalable topologies. In turn, FL can leverage capabilities to achieve learning adaptation, low-latency operation, edge intelligence, personalization, and, notably, privacy preservation. In our review, we gather relevant literature and open-source platforms that point out the feasibility of conducting experiments at the confluence of FL and intelligent networking. Our review is structured around key sections, including the introduction of FL concepts, the background of FL applied in networking, and experimental simulations covering networking for FL and FL for networking. Additionally, we delved into case studies showcasing FL potential in optimizing state-of-the-art network optimization objectives, such as learning performance, quality of service, energy, and cost. We also addressed the challenges and outlined future research directions that provide valuable guidance to researchers and practitioners in this trending field.</p> </abstract>
Дисертації з теми "Edge Networking"
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Peraccini, Simone. "Named Data Networking for Computing in the Mobile Edge." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/17059/.
Повний текст джерелаАнотація:
Oggi connettersi a Internet è una pratica di uso comune, destinata a crescere notevolmente con l'avvento dell'Internet of Things. Nonostante il grande successo, Internet presenta diversi limiti architetturali che lo rendono un veicolo povero in confronto alla grande mole di contenuti trasmessi. La seconda importante limitazione riguarda la sicurezza che è applicata solamente a livello di host ma non di contenuto. Per promuovere la prototipizzazione di nuovi paradigmi architetturali, nel 2010 la National Science Fondation crea il programma Future Internet Architecture. Tra i progetti nati, il più emergente è Named Data Networking(NDN). Il suo intento è quello di distogliere l'attenzione da "dove" trovare una risorsa per concentrarsi su "cosa" applicazioni e utenti cerchino. Per questo NDN pensa che l'identificazione non debba più riguardare gli host ma i contenuti. Quest'ultimi sono distinti da un nome univoco, godono di immutabilità e racchiudono la strategia di sicurezza.
L'obiettivo di questo progetto è quello di dare un piccolo contributo a Named Data Networking, ideando e sviluppando un protocollo di computazione cooperativa, che operi per mezzo del protocollo NDN. L'intento del protocollo è quello di permettere a generici dispositivi wifi di assegnare l'esecuzione di alcuni dei loro task ad un nodo nelle vicinanze. Inoltre, la tesi accenna come il protocollo si inserisca nel tema dell'Edge computing, che assieme al Fog computing pone le basi per l'evoluzione dell'architettura Cloud.
Il lavoro ha portato alla realizzazione di un prototipo del protocollo che è possibile installare sui nodi del simulatore di reti ndnSIM. Esso soddisfa i comportamenti base richiesti ed offre buone prestazioni negli scenari statici. L'elaborato si conclude con alcuni test che ne confermano il corretto funzionamento ma allo stesso tempo denotano alcuni aspetti da migliorare negli sviluppi futuri.
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Rajakaruna, A. (Archana). "Lightweight edge-based networking architecture for low-power IoT devices." Master's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201906072483.
Повний текст джерелаАнотація:
Abstract. The involvement of low power Internet of Things (IoT) devices in the Wireless Sensor Networks (WSN) allow enhanced autonomous monitoring capability in many application areas. Recently, the principles of edge computing paradigm have been used to cater onsite processing and managing actions in WSNs. However, WSNs deployed in remote sites require human involvement in data collection process since internet accessibility is still limited to population dense areas. Nowadays, researchers propose UAVs for monitoring applications where human involvement is required frequently. In this thesis work, we introduce an edge-based architecture which create end-to-end secure communication between IoT sensors in a remote WSN and central cloud via UAV, which assist the data collection, processing and managing procedures of the remote WSN. Since power is a limited resource, we propose Bluetooth Low Energy (BLE) as the communication media between UAV and sensors in the WSN, where BLE is considered as an ultra-low power radio access technology. To examine the performance of the system model, we have presented a simulation analysis considering three sensor nodes array types that can realize in the practical environment. The impact of BLE data rate, impact of speed of the UAV, impact of distance between adjacent sensors and impact of data generation rate of the sensor node have been analysed to examine the performance of system. Moreover, to observe the practical functionality of the proposed architecture, prototype implementation is presented using commercially available off-the-shelf devices. The prototype of the system is implemented assuming ideal environment.
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Krishna, Nitesh. "Software-Defined Computational Offloading for Mobile Edge Computing." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37580.
Повний текст джерелаАнотація:
Computational offloading advances the deployment of Mobile Edge Computing (MEC) in the next generation communication networks. However, the distributed nature of the mobile users and the complex applications make it challenging to schedule the tasks reasonably among multiple devices. Therefore, by leveraging the idea of Software-Defined Networking (SDN) and Service Composition (SC), we propose a Software-Defined Service Composition model (SDSC). In this model, the SDSC controller is deployed at the edge of the network and composes service in a centralized manner to reduce the latency of the task execution and the traffic on the access links by satisfying the user-specific requirement. We formulate the low latency service composition as a Constraint Satisfaction Problem (CSP) to make it a user-centric approach. With the advent of the SDN, the global view and the control of the entire network are made available to the network controller which is further leveraged by our SDSC approach.
