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ZTE Communications ›› 2017, Vol. 15 ›› Issue (3): 20-36.DOI: 10.3969/j.issn.1673-5188.2017.03.004

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  • 收稿日期:2017-06-08 出版日期:2017-08-25 发布日期:2019-12-24

Evolutionary Algorithms in Software Defined Networks: Techniques, Applications, and Issues

LIAO Lingxia1, Victor C. M. Leung1, LAI Chin-Feng2   

  1. 1. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver BC V6T 1Z4, Canada
    2. Department of Engineering Science, National Cheng Kung University, Tainan, China
  • Received:2017-06-08 Online:2017-08-25 Published:2019-12-24
  • About author:LIAO Lingxia (liaolx@ece.ubc.ca) is currently a Ph.D. candidate of Department of Electrical and Computer Engineering of the University of British Columbia (UBC), Canada. She had a bachelor degree from Tsinghua University, China and a master degree from UBC. She was a science researcher in Computer Science Department of UBC, and the R&D director and the general manager of high performance computing of Inspur Group, China. She had over ten years’ experience working in computer and network industry. Her current research interests are E-hearthcare, cloud computing, software defined networking, network function virtualization, network monitoring and optimization, and next generation network. She has contributed multiple technical papers and book chapters in these areas.|Victor C.M. Leung (vleung@ece.ubc.ca) is a professor of Electrical and Computer Engineering and holder of the TELUS Mobility Research Chair at the University of British Columbia (UBC). He has contributed some 1000 technical papers, 37 book chapters and 12 book titles in the areas of wireless networks and mobile systems. He was a Distinguished Lecturer of the IEEE Communications Society. He is serving/has served on the editorial boards of the IEEE Journal on Selected Areas in Communications, IEEE Access, IEEE Transactions on Wireless Communications, IEEE Transactions on Computers, IEEE Transactions on Vehicular Technology, IEEE Wireless Communications Letters and several other journals, and has contributed to the organizing and technical program committees of numerous conferences. Dr. Leung was a winner of the 2011 UBC Killam Research Prize, the IEEE Vancouver Section Centennial Award, the 2017 Canadian Award for Telecommunications Research. He co-authored a paper that won the 2017 IEEE Communications Society Fred W. Ellersick Prize.|LAI Chin-Feng (cinfon@ieee.org) is an associate professor at Department of Engineering Science, National Cheng Kung University, China and Department of Computer Science and Information Engineering, National Chung Cheng University, China since 2016. He received the Ph.D. degree in Department of Engineering Science from National Cheng Kung University, China in 2008. He received Best Paper Awards from IEEE 17th CCSE, 2014 International Conference on Cloud Computing, IEEE 10th EUC, and IEEE 12th CIT. He has more than 100 paper publications and 4 papers selected to TOP 1% most cited articles by Essential Science Indicators (ESI). He serves as an associate editor-in-chief, editor, or associate editor for many journals and is TPC Co-Chair for many conferences during 2012-2017. His research focuses on Internet of Things, body sensor networks, E-healthcare, mobile cloud computing, cloud-assisted multimedia network, embedded systems, etc. He has been an IEEE senior member since 2014.

Abstract:

A software defined networking (SDN) system has a logically centralized control plane that maintains a global network view and enables network-wide management, optimization, and innovation. Network-wide management and optimization problems are typically very complex with a huge solution space, large number of variables, and multiple objectives. Heuristic algorithms can solve these problems in an acceptable time but are usually limited to some particular problem circumstances. On the other hand, evolutionary algorithms (EAs), which are general stochastic algorithms inspired by the natural biological evolution and/or social behavior of species, can theoretically be used to solve any complex optimization problems including those found in SDNs. This paper reviews four types of EAs that are widely applied in current SDNs: Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Simulated Annealing (SA) by discussing their techniques, summarizing their representative applications, and highlighting their issues and future works. To the best of our knowledge, our work is the first that compares the techniques and categorizes the applications of these four EAs in SDNs.

Key words: SDN, evolutionary algorithms, Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization, Simulated Annealing