Performance evaluation of Heuristic and Metaheuristic Algorithms for Independent and Static Task Scheduling in Cloud Computing

Cloud computing is the general name of the services that enable the use of information technology resources or services to users over the internet on demand. Independent and static task scheduling is an important problem in cloud computing and deals with the optimal mapping of tasks to resources when task lengths are predetermined and can work independently from each other. In this study, the performances of FCFS, SJF, Min-Min, Max-MM heuristics, and ABC, PSO metaheuristics were measured on this problem. It has been observed that Min-Min, Max-MM and ABC algorithms are more successful than others according to the maximum completion time criterion. Considering the ease of implementation and fast running time, it has been observed that MM-MM and Max-MM heuristics are sufficient in solving this problem, and metaheuristic approaches do not contribute much.