Performance Evaluation of Meta-Heuristic Algorithms for Task Scheduling in Cloud Environment

Abstract

Cloud Computing is one of the important fields in the current time of technological era. Here, the resources are available virtually for users according to pay-per-usage. Many industries are providing cloud services nowadays as pay for usage which reduces the computing cost drastically. The updated software services, hardware services can be provided to the user at a minimum cost. The target of the industries and scientists is to reduce the computing cost by various technologies. Resource management or task scheduling may also play a positive role in this regard. There are various virtual machine management algorithms available that can be tested and enhanced for research and benefit of the society. In this paper, three famous Max-Min, Ant Colony Optimization, and Particle Swarm Optimization algorithms have been used for experiments. After simulation results, it is found that the PSO algorithm is performing well for makes pan and cost factors. Further, a new algorithm can be proposed or a meta-heuristic technique can be enhanced or modified for getting better results.