Furthermore, the service discovery and the offloading of tasks are designed for MEC environment so that the users can have a complex and robust system. Moreover, this approach performs the task execution in a distributed manner. We also define the QoS model which provides the composition rule that forms the best possible service composition at the time of need.
Moreover, we have extended our SDSC model to involve the constant mobility of the mobile devices. To solve the mobility issue, we propose a mobility model and a mobility-aware QoS approach enabled in the SDSC model. The experimental simulation results demonstrate that our approach can obtain better performance than the energy saving greedy algorithm and the random offloading approach in a mobile environment.
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SAPIO, AMEDEO. "Distributed services across the network from edge to core." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2706995.
Повний текст джерелаАнотація:
The current internet architecture is evolving from a simple carrier of bits to a platform able to provide multiple complex services running across the entire Network Service Provider (NSP) infrastructure. This calls for increased flexibility in resource management and allocation to provide dedicated, on-demand network services, leveraging a distributed infrastructure consisting of heterogeneous devices. More specifically, NSPs rely on a plethora of low-cost Customer Premise Equipment (CPE), as well as more powerful appliances at the edge of the network and in dedicated data-centers.
Currently a great research effort is spent to provide this flexibility through Fog computing, Network Functions Virtualization (NFV), and data plane programmability. Fog computing or Edge computing extends the compute and storage capabilities to the edge of the network, closer to the rapidly growing number of connected devices and applications that consume cloud services and generate massive amounts of data. A complementary technology is NFV, a network architecture concept targeting the execution of software Network Functions (NFs) in isolated Virtual Machines (VMs), potentially sharing a pool of general-purpose hosts, rather than running on dedicated hardware (i.e., appliances). Such a solution enables virtual network appliances (i.e., VMs executing network functions) to be provisioned, allocated a different amount of resources, and possibly moved across data centers in little time, which is key in ensuring that the network can keep up with the flexibility in the provisioning and deployment of virtual hosts in today’s virtualized data centers. Moreover, recent advances in networking hardware have introduced new programmable network devices that can efficiently execute complex operations at line rate. As a result, NFs can be (partially or entirely) folded into the network, speeding up the execution of distributed services.
The work described in this Ph.D. thesis aims at showing how various network services can be deployed throughout the NSP infrastructure, accommodating to the different hardware capabilities of various appliances, by applying and extending the above-mentioned solutions. First, we consider a data center environment and the deployment of (virtualized) NFs. In this scenario, we introduce a novel methodology for the modelization of different NFs aimed at estimating their performance on different execution platforms. Moreover, we propose to extend the traditional NFV deployment outside of the data center to leverage the entire NSP infrastructure. This can be achieved by integrating native NFs, commonly available in low-cost CPEs, with an existing NFV framework. This facilitates the provision of services that require NFs close to the end user (e.g., IPsec terminator). On the other hand, resource-hungry virtualized NFs are run in the NSP data center, where they can take advantage of the superior computing and storage capabilities.
As an application, we also present a novel technique to deploy a distributed service, specifically a web filter, to leverage both the low latency of a CPE and the computational power of a data center. We then show that also the core network, today dedicated solely to packet routing, can be exploited to provide useful services. In particular, we propose a novel method to provide distributed network services in core network devices by means of task distribution and a seamless coordination among the peers involved. The aim is to transform existing network nodes (e.g., routers, switches, access points) into a highly distributed data acquisition and processing platform, which will significantly reduce the storage requirements at the Network Operations Center and the packet duplication overhead.
Finally, we propose to use new programmable network devices in data center networks to provide much needed services to distributed applications. By offloading part of the computation directly to the networking hardware, we show that it is possible to reduce both the network traffic and the overall job completion time.
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Aouadj, Messaoud. "AirNet, le modèle de virtualisation « Edge-Fabric » comme plan de contrôle pour les réseaux programmables." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30138/document.
