Performance Evaluation of various Load Balancing Techniques in Cloud Computing

The survival of cloud computing (CC) depends on a load balancing (LB) algorithm that is more reliable, efficient, and scalable. LB is one of the most difficult aspects of CC since it distributes changing workloads over numerous nodes while guaranteeing that no one node is overburdened. Resource consumption is kept to a minimum with efficient LB, allowing for scalability, avoiding bottlenecks, and overprovisioning, among other benefits. A systematic review of existing LB approaches currently used in CC was conducted in this research. According to the findings, existing strategies are mostly focused on minimising reaction time, completion time, cost, and throughput. Neither technique was able to reveal efficient task scheduling LB in a single or federated cloud system. Existing techniques, on the other hand, do not take into account studies such as energy LB, server consolidation, or VM migration. Future research will concentrate on creating a multi-objective job scheduling system that improves service quality in a homogeneous and federated heterogeneous cloud environment.