Load Balancing Approach in Cloud Computing using Improvised Genetic Algorithm: A Soft Computing Approach

The concept of Cloud computing has significantly changed the field of parallel and distributed computing systems. The major issues to the cloud are resource discovery, fault tolerance, load balancing, safety measure, task scheduling, dependability, data backup, and data portability. Load balancing is one of the essential responsibilities of the cloud computing. In current situation, the load balancing algorithms built should be very efficient in allocating the request. It also ensures the usage of the resources in an intelligent way so that underutilization or overutilization of the resources does not occur in the cloud environment. In this paper, a soft computing based load balancing approach has been proposed called Improvised Genetic Algorithm (IGA), for allocation of incoming jobs to the servers or virtual machines (VMs). The proposed algorithm considers the cost value as a fitness function, of an individual node while performing load balancing. The proposed strategy has been simulated using MATLAB toolkit.