Повний текст джерелаАнотація:
Les travaux de cette thèse s'inscrivent dans le contexte général des réseaux logiciels, dits "Software-Defined Networking" (SDN). Ce paradigme récent est l'une des initiatives les plus notables pour rendre les réseaux actuels programmables ou, en d'autres termes, plus simple à configurer, à tester, à corriger et à faire évoluer. Dans un écosystème SDN, l'interface nord (Northbound API) est utilisée par l'administrateur réseaux pour définir ses politiques et programmer le plan de contrôle, elle représente donc un enjeu majeur. Idéalement, cette interface nord devrait permettre aux administrateurs de décrire, le plus simplement possible, des services réseaux et leurs interactions, plutôt que de spécifier comment et sur quels équipements physiques ils doivent être déployés. Des travaux existants montrent que cela peut être notamment réalisé grâce à des solutions de virtualisation de réseaux et des langages de programmation dédiés de haut niveau. L'objectif de ce travail de thèse est de proposer une nouvelle interface nord qui, d'une part, exploiterait la virtualisation de réseau et, d'autre part, exposerait ses services sous la forme d'un langage de programmation dédié. Actuellement, plusieurs langages intégrant des solutions de virtualisation de réseau existent. Néanmoins, nous pensons que les modèles d'abstraction qu'ils utilisent pour construire des réseaux virtuels restent inappropriés pour assurer des critères de simplicité, modularité et flexibilité des topologies virtuelles et des programmes de contrôle. Dans ce contexte, nous proposons un nouveau langage de contrôle de réseaux nommé AirNet. Ce dernier intègre un modèle d'abstraction dont la principale caractéristique est d'offrir une séparation nette entre les équipements de bordure (Edge) et de cœur de réseau (Fabric). Cette idée est bien connue et acceptée dans le domaine des architectures réseaux. L'originalité de notre contribution étant de faire remonter ce concept au niveau du plan de contrôle virtuel et non de le restreindre au seul plan physique. Ainsi, des frontières logiques entre les différents types de politiques existeront (fonctions de contrôle et de données vs. fonctions de transport), garantissant ainsi la modularité et la réutilisabilité de tout ou partie du programme de contrôle. De plus, dans l'approche proposée, la définition du réseau virtuel et des politiques peut être totalement dissociée de l'infrastructure physique cible, favorisant ainsi la portabilité des applications de contrôle. Une implémentation du langage AirNet a également été réalisée. Ce prototype inclut en particulier une bibliothèque des primitives et opérateurs du langage, ainsi qu'un hyperviseur qui assure la composition des politiques de contrôle sur un réseau virtuel, et leur transposition (mapping) sur l'infrastructure physique. Afin de s'appuyer sur des contrôleurs SDN existants, l'hyperviseur inclut des modules d'intégration des contrôleurs POX et RYU. Une validation expérimentale a été menée sur différents cas d'étude (filtrage, répartition de charge, authentification dynamique, limitation de bande passante, etc.) dont les résultats attestent de la faisabilité de la solution. Enfin, des mesures de performances ont montré que le surcoût apporté par cette nouvelle couche d'abstraction est parfaitement acceptableThe work of this thesis falls within the general context of software-defined networking (SDN). This new paradigm is one of the most significant initiatives to enable networks programmability or, in other words, to make current networks easier to configure, test, debug and evolve. Within an SDN ecosystem, the Northbound interface is used by network administrators to define policies and to program the control plane, it thus represents a major challenge. Ideally, this northbound interface should allow administrators to describe, as simply as possible, network services and their interactions, rather than specifying how and on what physical device they need to be deployed. Current related works show that this can be partly achieved through virtualization solutions and high-level domain specific languages (DSL). The objective of this thesis is to propose a new Northbound interface which will, on the one hand, rely on network virtualization and, on the other hand, expose its services as a domain specific programming language. Currently, several languages that include network virtualization solutions exist. Nevertheless, we believe that the abstract models they are using to build virtual networks remain inadequate to ensure simplicity, modularity and flexibility of virtual topologies and control programs. In this context, we propose a new network control language named AirNet. Our language is built on top of an abstraction model whose main feature is to provide a clear separation between edge and core network devices. This concept is a well-known and accepted idea within the network designer community. The originality of our contribution is to lift up this concept at the virtual control plane, not limiting it solely at the physical plane. Thus, logical boundaries between different types of policies will exist (control and data functions vs. transport functions), ensuring modularity and reusability of the control program. Moreover, in the proposed approach, the definition of the virtual network and policies is totally dissociated from the target physical infrastructure, promoting the portability of control applications. An implementation of the AirNet language has also been done. This prototype includes in particular a library that implements the primitives and operators of the language, and a hypervisor that achieves the composition of the control policies on the virtual network, and their mapping on the physical infrastructure. In order to rely on existing SDN controllers, the hypervisor includes integration modules for the POX and RYU controllers. An experimental validation has been also conducted on different use cases (filtering, load balancing, dynamic authentication, bandwidth throttling, etc.), whose results demonstrate the feasibility of our solution. Finally, performance measurements have shown that the additional cost brought by this new abstraction layer is perfectly acceptable
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Zacarias, Iulisloi. "Employing concepts of the SDN paradigm to support last-mile military tactical edge networks." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/183191.
