A comprehensive survey of load balancing techniques in software-defined network. (15th January 2021)

• Record Type: Journal Article
• Authors: Hamdan, Mosab; Hassan, Entisar; Abdelaziz, Ahmed; Elhigazi, Abdallah; Mohammed, Bushra; Khan, Suleman; Vasilakos, Athanasios V.; Marsono, M.N.
• Is Part Of: Journal of network and computer applications. Volume 174(2021)
• Publication Date: 2021-01-15
• Subjects: Load balancing -- Software-defined network -- Multiple controller -- Distributed controller; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2020.102856
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: A software-defined network (SDN) separates the network control plane from the data forwarding plane. SDN has shown significant benefits in many ways compared to conventional non-SDN networks. However, traffic distribution in SDN impacts efficiency and raises many other challenges. For instance, uneven load distribution in the SDN significantly impacts the network performance. Hence, several SDN load balancing (LB) techniques have been introduced to improve the efficiency of SDN. In this article, we provide a thematic taxonomy of LB in SDN, considering several parameters from the past technical studies such as the objectives of LB, data plane LB techniques, control plane LB techniques, other aspects of data plane/control plane LB as well as the performance metrics for LB techniques. Furthermore, useful insights on LB and a comparative analysis of various promising SDN LB techniques are also included in the survey. Finally, existing challenges and future direction on SDN LB techniques are highlighted. Graphical abstract: Image 1 Highlights: A comprehensive literature review of pertinent studies on Load Balancing in Software Defined Networks. Thematic taxonomy for classifying current load balancing techniques in SDN. Lesson learned from in-depth critical review based on proposed taxonomy. Key future direction is discussed based on the SDN requirement.