Open AccessEnergy‐aware dynamic‐link load balancing method for a software‐defined network using a multi‐objective artificial bee colony algorithm and genetic operators
Author(s) -
Neghabi Ali Akbar,
Navimipour Nima Jafari,
Hosseinzadeh Mehdi,
Rezaee Ali
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.1300
Subject(s) - computer science , load balancing (electrical power) , energy consumption , ant colony optimization algorithms , software defined networking , distributed computing , scalability , real time computing , algorithm , ecology , geometry , mathematics , database , biology , grid
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.