Повний текст джерелаАнотація:
Em um futuro próximo, “dispositivos inteligentes” serão massivamente empregados em campos de batalha. Essa já é uma realidade, porém, o número de dispositivos utilizados em campos de batalha tende a aumentar em ordens de magnitude. As redes de comunicação de dados serão essenciais para transmitir os dados que esses dispositivos coletam e transformá-los em informações valiosas utilizadas como suporte à atuação humana. O suporte à tomada de decisão, ou mesmo níveis de autonomia, permitindo que estes dispositivos coordenem outros dispositivos, exigem comunicação contínua. Desafios relacionados à comunicação surgirão devido à dinamicidade do ambiente. A configuração da rede deve refletir decisões superiores automaticamente. A grande escala das redes conectando os altos escalões, tropas, veículos e sensores, aliada à falta de padronização dos dispositivos, tornará a integração destes desafiadora. Em um ambiente tão heterogêneo, muitos protocolos e tecnologias coexistirão. As redes de campo de batalha são um elemento de suma importância nas operações militares modernas e conceito de guerra centrada em rede é uma tendência sem volta e influencia desde os altos escalões até o controle de tropas Embora estudos tenham sido realizados nessa área, a maioria deles aborda redes estratégicas de alto nível e portanto não levam em conta as “redes táticas de última milha” (TEN), que compreendem dispositivos de comunicação com recursos limitados, como sensores ou ainda pequenos veículos aéreos não tripulados. Em uma tentativa de preencher esta lacuna, esse trabalho propõe uma arquitetura que combina conceitos dos paradigmas de redes definidas por software (SDN) juntamente com redes tolerantes à atraso/disrupçoes (DTN), para aplicação em redes táticas de última milha. O uso de SDN em cenários com nodos móveis é avaliado considerando uma aplicação de vigilância que utiliza streaming de vídeo e medidas de Qualidade de Experiência (QoE) de usuário são coletadas. Com base nos resultados obtidos, uma aplicação em conjunto dos conceitos de SDN e DTN é proposta, além disso abordamos a escolha do nodo que atuará como controlador SDN na rede. Os experimentos foram executados utilizando um emulador de redes. Apesar de pesquisas adicionais serem necessárias – considerado requisitos de segurança, por exemplo – os resultados foram promissores e demonstram a aplicabilidade destes conceitos no cenários das TENs.The future battlefield tends to be populated by a plethora of “intelligent things”. In some ways, this is already a reality, but in future battlefields, the number of deployed things should be orders of magnitude higher. Networked communication is essential to take real advantage of the deployed devices on the battlefield, and to transform the data collected by them into information valuable for the human warfighters. Support for human decision making and even a level of autonomy, allowing devices to coordinate and interact with each other to execute their activities in a collaborative way require continuous communication. Challenges regarding communication will arise from the high dynamics of the environment. The network adaption and management should occur autonomously, and it should reflect upper-level decisions. The large scale of the network connecting high-level echelons, troops on the field, and sensors of many types, beside the lack of communication standards turn the integration of the devices more challenging. In such a heterogeneous environment, many protocols and communication technologies coexist. This way, battlefield networks is an element of paramount importance in modern military operations Additionally, a change of paradigm regarding levels of autonomy and cooperation between humans and machines is in course and the concept of network-centric warfare is a no way back trend. Although new studies have been carried out in this area, most of these concern higher-level strategic networks, with abundant resources. Thus, these studies fail to take into account the “last-mile Tactical Edge Network (TEN) level,” which comprises resource constrained communication devices carried by troopers, sensor nodes deployed on the field or small unmanned aerial vehicles. In an attempt to fill this gap, this work proposes an architecture combining concepts from software-defined networking (SDN) paradigm and the delay-tolerant approach to support applications in the last-mile TEN. First, the use of SDN in dynamic scenarios regarding node positioning is evaluated through a surveillance application using video streaming and Quality of Experience (QoE) measures are captured on the video player. We also explore the election of nodes to act as SDN Controllers in the TEN environment. The experiments use emulator for SDN with support to wireless networks. Further investigation is required, for example, considering security requirements, however the results are promising and demonstrate the applicability of this architecture in the TEN network scenario.
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Sadat, Mohammad Nazmus. "QoE-Aware Video Communication in Emerging Network Architectures." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin162766498933367.
Повний текст джерела
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Mekki, Mohamed. "Enabling Zero-Touch Cloud Edge Computing Continuum Management." Electronic Thesis or Diss., Sorbonne université, 2024. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2024SORUS231.pdf.
