Blue monkey updated chimp optimization algorithm for enhanced load balancing model

Abstract

Even though, Software Defined Networks (SDN) have exposed greater advantages in a lot of aspects, still the issue related to load balancing (LB) exists like poor performance, efficiency, load imbalance, resource management etc. Diverse methods are performed to resolve this problem; nevertheless, the schemes are found as a challenging one in solving this issue in an optimal manner. Henceforth, this work adopts a new LB strategy with optimization algorithm. The steps followed in this model are (i) Load balancing detection (ii) Switch Migration. Switch migration is done to move the overloaded machines to underloaded ones when the load has been balanced. Here, factors like migration efficiency and migration cost are taken into account while determining the best distribution of work among machines. For this, a new Blue Monkey Updated Chimp Optimization Algorithm (BMU-COA) is introduced that combines the models like blue monkey optimization (BMO) and chimp optimization algorithm (CO).At last, the developed model compared with the certain measures like migration efficiency, migration cost, convergence and fitness. And, the developed model attains higher migration efficiency at 0.186492, less migration cost at 5.362167, and total fitness at0.135873 respectively.