BIROn - Birkbeck Institutional Research Online

    Meta-scheduling Issues in Interoperable HPCs, Grids and Clouds

    Bessis, N. and Sotiriadis, Stelios and Xhafa, F. and Pop, F. and Cristea, V. (2012) Meta-scheduling Issues in Interoperable HPCs, Grids and Clouds. International Journal of Web and Grid Services 8 (2), pp. 153-172. ISSN 1741-1106.

    [img]
    Preview
    Text
    ijwgs.pdf - Author's Accepted Manuscript

    Download (1MB) | Preview

    Abstract

    Over the last years, interoperability among resources has been emerged as one of the most challenging research topics. However, the commonality of the complexity of the architectures (e.g., heterogeneity) and the targets that each computational paradigm including HPC, grids and clouds aims to achieve (e.g., flexibility) remain the same. This is to efficiently orchestrate resources in a distributed computing fashion by bridging the gap among local and remote participants. Initially, this is closely related with the scheduling concept which is one of the most important issues for designing a cooperative resource management system, especially in large scale settings such as in grids and clouds. Within this context, meta-scheduling offers additional functionalities in the area of interoperable resource management, this is because of its great agility to handle sudden variations and dynamic situations in user demands. Accordingly, the case of inter-infrastructures, including InterCloud, entitle that the decentralised meta-scheduling scheme overcome issues like consolidated administration management, bottleneck and local information exposition. In this work, we detail the fundamental issues for developing an effective interoperable meta-scheduler for e-infrastructures in general and InterCloud in particular. Finally, we describe a simulation and experimental configuration based on real grid workload traces to demonstrate the interoperable setting as well as provide experimental results as part of a strategic plan for integrating future meta-schedulers.

    Metadata

    Item Type: Article
    School: Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Stelios Sotiriadis
    Date Deposited: 17 Apr 2018 12:43
    Last Modified: 09 Aug 2023 12:43
    URI: https://eprints.bbk.ac.uk/id/eprint/21796

    Statistics

    Activity Overview
    6 month trend
    469Downloads
    6 month trend
    265Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item
    Edit/View Item