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Modeling user submission strategies on production grids

Published: 11 June 2009 Publication History

Abstract

Production-grid users experience many system faults as well as high and variable latencies due to the scale, complexity and sharing of such infrastructures. To improve performance, they adopt different submission strategies, that are potentially aggressive for the infrastructure.
This work studies the impact of three different strategies. It is based on a probabilistic modeling of these strategies which are evaluated according to their performance, measured as the reduction of the latency expectation, and the infrastructure overhead, measured as the additional number of submitted jobs. A strategy cost criterion is then derived.
Experiments are performed using real workload traces collected from the EGEE production infrastructure. Under these conditions, a good balance between high performance and low overhead can be found.

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    cover image ACM Conferences
    HPDC '09: Proceedings of the 18th ACM international symposium on High performance distributed computing
    June 2009
    237 pages
    ISBN:9781605585871
    DOI:10.1145/1551609
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 11 June 2009

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    Author Tags

    1. grid computing
    2. modelisation
    3. submission strategy

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    • (2016)GinFlow: A Decentralised Adaptive Workflow Execution Manager2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS.2016.63(923-932)Online publication date: May-2016
    • (2014)Controlling the deployment of virtual machines on clusters and clouds for scientific computing in CBRAINProceedings of the 14th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing10.1109/CCGrid.2014.42(384-393)Online publication date: 26-May-2014
    • (2012)Scalable and Resilient Workflow Executions on Production Distributed Computing InfrastructuresProceedings of the 2012 11th International Symposium on Parallel and Distributed Computing10.1109/ISPDC.2012.24(119-126)Online publication date: 25-Jun-2012
    • (2011)Practical Considerations in Cloud Utilization for the Science Gateway nanoHUB.org2011 Fourth IEEE International Conference on Utility and Cloud Computing10.1109/UCC.2011.46(287-292)Online publication date: Dec-2011
    • (2011)On-demand service hosting on production grid infrastructuresThe Journal of Supercomputing10.1007/s11227-011-0666-566:3(1178-1193)Online publication date: 12-Aug-2011
    • (2010)TeraGrid resource selection toolsProceedings of the 2010 TeraGrid Conference10.1145/1838574.1838594(1-6)Online publication date: 2-Aug-2010
    • (2010)Issues and scenarios for self-managing grid middlewareProceedings of the 2nd workshop on Grids meets autonomic computing10.1145/1809029.1809033(1-10)Online publication date: 7-Jun-2010
    • (2010)Two experiments with application-level quality of service on the EGEE gridProceedings of the 2nd workshop on Grids meets autonomic computing10.1145/1809029.1809031(11-20)Online publication date: 7-Jun-2010
    • (2010)Efficient Resubmission Strategies to Design Robust Grid Production EnvironmentsProceedings of the 2010 IEEE Sixth International Conference on e-Science10.1109/eScience.2010.11(198-205)Online publication date: 7-Dec-2010
    • (2010)Cyberaide onServeProceedings of the 2010 39th International Conference on Parallel Processing10.1109/ICPP.2010.47(395-403)Online publication date: 13-Sep-2010
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