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research-article

Energy‐aware dynamic‐link load balancing method for a software‐defined network using a multi‐objective artificial bee colony algorithm and genetic operators

Authors:

Ali Akbar Neghabi,

Nima Jafari Navimipour,

Mehdi Hosseinzadeh,

Ali RezaeeAuthors Info & Claims

IET Communications, Volume 14, Issue 18

Pages 3284 - 3293

https://doi.org/10.1049/iet-com.2019.1300

Published: 13 October 2020 Publication History

Abstract

Information and communication technology (ICT) is one of the sectors that have the highest energy consumption worldwide. It implies that the use of energy in the ICT must be controlled. A software‐defined network (SDN) is a new technology in computer networking. It separates the control and data planes to make networks more programmable and flexible. To obtain maximum scalability and robustness, load balancing is essential. The SDN controller has full knowledge of the network. It can perform load balancing efficiently. Link congestion causes some problems such as long transmission delay and increased queueing time. To overcome this obstacle, the link load balancing strategy is useful. The link load‐balancing problem has the nature of NP‐complete; therefore, it can be solved using a meta‐heuristic approach. In this study, a novel energy‐aware dynamic routing method is proposed to solve the link load‐balancing problem while reducing power consumption using the multi‐objective artificial bee colony algorithm and genetic operators. The simulation results have shown that the proposed scheme has improved packet loss rate, round trip time and jitter metrics compared with the basic ant colony, genetic‐ant colony optimisation, and round‐robin methods. Moreover, it has reduced energy consumption.

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Cited By

Sutar MJadhav H(2023)A modified artificial bee colony algorithm based on a non-dominated sorting genetic approach for combined economic-emission load dispatch problem▪Applied Soft Computing10.1016/j.asoc.2023.110433144:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.asoc.2023.110433

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Information & Contributors

Information

Published In

cover image IET Communications

IET Communications Volume 14, Issue 18

November 2020

216 pages

EISSN:1751-8636

DOI:10.1049/cmu2.v14.18

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© 2021 The Institution of Engineering and Technology.

Publisher

John Wiley & Sons, Inc.

United States

Publication History

Published: 13 October 2020

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Cited By

Sutar MJadhav H(2023)A modified artificial bee colony algorithm based on a non-dominated sorting genetic approach for combined economic-emission load dispatch problem▪Applied Soft Computing10.1016/j.asoc.2023.110433144:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.asoc.2023.110433

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