Повний текст джерелаАнотація:
La maturation de la provision et de la gestion des infrastructures de cloud computing et d'edge computing a engendré le Cloud Edge Computing Continuum (CECC), facilitant le déploiement et la migration d'applications entre les infrastructures cloud centralisées et les infrastructures edge décentralisées. Cette transition a donné vie à des nouveaux cas d'utilisation dans des secteurs tels que l'Internet Industriel des Objets (IIoT), les véhicules autonomes et la réalité augmentée, tous profitant de cette architecture distribuée. Ces domaines d'application requièrent à la fois la scalabilité des centres de données massifs du cloud traditionnel et la faible latence des infrastructures edge computing. Les progrès technologiques, tels que la virtualisation, la conteneurisation et les réseaux 5G, ont facilité le développement d'applications CECC, passant des architectures monolithiques aux microservices. L'orchestration efficace des applications CECC est essentielle pour garantir la performance et optimiser l'utilisation des ressources. Cette thèse propose des solutions pour la gestion automatisée du CECC, se concentrant sur la collecte de données de supervision, la compréhension du fonctionnement des applications et de l'infrastructure, et la prise de décisions sur le placement la migration et l'adaptation des ressources des applications. Dans la première contribution de cette thèse, nous proposons un framework de supervision de services multi-domaines de bout en bout. De tels services consistent en des applications et des fonctions réseau qui s'étendent sur plusieurs domaines technologiques, chacun présentant ses propres intrications uniques. Le système de supervision proposé utilise une structure unifiée des Key Performance Indicators (KPIs), abstrayant efficacement toutes les complexités sous-jacentes. Des tests approfondis dans différents scénarios valident la scalabilité du framework et sa capacité à superviser un grand nombre de services simultanément. La prochaine étape de la thèse impliquait le profilage des applications, dans lequel nous avons mené une étude expérimentale pour explorer le comportement de différents types d'applications dans des environnements cloud-native. Cette étude met en évidence l'incapacité des propriétaires d'applications à configurer les ressources appropriées pour leurs applications afin de fonctionner de manière optimale sans entraîner de gaspillage des ressources d'infrastructure. Ensuite, nous avons utilisé des techniques de machine learning et d'eXplainable AI (XAI) pour construire des modèles capables de prédire la dégradation des performances des applications, en utilisant des ensembles de données générés à partir de notre étude. Lorsque le modèle prédit un déclin des performances de l'application, le module XAI fournit des explications pour la sortie du modèle, facilitant l'identification de la cause profonde de la dégradation du service. Cette cause profonde est ensuite traitée par le gestionnaire d'application.Le parcours de cette thèse s'est conclu par la proposition d'une architecture pour la gestion du cycle de vie des applications CECC. Cette architecture utilise des profils d'application et d'infrastructure pour déployer et migrer des applications tout en tenant compte de l'empreinte carbone du déploiement CECC.Le principal défi réside dans la représentation concrète du profil d'application de manière à pouvoir spécifier les exigences actuelles et futures de l'application. Ce défi a été relevé en représentant efficacement le profil d'application pour faciliter la dérivation des exigences actuelles et futures de l'applicationThe maturation of cloud computing and edge computing infrastructure provisioning and management has led to the emergence of Cloud Edge Computing Continuum (CECC). CECC enables seamless deployment and migration of applications between centralized cloud infrastructures and decentralized edge infrastructure. This evolution has driven new use cases across industries, including Industrial Internet of Things (IIoT), autonomous vehicles, and augmented reality, all benefiting from this distributed architecture.These use cases require scalability and storage from massive data centers typical of traditional cloud computing, as well as the low latency and high bandwidth offered by edge computing infrastructures. Several factors enable the development and deployment of applications to fully leverage CECC : advancements in application deployment technologies like virtualization and containerization, a shift in application architecture and development methodology towards microservices architectures, and innovations in networking technologies such as 5G mobile networks. Efficiently orchestrating applications within the CECC framework is crucial for meeting performance requirements and optimizing infrastructure resource utilization. This thesis proposes solutions for zero-touch management of CECC, focusing on automated monitoring, profiling, and decision-making processes. These solutions aim to automate application management, facilitating seamless orchestration and resource optimization.In the first contribution, a novel monitoring system for multi-domain services is proposed, utilizing a unified structure for Key Performance Indicators (KPIs) to abstract underlying technologies. This scalable system monitors end-to-end network slices, including Radio Access Network (RAN), Core Network (CN), and Cloud/Edge domains.The second contribution presents results from an experimental study aiming to detect if a tenant's configuration allows running its service optimally. The study provides insights on detecting and correcting performance degradation due to misconfiguration of service resources.Moving towards decision-making of a CECC manager, the third contribution proposes a Zero-Touch Service Management (ZSM) framework featuring a fine-granular computing resource scaler in a cloud-native environment. The scaler uses AI/ML models to predict microservice performances, with an XAI module conducting root-cause analysis for service degradation. Afterwards, the proposed framework scales only the needed resources (i.e., CPU or memory) to overcome the service degradation. Finally, in the last contribution, an architecture of CECC Application Orchestrator is proposed, leveraging applications and infrastructures profiling for efficient management. These profiles represent current and future applications' requirements, guiding decision-making processes (placement, resources scaling. migration) to minimize carbon footprint and deployment costs
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Da, Silva Silvestre Guthemberg. "Designing Adaptive Replication Schemes for Efficient Content Delivery in Edge Networks." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2013. http://tel.archives-ouvertes.fr/tel-00931562.
