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Data plane failure and its recovery techniques in SDN: A systematic literature review

Software-defined networking (SDN) plays a crucial role in the enterprise and wide-area networking. The increasing demand for strict service-level agreement applications on the Internet requires networks to be scalable and resilient in the face of link and switch failure. However, there is a lack of...

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Main Authors: Khan, Nauman, Bin Salleh, Rosli, Koubaa, Anis, Khan, Zahid, Khan, Muhammad Khurram, Ali, Ihsan
Format: Article
Published: Elsevier 2023
Subjects:
QA75 Electronic computers. Computer science
Library science. Information science
Online Access:http://eprints.um.edu.my/38574/
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spelling my.um.eprints.385742023-11-23T01:19:05Z http://eprints.um.edu.my/38574/ Data plane failure and its recovery techniques in SDN: A systematic literature review Khan, Nauman Bin Salleh, Rosli Koubaa, Anis Khan, Zahid Khan, Muhammad Khurram Ali, Ihsan QA75 Electronic computers. Computer science Library science. Information science Software-defined networking (SDN) plays a crucial role in the enterprise and wide-area networking. The increasing demand for strict service-level agreement applications on the Internet requires networks to be scalable and resilient in the face of link and switch failure. However, there is a lack of systematic reviews on SDN data plane failure recovery techniques. This review article assesses SDN current state-of-the-art link and switches failure recovery solutions. We cover the root causes of failures in the traditional core network and their detection and classify the current failure recovery techniques for SDN into two categories: traditional and artificial intelligence (AI) approaches. AI-based techniques enable efficient failure recovery and enhance the quality of service. We also consider performance measure metrics to evaluate and determine the limitations of existing solutions. This study reviews 188 papers from 2010 to 2021, selecting 70 articles that are highly relevant to our work. All articles are written in English. Our research aims to collect a large amount of evidence that will assist the industry and academic researchers in networking to address current research gaps in failure recovery solutions for the SDN data plane. (c) 2023 Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Elsevier 2023-03 Article PeerReviewed Khan, Nauman and Bin Salleh, Rosli and Koubaa, Anis and Khan, Zahid and Khan, Muhammad Khurram and Ali, Ihsan (2023) Data plane failure and its recovery techniques in SDN: A systematic literature review. Journal of King Saud University - Computer and Information Sciences, 35 (3). pp. 176-201. ISSN 1319-1578, DOI https://doi.org/10.1016/j.jksuci.2023.02.001 <https://doi.org/10.1016/j.jksuci.2023.02.001>. 10.1016/j.jksuci.2023.02.001
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA75 Electronic computers. Computer science
Library science. Information science
spellingShingle QA75 Electronic computers. Computer science
Library science. Information science
Khan, Nauman
Bin Salleh, Rosli
Koubaa, Anis
Khan, Zahid
Khan, Muhammad Khurram
Ali, Ihsan
Data plane failure and its recovery techniques in SDN: A systematic literature review
description Software-defined networking (SDN) plays a crucial role in the enterprise and wide-area networking. The increasing demand for strict service-level agreement applications on the Internet requires networks to be scalable and resilient in the face of link and switch failure. However, there is a lack of systematic reviews on SDN data plane failure recovery techniques. This review article assesses SDN current state-of-the-art link and switches failure recovery solutions. We cover the root causes of failures in the traditional core network and their detection and classify the current failure recovery techniques for SDN into two categories: traditional and artificial intelligence (AI) approaches. AI-based techniques enable efficient failure recovery and enhance the quality of service. We also consider performance measure metrics to evaluate and determine the limitations of existing solutions. This study reviews 188 papers from 2010 to 2021, selecting 70 articles that are highly relevant to our work. All articles are written in English. Our research aims to collect a large amount of evidence that will assist the industry and academic researchers in networking to address current research gaps in failure recovery solutions for the SDN data plane. (c) 2023 Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
format Article
author Khan, Nauman
Bin Salleh, Rosli
Koubaa, Anis
Khan, Zahid
Khan, Muhammad Khurram
Ali, Ihsan
author_facet Khan, Nauman
Bin Salleh, Rosli
Koubaa, Anis
Khan, Zahid
Khan, Muhammad Khurram
Ali, Ihsan
author_sort Khan, Nauman
title Data plane failure and its recovery techniques in SDN: A systematic literature review
title_short Data plane failure and its recovery techniques in SDN: A systematic literature review
title_full Data plane failure and its recovery techniques in SDN: A systematic literature review
title_fullStr Data plane failure and its recovery techniques in SDN: A systematic literature review
title_full_unstemmed Data plane failure and its recovery techniques in SDN: A systematic literature review
title_sort data plane failure and its recovery techniques in sdn: a systematic literature review
publisher Elsevier
publishDate 2023
url http://eprints.um.edu.my/38574/
_version_ 1783876668615557120
score 13.226474

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