An efficient meta-heuristic algorithm for grid computing

Zahra Pooranian, Mohammad Shojafar (), Jemal H. Abawajy and Ajith Abraham
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Zahra Pooranian: Dezful Islamic Azad University
Mohammad Shojafar: Sapienza University of Rome
Jemal H. Abawajy: Deakin University
Ajith Abraham: Scientific Network for Innovation and Research Excellence

Journal of Combinatorial Optimization, 2015, vol. 30, issue 3, No 2, 413-434

Abstract: Abstract A grid computing system consists of a group of programs and resources that are spread across machines in the grid. A grid system has a dynamic environment and decentralized distributed resources, so it is important to provide efficient scheduling for applications. Task scheduling is an NP-hard problem and deterministic algorithms are inadequate and heuristic algorithms such as particle swarm optimization (PSO) are needed to solve the problem. PSO is a simple parallel algorithm that can be applied in different ways to resolve optimization problems. PSO searches the problem space globally and needs to be combined with other methods to search locally as well. In this paper, we propose a hybrid-scheduling algorithm to solve the independent task-scheduling problem in grid computing. We have combined PSO with the gravitational emulation local search (GELS) algorithm to form a new method, PSO–GELS. Our experimental results demonstrate the effectiveness of PSO–GELS compared to other algorithms.

Keywords: Grid computing; PSO algorithm; GELS; Scheduling; Independent tasks (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10878-013-9644-6

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