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New approach to dynamic load balancing in software-defined network-based data centers

  • Received : 2022.02.28
  • Accepted : 2022.09.21
  • Published : 2023.06.20

Abstract

Critical issues such as connection congestion, long transmission delay, and packet loss become even worse during epidemic, disaster, and so on. In this study, a link load balancing method is proposed to address these issues on the data plane, a plane of the software-defined network (SDN) architecture. These problems are NP-complete, so a meta-heuristic approach, discrete particle swarm optimization, is used with a novel hybrid cost function. The superiority of the proposed method over existing methods in the literature is that it provides link and switch load balancing simultaneously. The goal is to choose a path that minimizes the connection load between the source and destination in multipath SDNs. Furthermore, the proposed work is dynamic, so selected paths are regularly updated. Simulation results prove that with the proposed method, streams reach the target with minimum time, no loss, low power consumption, and low memory usage.

Keywords

Acknowledgement

This work was supported by the Office of Scientific Research Projects of Karadeniz Technical University (Project Number FAY-2021-9701).

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