Повний текст джерелаАнотація:
La disponibilité des contenus partagés en ligne devient un élément essentiel pour toute la chaîne de distribution de vidéos. Pour fournir des contenus aux utilisateurs avec une excellente disponibilité et répondre à leurs exigences toujours croissantes, les opérateurs de content delivery networks (CDNs) doivent assurer une haute qualité de services, définie par des métriques comme le taux de transfert ou la latence inclus dans les contrats de Service Level Agreement (SLA). La réplication adaptative se présente comme un mécanisme de stockage très prometteur pour at- teindre cet objectif. Par contre, une question importante reste encore ouverte: comment assurer la mise en place de ces SLAs, tout en évitant le gaspillage de ressources? Le sujet de la thèse porte précisément sur l'étude et l'évaluation de systèmes de réplication de données pour la nouvelle génération de CDNs hybrides, dont une partie des ressources de réseaux et de stockage proviennent de l'équipement des utilisateurs. Pour cela, nous proposons (i) une architecture de gestion de ressources des utilisateurs nommée Caju, et (ii) trois nouveaux systèmes de réplication adaptatifs, AREN, Hermes, et WiseReplica. Des simulations précises avec Caju montrent que nos systèmes de réplication adaptatifs sont très performants et peuvent être facilement étendus à d'autres types d'architecture. Comme perspectives, nous comptons réaliser le développement et l'évaluation d'un prototype proof-of-concept sur PlanetLab.
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Aguiari, Davide. "Exploring Computing Continuum in IoT Systems : sensing, communicating and processing at the Network Edge." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS131.
Повний текст джерелаАнотація:
L'Internet des objets (IoT), ne comprenant à l'origine que quelques dispositifs de détection simple, atteint aujourd’hui 34 milliards d’objets connectés d'ici fin 2020. Ces objets ne peuvent plus être définis comme de simples capteurs de surveillance. Les capacités de l'IoT ont été améliorées ces dernières années tandis-que que les capacités de calcul et de stockage de masse sont devenus des marchandises. Aux débuts de l'IoT, le traitement et le stockage étaient généralement effectués dans le cloud. Les nouvelles architectures IoT sont capables d'exécuter des tâches complexes directement sur l'appareil, permettant ainsi le concept d'un continuum de calcul étendu. Les scénarios critiques et temps réel, comme par exemple la détection de véhicules autonomes, la surveillance de zone ou le sauvetage en cas de catastrophe, nécessitent que l’ensemble des acteurs impliqués soient coordonnés et collaborent sans interaction humaine vers un objectif commun, partageant des données et des ressources, même dans les zones couvertes par des réseaux intermittents. Cela pose de nouveaux problèmes dans les systèmes distribués, la gestion des ressources, l'orchestration des appareils et le traitement des données. Ce travail propose un nouveau cadre de communication et d'orchestration, à savoir le C-Continuum, conçu dans des architectures IoT hétérogènes à travers plusieurs scénarios d'application. Ce travail se concentre pour gérer les ressources sur deux macro-scénarios clés de durabilité : (a) la détection et la sensibilisation à l'environnement, et (b) le soutien à la mobilité électrique. Dans le premier cas, un mécanisme de mesure de la qualité de l'air sur une longue période avec différentes applications à l'échelle mondiale (3 continents et 4 pays) est introduit. Le système a été développé en interne depuis la conception du capteur jusqu'aux opérations de mist-computing effectuées par les nœuds. Dans le deuxième scénario une technique pour transmettre de grandes quantités de données, entre un véhicule en mouvement et un centre de contrôle est proposé. Ces données sont de haute granularité temporelle relatives et permettent conjointement d'allouer des tâches sur demande dans le continuum de calculAs Internet of Things (IoT), originally comprising of only a few simple sensing devices, reaches 34 billion units by the end of 2020, they cannot be defined as merely monitoring sensors anymore. IoT capabilities have been improved in recent years as relatively large internal computation and storage capacity are becoming a commodity. In the early days of IoT, processing and storage were typically performed in cloud. New IoT architectures are able to perform complex tasks directly on-device, thus enabling the concept of an extended computational continuum. Real-time critical scenarios e.g. autonomous vehicles sensing, area surveying or disaster rescue and recovery require all the actors involved to be coordinated and collaborate without human interaction to a common goal, sharing data and resources, even in intermittent networks covered areas. This poses new problems in distributed systems, resource management, device orchestration,as well as data processing. This work proposes a new orchestration and communication framework, namely CContinuum, designed to manage resources in heterogeneous IoT architectures across multiple application scenarios. This work focuses on two key sustainability macroscenarios: (a) environmental sensing and awareness, and (b) electric mobility support. In the first case a mechanism to measure air quality over a long period of time for different applications at global scale (3 continents 4 countries) is introduced. The system has been developed in-house from the sensor design to the mist-computing operations performed by the nodes. In the second scenario, a technique to transmit large amounts of fine-time granularity battery data from a moving vehicle to a control center is proposed jointly with the ability of allocating tasks on demand within the computing continuum
Книги з теми "Edge Networking"
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Dale, Dougherty, and Koman Richard, eds. 2001 P2P networking overview: The emergent P2P platform of presence, identity, and edge resources. Sebastopol, CA: O'Reilly & Associates, 2001.
