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Lookup NU author(s): Visalakshmi Suresh, Dr Paul EzhilchelvanORCiD, Professor Paul WatsonORCiD, Cuong Pham, Dan JacksonORCiD, Professor Patrick OlivierORCiD
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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.
Author(s): Suresh V, Ezhilchelvan P, Watson P, Pham C, Jackson D, Olivier P
Publication type: Report
Publication status: Published
Series Title: School of Computing Science Technical Report Series
Year: 2011
Pages: 6
Print publication date: 01/06/2011
Source Publication Date: June 2011
Report Number: 1258
Institution: School of Computing Science, University of Newcastle upon Tyne
Place Published: Newcastle upon Tyne
