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Distributed Event Processing For Activity Recognition

Lookup NU author(s): Visalakshmi Suresh, Dr Paul Ezhilchelvan, Professor Paul Watson, Cuong Pham, Dan Jackson, Professor Patrick Olivier

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Abstract

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.


Publication metadata

Author(s): Suresh V, Ezhilchelvan P, Watson P, Pham C, Jackson D, Olivier P

Publication type: Report

Series Title: School of Computing Science Technical Report Series

Year: 2011

Pages: 6

Source Publication Date: June 2011

Report Number: 1258

Institution: School of Computing Science, University of Newcastle upon Tyne

Place Published: Newcastle upon Tyne


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