An efficient resource utilization based integrated task scheduling algorithm

Cloud computing is the network of distributed remote servers to access the information anytime, anywhere. Thus, it also referred to as ubiquitous computing. Cloud computing offers the high performance environment that has great sharing of resources across the distributed servers. Though there are large numbers of tasks to be allocated to these resources, it becomes very necessary to efficiently assign the tasks to the resources so as to gain the maximum resource utilization. Due to enormous data available, scheduling task appears to be NP hard problem. As it becomes critical to find the exact solutions, various meta-heuristic techniques are used to attain approximate optimal solutions. In this research paper, an optimal task scheduling method is implemented. Tasks are scheduled by using Particle Swarm Optimization (PSO) algorithm by means of max-min algorithm. The main attention is to reduce the makespan and maximize the CPU utilization. From result simulations, it has been observed that makespan value shows makespan improvement by an average of 5.01% over the existing scheduling technique which is integration of Bee colony optimization algorithm and Particle swarm optimization. Similarly, for resource utilization parameter, this technique shows an average improvement by 3.63% over the previous existing method.