A new task scheduling approach based on Spacing Multi-Objective Genetic algorithm in cloud

Abstract

The dazzling progress in information and communication technologies, contributed significantly to the emergence of cloud computing paradigm, where it promotes prosperity in all fields of human activity, especially in business. Furthermore, manage the resources and use in ways that sharing with large number of users, consider as one of the challenges facing cloud computing environment today. Because cloud processes a huge tasks, which require the employment of scheduling techniques to handle and monitor the resources in an optimal, flexible and dynamic manner. In this paper, we review a new approach called Spacing-MOGA based on spacing distance to rank no-dominate solutions. It aims mainly to minimize both the makespan and cost of execution tasks on virtual machines (VMs). As well, we study its impact on the availability of resources. Experimental results show that S-MOGA is better than Max-min, PSO and MOGA methods, especially as it minimizes the number of active VMs.