Grey Wolf Aware Energy-saving and Load Balancing in Software Defined Networks Considering Real Time Traffic

Abstract

The energy depletion in Software Defined Network (SDN) is a primary issue for the operators and regulators of the network because of the ubiquitous implementation of SDN to satisfy the demands of bandwidth-consuming applications. While conventional optimization of edge weights technique is used in various load balancing mechanisms in IGP networks. In this paper, we present a new edge weight optimization algorithm known as Grey Wolf Aware Load balancing and Energy sav-ing(GLE) which simultaneously optimizes energy consumption and load balance in SDN networks. This technique can be applied along with the current mechanisms which use the link active/inactive concept to achieve a significant improvement in energy efficiency. The proposed method in this paper is a new aspect to save energy in SDN networks without compromising conventional traffic-engineering realizations in the environment of plain IP routing. To evaluate the energy-saving by the proposed mechanism without loss of generality, we tested it on various currently proposed methods who have used the technique of link sleeping as described in the related works. The evaluation is tested on the GEANT network topology. GLE shows a noteworthy improvement in the energy-saving as compared to the recently proposed algorithms while achieving significant performance in load balance.