A Survey of Fault Management in Network Virtualization Environments: Challenges and Solutions

Cherrared, Sihem; Imadali, Sofiane; Fabre, Éric; Gößler, Gregor; Yahia, Imen Grida Ben

doi:10.1109/tnsm.2019.2948420

Cited by 43 publications

(21 citation statements)

References 73 publications

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“…Two studies [15,16] reviewed virtualization solutions specifically developed for IoT networks, allowing users and operators to create environments that match their demands while coexisting with other networks in the same physical space.The article [17] looks at the characteristics of the fourth industrial revolution and considers 5G's potential as a GPT. Other researchers offered a new classification of recent fault management research accomplishments in network virtualization environments, as well as a comparison of their primary contributions and flaws [18].…”

Section: Review and Survey Articlesmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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Due to the rapid development of the fifth-generation (5G) applications, and increased demand for even faster communication networks, we expected to witness the birth of a new 6G technology within the next ten years. Many references suggested that the 6G wireless network standard may arrive around 2030. Therefore, this paper presents a critical analysis of 5G wireless networks’, significant technological limitations and reviews the anticipated challenges of the 6G communication networks. In this work, we have considered the applications of three of the highly demanding domains, namely: energy, Internet-of-Things (IoT) and machine learning. To this end, we present our vision on how the 6G communication networks should look like to support the applications of these domains. This work presents a thorough review of 370 papers on the application of energy, IoT and machine learning in 5G and 6G from three major libraries: Web of Science, ACM Digital Library, and IEEE Explore. The main contribution of this work is to provide a more comprehensive perspective, challenges, requirements, and context for potential work in the 6G communication standard.

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Section: Review and Survey Articlesmentioning

confidence: 99%

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

Mahdi

Ahmad

Qassim³

et al. 2021

Applied Sciences

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“…Extensive literature has been carried out on the various aspects of NFV such as architectural designs [191], [192], resource allocation [193], [194], energy efficiency [195], performance improvement [196] and security [197], [198]. More details can be found in [191], [199], [200].…”

Section: A Network Function Virtualization (Nfv)mentioning

confidence: 99%

“…Hardware failure due to several factors such as component malfunctioning, temporary unavailability and malicious attacks affects the implementation of NFV, hindering the provision of services. Apart from the fault-tolerant virtualization strategies that are based on the diversity approach which maps VNFs onto the various virtual machines (VMs) such that the probability of a disruptive failure is minimized [199], coding approach can also be used to minimize computation latency in NFV.…”

Section: A Network Function Virtualization (Nfv)mentioning

confidence: 99%

A Survey of Coded Distributed Computing

Ng¹,

Lim²,

Luong³

et al. 2020

Preprint

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Distributed computing has become a common approach for large-scale computation of tasks due to benefits such as high reliability, scalability, computation speed, and costeffectiveness. However, distributed computing faces critical issues related to communication load and straggler effects. In particular, computing nodes need to exchange intermediate results with each other in order to calculate the final result, and this significantly increases communication overheads. Furthermore, a distributed computing network may include straggling nodes that run intermittently slower. This results in a longer overall time needed to execute the computation tasks, thereby limiting the performance of distributed computing. To address these issues, coded distributed computing (CDC), i.e., a combination of coding theoretic techniques and distributed computing, has been recently proposed as a promising solution. Coding theoretic techniques have proved effective in WiFi and cellular systems to deal with channel noise. Therefore, CDC may significantly reduce communication load, alleviate the effects of stragglers, provide fault-tolerance, privacy and security. In this survey, we first introduce the fundamentals of CDC, followed by basic CDC schemes. Then, we review and analyze a number of CDC approaches proposed to reduce the communication costs, mitigate the straggler effects, and guarantee privacy and security. Furthermore, we present and discuss applications of CDC in modern computer networks. Finally, we highlight important challenges and promising research directions related to CDC.

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“…The different Machine Learning techniques and their advantages for the usage are presented and future research directions are given. Cherrared et al [25] present the state-of-the-art of fault management techniques in Network Virtualization Environments. The following papers all deal with Software Defined Networks (SDN) [22], [26], [27].…”

Section: Introductionmentioning

confidence: 99%

Fault Prediction for Heterogeneous Networks using Machine Learning : a Survey

Murphy¹,

Lepers²,

Lavignotte³

2022

Preprint

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<div>This manuscript provides a survey of Network Fault Prediction using Machine Learning from the years 1997 to 2021. Operational elements from the industry are shared to provide context. An overview of the different ML techniques that have been applied to Network Fault Prediction (NFP) is given. This is followed by a systematic review of the studies on NFP. Future research perspectives in the field are proposed.</div>

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A Survey of Fault Management in Network Virtualization Environments: Challenges and Solutions

Cited by 43 publications

References 73 publications

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

From 5G to 6G Technology: Meets Energy, Internet-of-Things and Machine Learning: A Survey

A Survey of Coded Distributed Computing

Fault Prediction for Heterogeneous Networks using Machine Learning : a Survey

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