DocumentCode
2116602
Title
Optimal Structure Analysis for Ubiquitous Access of Mobile Collectors in Clustered Sensor Networks
Author
Sun, Bo ; Chen, Canfeng ; Ma, Jian
Author_Institution
Grad. Univ. of Chinese Acad. of Sci., Beijing
fYear
2009
fDate
27-28 Feb. 2009
Firstpage
97
Lastpage
101
Abstract
One important application of wireless sensor networks is data storage for the ubiquitous access of mobile collectors. Events are detected and their readings are disseminated in the sensor network, where sensors store the coded form of received data for the access of mobile collectors. Clustering is an effective method to reduce the data dissemination cost in this application. In clustered networks, data are only disseminated inside cluster, and sensors encode the data of its own cluster. However, the probability of recovering all the original data decreases in clustered networks. This paper first analyzes the optimal network structure to minimize the overall energy consumption of sensor network under the constraint of successful decoding probability. An optimization model is proposed and equal clustered networks are strictly proved to be optimal in our model. We also prove that clustering sharply decreases the successful data decoding probability, and show that increasing the mobile collectorpsilas sample size will significantly improve the decoding efficiency.
Keywords
decoding; mobile radio; probability; wireless sensor networks; clustered sensor networks; data dissemination; data storage; decoding probability; mobile collectors; optimal structure analysis; optimization model; ubiquitous access; wireless sensor networks; Decoding; Energy consumption; Energy storage; Humans; Memory; Mobile communication; Monitoring; Network coding; Temperature sensors; Wireless sensor networks; clustering; data decoding probability; energy consumption; network coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Software and Networks, 2009. ICCSN '09. International Conference on
Conference_Location
Macau
Print_ISBN
978-0-7695-3522-7
Type
conf
DOI
10.1109/ICCSN.2009.68
Filename
5076819
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