DocumentCode :
3357264
Title :
EDA: Event-oriented data aggregation in sensor networks
Author :
Guo, Ying ; Hong, Feng ; Guo, Zhongwen ; Jin, Zongke ; Feng, Yuan
Author_Institution :
Dept. of Comput. Sci. & Eng., Ocean Univ. of China, Qingdao, China
fYear :
2009
fDate :
14-16 Dec. 2009
Firstpage :
25
Lastpage :
32
Abstract :
Data aggregation is a crucial technique for energy constrained sensor networks. Previous researches on data aggregation are featured as query-oriented, which only provide partial information of the event happened in the deployment area at the base station. In this paper, we propose an event-oriented data aggregation approach, called EDA. EDA presents the distributed algorithm by exploiting Cloud Membership model of fuzzy logic to aggregate the information of events in the sensor networks. It also presents a distributed algorithm to collect and aggregate the event information. The base station will restore the whole event information when receiving the aggregated packets of event features. EDA can balance the tradeoff between delay, traffic savings, and precision of the restored events. The performance has been evaluated through both theoretical analysis and simulations. We also confirm the performance with the traces of our offshore sensor network testbed (OceanSense).
Keywords :
fuzzy logic; wireless sensor networks; EDA; aggregated packets; cloud membership model; distributed algorithm; energy constrained sensor networks; event-oriented data aggregation; fuzzy logic; offshore sensor network; traffic savings; wireless sensor network; Aggregates; Base stations; Clouds; Delay; Distributed algorithms; Electronic design automation and methodology; Fuzzy logic; Performance analysis; Telecommunication traffic; Traffic control; cloud membership model; data aggregation; event-oriented; wireless sensor network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Performance Computing and Communications Conference (IPCCC), 2009 IEEE 28th International
Conference_Location :
Scottsdale, AZ
ISSN :
1097-2641
Print_ISBN :
978-1-4244-5737-3
Type :
conf
DOI :
10.1109/PCCC.2009.5403819
Filename :
5403819
Link To Document :
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