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2
Victoria, Rosenborg, ed. Technology edge: A guide to multimedia. Carmel, Ind: New Riders Pub, 1993.
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3
AGHA, Loygue. Edge Networking : Internet des Edges Hb: Edge Networking. ISTE Editions Ltd., 2022.
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4
Loygue, Pauline, Guy Pujolle, and Khaldoun Al Agha. Edge Networking: Internet of Edges. Wiley & Sons, Incorporated, John, 2022.
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Loygue, Pauline, Guy Pujolle, and Khaldoun Al Agha. Edge Networking: Internet of Edges. Wiley & Sons, Incorporated, John, 2022.
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Loygue, Pauline, Guy Pujolle, and Khaldoun Al Agha. Edge Networking: Internet of Edges. Wiley & Sons, Incorporated, John, 2022.
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7
Loygue, Pauline, Guy Pujolle, and Khaldoun Al Agha. Edge Networking: Internet of Edges. Wiley & Sons, Incorporated, John, 2022.
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8
Haddadou, Kamel. Cloud and Edge Networking. Wiley & Sons, Incorporated, John, 2023.
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Haddadou, Kamel. Cloud and Edge Networking. Wiley & Sons, Incorporated, John, 2023.
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Haddadou, Kamel. Cloud and Edge Networking. Wiley & Sons, Incorporated, John, 2023.
Знайти повний текст джерелаЧастини книг з теми "Edge Networking"
1
Pinho, André C., Alexandre A. Santos, Daniel R. Figueiredo, and Felipe M. G. França. "Two ID-Free Distributed Distance-2 Edge Coloring Algorithms for WSNs." In NETWORKING 2009, 919–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01399-7_72.
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Li, Lanhui, and Tiejun Lv. "Pricing-Based Partial Computation Offloading in Mobile Edge Computing." In Communications and Networking, 3–14. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41114-5_1.
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Ren, Yanling, Zhihui Weng, Yuanjiang Li, Zhibin Xie, Kening Song, and Xiaolei Sun. "Distributed Task Splitting and Offloading in Mobile Edge Computing." In Communications and Networking, 33–42. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41114-5_3.
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Xu, Fangmin, Huanyu Ye, Shaohua Cui, Chenglin Zhao, and Haipeng Yao. "Software Defined Industrial Network: Architecture and Edge Offloading Strategy." In Communications and Networking, 46–56. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06161-6_5.
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Watanabe, Ryu, Ayumu Kubota, and Jun Kurihara. "Resource Authorization Methods for Edge Computing." In Advanced Information Networking and Applications, 167–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99584-3_15.
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An, Li, and Xin Su. "Cloud-Edge Collaboration Based Data Mining for Power Distribution Networks." In Communications and Networking, 438–51. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99200-2_33.
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Tomar, Kavish, Sarishma Dangi, and Sachin Sharma. "Edge computing-enabled secure information-centric networking." In Advances in Cyber Security and Intelligent Analytics, 1–26. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003269144-1.
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Bruschi, Francesco, Marco Zanghieri, Michele Terziani, and Donatella Sciuto. "Decentralized Updates of IoT and Edge Devices." In Advanced Information Networking and Applications, 161–70. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57931-8_16.
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Zanussi, Luca, Daniele Tessera, Luisa Massari, and Maria Carla Calzarossa. "Workflow Scheduling in the Cloud-Edge Continuum." In Advanced Information Networking and Applications, 182–90. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57931-8_18.
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D’Aniello, Giuseppe, Matteo Gaeta, Francesco Flammini, and Giancarlo Fortino. "Situation Awareness in the Cloud-Edge Continuum." In Advanced Information Networking and Applications, 307–16. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57931-8_30.
Повний текст джерелаТези доповідей конференцій з теми "Edge Networking"
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Liang, Weifa. "AoI-Aware Query Services in Digital-TwinEmpowered Edge Computing." In 2024 IFIP Networking Conference (IFIP Networking), 2. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619776.
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Oikonomou, Efthymios, Stefanos Plastras, Dimitrios Tsoumatidis, Dimitrios N. Skoutas, and Angelos Rouskas. "Workload Prediction for Efficient Node Management in Mobile Edge Computing." In 2024 IFIP Networking Conference (IFIP Networking), 461–67. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619775.
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Olliaro, D., V. Mancuso, P. Castagno, M. Sereno, and M. Ajmone Marsan. "Gaming on the Edge: Performance Issues of Distributed Online Gaming." In 2024 IFIP Networking Conference (IFIP Networking), 259–67. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619768.
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Al Azad, Md Washik, and Spyridon Mastorakis. "Deduplicator: When Computation Reuse Meets Load Balancing at the Network Edge." In 2024 IFIP Networking Conference (IFIP Networking), 448–54. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619734.
