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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 17

Communication Papers of the 2018 Federated Conference on Computer Science and Information Systems

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

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DOI: http://dx.doi.org/10.15439/2018F180

Citation: Communication Papers of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 17, pages 189195 ()

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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 resource allocation and use in ways that sharing with large number of users, consider as one of the challenges facing the 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 Maxmin, PSO and MOGA methods, especially as it minimizes the number of active VMs.


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