DocumentCode :
2076245
Title :
An Efficient Event Matching Algorithm for Information Dissemination on Grid
Author :
Hassan, Mohammad Mehedi ; Seok, Bo-Hyun ; Choi, Ki-moon ; Huh, Eui-Nam
Author_Institution :
Dept. of Comput. Eng., Kyung Hee Univ., Yongin
fYear :
2008
fDate :
June 30 2008-July 3 2008
Firstpage :
26
Lastpage :
32
Abstract :
In ubiquitous environment, wireless sensor networks are increasingly being deployed to collect information from real world. For sharing huge amount of sensor data efficiently with diverse users, an information dissemination (INFOD) system is very important. In our previous work, we proposed an INFOD system integrated with sensor network and data grid as a publish/subscribe system for a ubiquitous-healthcare application. To disseminate sensed data to diverse users, a matching algorithm called classed group index matching (CGIM) was proposed in our previous work to match published events with subscriptions efficiently. CGIM used statistical grouping method with equivalent intervals for each group which showed poor performance in case of non-uniform subscription distributions. We need to decide proper number of groups to improve the performance. In this paper, we propose efficiency based dynamic re-grouping (DRG) method for CGIM to improve its performance for our INFOD system. Experimental results clearly demonstrate the performance improvement of CGIM algorithm.
Keywords :
grid computing; indexing; information dissemination; classed group index matching; dynamic regrouping; event matching algorithm; grid; information dissemination; sensor data sharing; Application software; Computer networks; Computer security; Grid computing; IP networks; Pervasive computing; Sensor systems; Service oriented architecture; Subscriptions; Wireless sensor networks; Grid; Information Dissemination; Matching Algorithm; Pub-Sub System; Sensor Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Its Applications, 2008. ICCSA '08. International Conference on
Conference_Location :
Perugia
Print_ISBN :
978-0-7695-3243-1
Type :
conf
DOI :
10.1109/ICCSA.2008.14
Filename :
4561199
Link To Document :
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