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Zou, Yan, Tian Pan, Lu Lu, Zhiqiang Li, Kehan Yao, Yan Mu, Ying Wan, Tao Huang, and Yunjie Liu. "HyperSFC: State-Intensive Service Function Chaining on Hyper-Converged Edge Infrastructure." In 2024 IFIP Networking Conference (IFIP Networking), 1–9. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619908.
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Deka, Sikha, and Radhika Sukapuram. "Edge Service Caching with Delayed Hits and Request Forwarding to Reduce Latency." In 2024 IFIP Networking Conference (IFIP Networking), 792–97. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619791.
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Xiao, Ke, Jiaxin Wang, Chaofei Li, Zhenwei Yu, and Feifei Gao. "Private Edge Computing Resource Allocation and Communication Optimization Based on Federated Learning." In 2024 IFIP Networking Conference (IFIP Networking), 601–6. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619751.
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Zhang, Yuncan, and Weifa Liang. "Cost-Aware Digital Twin Migration in Mobile Edge Computing via Deep Reinforcement Learning." In 2024 IFIP Networking Conference (IFIP Networking), 441–47. IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619837.
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Koukis, Georgios, Sotiris Skaperas, Ioanna Angeliki Kapetanidou, Lefteris Mamatas, and Vassilis Tsaoussidis. "Performance Evaluation of Kubernetes Networking Approaches across Constraint Edge Environments." In 2024 IEEE Symposium on Computers and Communications (ISCC), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/iscc61673.2024.10733726.
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Mtibaa, Abderrahmen, Reza Tourani, Satyajayant Misra, Jeff Burke, and Lixia Zhang. "Towards Edge Computing over Named Data Networking." In 2018 IEEE International Conference on Edge Computing (EDGE). IEEE, 2018. http://dx.doi.org/10.1109/edge.2018.00023.
Повний текст джерелаЗвіти організацій з теми "Edge Networking"
1
Carpenter, Marie, and William Lazonick. The Pursuit of Shareholder Value: Cisco’s Transformation from Innovation to Financialization. Institute for New Economic Thinking Working Paper Series, February 2023. http://dx.doi.org/10.36687/inetwp202.
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Once the global leader in telecommunication systems and the Internet, over the past two decades the United States has fallen behind global competitors, and in particular China, in mobile communication infrastructure—specifically 5G and Internet of Things (IoT). This national failure, with the socioeconomic and geopolitical tensions that it creates, is not due to a lack of US government investment in the knowledge required for the mobility revolution. Nor is it because of a dearth of domestic demand for the equipment, devices, and applications that can make use of this infrastructure. Rather, the problem is the dereliction of key US-based business corporations to take the lead in making the investments in organizational learning required to generate cutting edge communication-infrastructure products. No company in the United States exemplifies this deficiency more than Cisco Systems, the business corporation founded in Silicon Valley in 1984 that had explosive growth in the 1990s to become the foremost global enterprise-networking equipment producer in the Internet revolution. This paper provides in-depth analysis of Cisco’s organizational failure, attributing it ultimately to the company’s turn from innovation in the last decades of 20th century to financialization in the early decades of the 21st century. Since 2001, Cisco’s top management has chosen to allocate corporate cash to open-market share repurchases— aka stock buybacks—for the purpose of giving manipulative boosts to the company stock price rather than make the investments in organizational learning required to become a world leader in communication-infrastructure equipment for the era of 5G and IoT. From October 2001 through October 2022, Cisco spent $152.3 billion—95 percent of its net income over the period—on stock buybacks for the purpose of propping up its stock price. These funds wasted in pursuit of “maximizing shareholder value” were on top of the $55.5 billion that Cisco paid out to shareholders in dividends, representing an additional 35 percent of net income. In this paper, we trace how Cisco grew from a Silicon Valley startup in 1984 to become, through its innovative products, the world leader in enterprise-networking equipment over the next decade and a half. As the company entered the 21st century, building on its dominance of enterprise-networking, Cisco was positioned to upgrade its technological capabilities to become a major infrastructureequipment vendor to service providers. We analyze how and why, when the Internet boom turned to bust in 2001, the organizational structure that enabled Cisco to dominate enterprise networking posed constraints related to manufacturing and marketing on the company’s growth in the more sophisticated infrastructure-equipment segment. We then document how from 2002 Cisco turned from innovation to financialization, as it used its ample profits to do stock buybacks to prop up its stock price. Finally, we ponder the larger policy implications of Cisco’s turn from innovation to financialization for the competitive position of the US information-and-communication technology (ICT) industry in the global economy.
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African Open Science Platform Part 1: Landscape Study. Academy of Science of South Africa (ASSAf), 2019. http://dx.doi.org/10.17159/assaf.2019/0047.
Повний текст джерелаАнотація:
This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.