Toggle Main Menu Toggle Search

Open Access padlockePrints

The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

Distributed Event Processing For Activity Recognition

Lookup NU author(s): Visalakshmi Suresh, Dr Paul EzhilchelvanORCiD, Professor Paul WatsonORCiD, Cuong Pham, Dan JacksonORCiD, Professor Patrick OlivierORCiD

Downloads

Full text is not currently available for this publication.

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

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

Share