MODIFIED META-HEURISTIC OPTIMIZED LOAD-BALANCING ALGORITHM FOR CLOUD COMPUTING INFRASTRUCTURE

Abstract

In cloud computing, balancing the load among the virtual machines is the key to increase the efficiency of the cloud infrastructure. The load balancing can be achieved using proper task scheduling and virtual machine mapping algorithm. As task scheduling is the non-deterministic polynomial-time hard(NP- hard) problem. Which cannot be achieved using polynomial time algorithm, hence meta-heuristic algorithm is required to solve task scheduling problem. In this paper a meta-heuristic Firefly swarm optimization algorithm is used to give the solution for task schedule in problem in cloud computing. The proposed modified Firefly swarm optimization algorithm can minimize the total execution time of the tasks and keeping the completion time as low within the deadline. The proposed algorithm is compared in terms of total execution time and completion time of the task matrices with some existing research work which used the meta-heuristic approach such as Particle Swarm optimization(PSO), Dragon fly Optimization(DFO) and Bacteria Foraging algorithm(BFA).