Distributed Event Processing For Activity Recognition

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  2. Visalakshmi Suresh
  3. Dr Paul Ezhilchelvan
  4. Paul Watson
  5. Cuong Pham
  6. Dan Jackson
  7. Professor Patrick Olivier
Author(s)Suresh V, Ezhilchelvan P, Watson P, Pham C, Jackson D, Olivier P
Publication type Report
Series TitleSchool of Computing Science Technical Report Series
Year2011
DateJune 2011
Report Number1258
Pages6
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Stream-processing systems inevitably face unpredictable variations in incoming event loads. One way of handling this without a ecting end-to-end performance metrics, will be to dynamically distribute event-processing on multiple computers and thus avail compute power for optimal performance.More precisely, data streams are processed in part or in parallel on multiple computers connected by a high bandwidth network. The number of computers being used is to be varied dynamically to cope with input load uctuations.This paper uses data from ambient kitchen to make a preliminary assessment of performance advantages by distribution of real-time data stream processing. The motivation is to leverage cloud computing for optimal realtime event processing.
InstitutionSchool of Computing Science, University of Newcastle upon Tyne
Place PublishedNewcastle upon Tyne
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