DocumentCode :
1987821
Title :
Maximization of Data Gathering in Clustered Wireless Sensor Networks
Author :
Wang, Tianqi ; Heinzelman, Wendi ; Seyedi, Alireza
fYear :
2010
fDate :
6-10 Dec. 2010
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, we investigate the maximization of the amount of gathered data in a clustered wireless sensor network (WSN). The amount of gathered data is maximized by (1) choosing the optimal transmit power, and (2) selecting the optimal cluster head. For problem (1), we find closed-form solutions for the optimal or near optimal transmit power of cluster members (CM). For problem (2), we propose a near optimal cluster head selection (CHS) algorithm. The communication burden and computational complexity of CHS only grow linearly with the size of the cluster. In the proposed algorithms, iterations have been avoided in order to significantly lower the complexity of the algorithms compared with traditional iteration-based numerical optimization algorithms, making these approaches suitable for use in energy-constrained wireless sensor networks. The optimization gain is shown to be significant.
Keywords :
computational complexity; optimisation; wireless sensor networks; clustered wireless sensor networks; computational complexity; data gathering; maximization; numerical optimization algorithms; optimal transmit power; Approximation algorithms; Clustering algorithms; Linear approximation; Neodymium; Optimization; Peer to peer computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Telecommunications Conference (GLOBECOM 2010), 2010 IEEE
Conference_Location :
Miami, FL
ISSN :
1930-529X
Print_ISBN :
978-1-4244-5636-9
Electronic_ISBN :
1930-529X
Type :
conf
DOI :
10.1109/GLOCOM.2010.5683482
Filename :
5683482
Link To Document :
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