A HYBRID G-ACO APPROACH ON LOAD BALANCING IN CLOUD COMPUTING

Abstract

Cloud computing permits facilitating of various administrations on various datacenters where assets are designated to clients on request. It utilizes the concept of virtualization for working online, on the grounds that without virtualization cloud computing is inefficient and not adaptable. Load balancing is a method that distribute the workload among different nodes in the given environment such that it no node in the system is overloaded .The different conventional load balancing techniques not performed well and they doesn't consider SLA quality of service parameters while choosing virtual machine for relocation. Many other issues are likewise associated with migration process like number of migration, utilization of resources, response time and memory. So there is have to grow new approach for load balancing in data centers using VM algorithms that beat the issues in customary methodologies and enhance their execution. So the hybrid approach utilizing different strategies like Ant Colony Optimization (ACO) and Genetic algorithm (GA) is proposed in this paper. This paper defeat the issue of stagnation in ACO-VMM system. The outcomes are mimicked in cloudsim environment.