Distributed event processing for activity recognition

Visalakshmi Suresh, Paul Ezhilchelvan, Paul Watson, Cuong Pham, Dan Jackson, Patrick Olivier

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

4 Citations (Scopus)

Abstract

Stream-processing systems inevitably face unpredictable variations in incoming event loads. One way of handling this without affecting 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 fluctuations. 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.

Original languageEnglish
Title of host publicationDEBS'11 - Proceedings of the 5th ACM International Conference on Distributed Event-Based Systems
PublisherAssociation for Computing Machinery (ACM)
Pages371-372
Number of pages2
ISBN (Print)9781450309059
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event5th ACM International Conference on Distributed Event-Based Systems, DEBS'11 - New York, NY, United States of America
Duration: 11 Jul 201115 Jul 2011

Conference

Conference5th ACM International Conference on Distributed Event-Based Systems, DEBS'11
CountryUnited States of America
CityNew York, NY
Period11/07/1115/07/11

Keywords

  • distributed applications
  • performance attributes
  • real time and embedded systems

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