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
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