Workload models for autonomic database management systems

Pat Martin, Said Elnaffar, Ted Wasserman

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

    17 Citations (Scopus)

    Abstract

    Autonomic computing is a promising approach to the problem of effectively managing large complex software systems such as database management systems (DBMSs). In order to be self-managing, an autonomic DBMS (ADBMS) must understand key aspects of its workload, including composition, frequency patterns, intensity and resource requirements. It must therefore use and maintain different characterizations, or models, of the workload to support its various kinds of decision-making. Our research into various aspects of ADBMSs has led us to develop a number of different workload models. In this paper, we examine the importance of workload models to ADBMSs. We discuss the types of workload models needed by ADBMSs and describe examples from our research. We then outline the requirements for an infrastructure to develop and maintain the workload models needed by an ADBMS.

    Original languageEnglish
    Title of host publication2006 International Conference on Autonomic and Autonomous Systems, ICAS'06
    DOIs
    Publication statusPublished - 2006
    Event2006 International Conference on Autonomic and Autonomous Systems, ICAS'06 - San Jose, CA, United States
    Duration: Jul 20 2006Jul 21 2006

    Publication series

    Name2006 International Conference on Autonomic and Autonomous Systems, ICAS'06

    Other

    Other2006 International Conference on Autonomic and Autonomous Systems, ICAS'06
    Country/TerritoryUnited States
    CitySan Jose, CA
    Period7/20/067/21/06

    ASJC Scopus subject areas

    • Computer Science Applications
    • Software
    • Mathematics(all)

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