Intelligent load balancing techniques in software defined networks: A survey

Thabo Semong, Thabiso Maupong, Stephen Anokye, Kefalotse Kehulakae, Setso Dimakatso, Gabanthone Boipelo, Seth Sarefo

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

In the current technology driven era, the use of devices that connect to the internet has increased significantly. Consequently, there has been a significant increase in internet traffic. Some of the challenges that arise from the increased traffic include, but are not limited to, multiple clients on a single server (which can result in denial of service (DoS)), difficulty in network scalability, and poor service availability. One of the solutions proposed in literature, to mitigate these, is the use of multiple servers with a load balancer. Despite their common use, load balancers, have shown to have some disadvantages, like being vendor specific and non-programmable. To address these disadvantages and improve internet traffic, there has been a paradigm shift which resulted in the introduction of software defined networking (SDN). SDN allows for load balancers that are programmable and provides the flexibility for one to design and implement own load balancing strategies. In this survey, we highlight the key elements of SDN and OpenFlow technology and their effect on load balancing. We provide an overview of the various load balancing schemes in SDN. The overview is based on research challenges, existing solutions, and we give possible future research directions. A summary of emulators/mathematical tools commonly used in the design of intelligent load balancing SDN algorithms is provided. Finally, we outline the performance metrics used to evaluate the algorithms.

Original languageEnglish
Article number1091
Pages (from-to)1-24
Number of pages24
JournalElectronics (Switzerland)
Volume9
Issue number7
DOIs
Publication statusPublished - Jul 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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