Title: BABC task scheduler: hybridisation of BAT and artificial bee colony for deadline constrained task scheduling

Authors: A.R. Arunarani; D. Manjula

Addresses: Faculty of Computer Science and Engineering, Anna University of India, India ' Department of Computer Science and Engineering, Anna University of India, India

Abstract: In information technology, one of the modern and rising trends is cloud computing, the foremost problems in cloud computing is task scheduling. A good scheduling algorithm has to reduce the execution time and cost together with QoS requirements of the users. In this paper, a task scheduling scheme with the aid of a hybridisation of BAT and artificial bee colony (BABC) on diverse computing systems is proposed. In BABC, each dimension of a solution represents a task and a solution as a whole signifies all tasks priorities. The vital issue is how to allocate users tasks to exploit the income of infrastructure as a service (IaaS) provider while promising quality-of-service (QoS). The generated solution is proficient to quality of service (QoS) and improves IaaS providers' credibility and economic benefit. According to the evolved results, it has been found that our algorithm always outperforms the traditional algorithms.

Keywords: infrastructure as a service; IaaS; quality of service; QoS; artificial bee colony; ABC; bat algorithm; metaheuristics; deadline constraints; task scheduling; cloud computing; optimisation.

DOI: 10.1504/IJBIDM.2016.082216

International Journal of Business Intelligence and Data Mining, 2016 Vol.11 No.4, pp.379 - 399

Received: 09 Sep 2016
Accepted: 10 Oct 2016
Published online: 12 Feb 2017 *

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