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dc.contributor.authorAlrahmani, Zain
dc.date.accessioned2017-12-18T17:20:56Z
dc.date.available2017-12-18T17:20:56Z
dc.identifier.urihttp://hdl.handle.net/10222/73545
dc.description.abstractBecause stream processing applications operate under strict time constraints, most previous research focuses on enhancing real-time response by decreasing a single cost function. Although such research generates an optimal or near-optimal query execution plan under the selected cost function, either in terms of memory or CPU resources, the generated plan may not actually qualify for real execution; that is, although it is optimal in minimizing the chosen memory (CPU) cost function, it may exceed the available capacity of the CPU (memory) resource. A plan is not qualified if it is optimal or near-optimal in one resource usage, whereas it is out of bound in the other. These kinds of plans are not viable in stream processing applications because one of the resource usages, either CPU or memory, will hinder the system in processing queries. This thesis proposes a technique that generates qualified global plans for multiple queries under constraints for both CPU and memory resources by scheduling MJoin and BJtree operators while sharing common operations and their results among queries.en_US
dc.language.isoen_USen_US
dc.subjectData streamen_US
dc.subjectQuery Optimizationen_US
dc.titleGENERATING QUALIFIED PLANS FOR MULTIPLE QUERIES IN DATA STREAM SYSTEMSen_US
dc.date.defence2015-04-13
dc.contributor.departmentFaculty of Computer Scienceen_US
dc.contributor.degreeMaster of Computer Scienceen_US
dc.contributor.external-examiner-en_US
dc.contributor.graduate-coordinatorDr. Norbert Zehen_US
dc.contributor.thesis-readerDr. V. Keseljen_US
dc.contributor.thesis-readerDr. M. McAllisteren_US
dc.contributor.thesis-supervisorDr. Peter Bodoriken_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.copyright-releaseNot Applicableen_US
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