Indian Journal of Science and Technology

Abstract

Background/Objectives: In this paper, the performance of cloud computing system is greatly influenced by the problem of load balancing. The complexity class of the load balancing problem with respect to the complexity class belongs to the NP-system complete which involves intensely huge search space with huge number of potential solutions and also to find the optimal solution, it takes longer time. Based on these circumstances, there is no methodology to solve the problem. Methods/Statistical Analysis: In the cloud, we can find a near optimal solution, within a brief span of time. In this situation IT practitioners are focusing on heuristic methods. This paper proposes a multi objective load balancing in a cloud computing environment. Findings: This model can be applied to schedule the tasks on to the distinct data center resources. Ant Colony Optimization (ACO) algorithm is considered to know the optimal solution. Application/ Improvements: Experimental results show that proposed model exceeds existing models in terms of reduction in energy consumption, improving pool utilization, minimizing the number of active nodes.

Keywords: Ant Colony Optimization (ACO), Cloud Computing, FCFS Algorithm, Genetic Algorithm