A PSO Algorithm-Based Task Scheduling in Cloud Computing

Abstract

Cloud computing is one of the most acceptable emerging technologies, which involves the allocation and de-allocation of the computing resources using the Internet as the core technology to compute the tasks or jobs submitted by the users. Task scheduling is one of the fundamental issues in cloud computing and lots of efforts have been made to solve this problem. For the success of any cloud-based computing model, efficient task scheduling mechanism is always needed which, in turn, is responsible for the allocation of tasks to the available processing machines in such a manner that no machine is over- or under-utilized while executing them. Scheduling of tasks belongs to the category of NP-Hard problem. Through this paper, we are proposing the particle swarm optimization (PSO)-based task scheduling mechanism for the efficient distribution of the task among the virtual machines (VMs) in order to keep the overall response time minimum. The proposed algorithm is compared using the CloudSim simulator with the existing greedy and genetic algorithm-based task scheduling mechanism and results clearly shows that the PSO-based task scheduling mechanism clearly outperforms the others techniques which are taken into consideration.