MURAL - Maynooth University Research Archive Library



    Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments


    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

    [img] Download (661kB)


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    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:

    Repository Staff Only(login required)

    View Item Item control page

    Downloads

    Downloads per month over past year