Liu, Hongbo and Abraham, Ajith and Snášel, Vaclav and McLoone, Sean F. (2012) Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments. Information Sciences, 19. pp. 228-243. ISSN 0020-0255

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Abstract

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications.

Item Type:	Article
Keywords:	Swarm intelligence; Particle swarm; Scheduling problem Work-flow; Security constraints; Distributed data-intensive computing; environments
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering
Item ID:	3869
Depositing User:	Sean McLoone
Date Deposited:	17 Sep 2012 13:31
Journal or Publication Title:	Information Sciences
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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