RESOURCE SCHEDULING BASED ON LOAD BALANCING WITH FAULT TOLERANCE IN CLOUD COMPUTING

Abstract: Cloud Computing is an emerging technology in today's world. The way tasks are distributed and coordinated in cloud computing is a challenging issue utilize the resource in an optimized way, avoid overload with resource failure. In this paper, we present a novel approach to load balancing through ant colony optimization (ACO) and to control resource failure. The strategies are used forward-backward ant mechanism, max-min rule, and checkpoint-based rollback recovery. To accelerate the searching process, moving probability of two ants. The proposed strategy provides the dynamic load balancing for cloud computing with less searching time whereas it will also have high network performance and fault tolerance related to the task.

Keywords: Load balancing, Cloud computing, Ant colony optimization, Fault Tolerance.