Probabilistic adaptive load balancing for parallel queries

Daniel M. Yellin, Jorge Buenabad-Chávez, Norman W. Paton

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    In the context of adaptive query processing (AQP), several techniques have been proposed for dynamically adapting/redistributing processor load assignments throughout a computation to take account of varying resource capabilities. The effectiveness of these techniques depends heavily on when and to what they adapt processor load assignments, particularly in the presence of varying load imbalance. This paper presents a probabilistic approach to decide when and to what to adapt processor load assignments. Using a simulation based evaluation, it is compared to two other approaches already reported. These two approaches are simpler in their decision making than the probabilistic approach, but the latter performs better under several scenarios of load imbalance. © 2008 IEEE.
    Original languageEnglish
    Title of host publicationProceedings - International Conference on Data Engineering|Proc Int Conf Data Eng
    PublisherIEEE Computer Society
    Number of pages7
    ISBN (Print)9781424421626
    Publication statusPublished - 2008
    Event2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08 - Cancun
    Duration: 1 Jul 2008 → …


    Conference2008 - IEEE 24th International Conference on Data Engineering Workshop, ICDE'08
    Period1/07/08 → …
    Internet address


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