Title: Hybrid algorithm based on genetic algorithm and PSO for task scheduling in cloud computing environment

Authors: A. Kousalya; R. Radhakrishnan

Addresses: Computer Science and Engineering, United Institute of Technology, Tamil Nadu, India ' Computer Science and Engineering, Vidhya Mandhir Institute of Technology, Tamil Nadu, India

Abstract: The cloud computing enable the user to run their applications in remote data centres. Parallel processing solves the complexity of the application and it focus on improving responsiveness and utilisation. However, most existing task-scheduling methods do not considers the bandwidth requirements rather they consider task resource requirements for CPU and memory. In this paper, a novel task allocation model is proposed for the divisible task-scheduling. Foreground and background are the two partition of virtual machine based on the quantity of node. In order to achieve the optimised task allocation an optimisation algorithm (improved genetic algorithm) is implemented along with the foreground and background process. The optimised allocation scheme that determines proper number of tasks assigned to each virtual resource node is obtained.

Keywords: cloud computing; parallel processing; genetic algorithm.

DOI: 10.1504/IJNVO.2017.085524

International Journal of Networking and Virtual Organisations, 2017 Vol.17 No.2/3, pp.149 - 157

Received: 02 Apr 2016
Accepted: 16 May 2016

Published online: 30 Jul 2017 *

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