DocumentCode :
3055381
Title :
Optimal traffic distribution in minimum energy wireless sensor networks
Author :
Wang, Jing ; Howitt, Ivan
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina Univ., Charlotte, NC
Volume :
6
fYear :
2005
fDate :
2-2 Dec. 2005
Lastpage :
3278
Abstract :
Energy efficient data transmission and traffic control are essential for increasing the lifetime of wireless sensor networks (WSN). In traditional sensor networks, the optimization of the traffic distribution is restricted to a subset of the possible routes. This constraint makes achieving a global energy minimization impossible. In this paper, the stochastic based traffic distribution (SBTD) is formulated in terms of the traffic segmentation with an additional degree of freedom of the routes. It is derived based on the parametric stochastic models underlying the operational characteristics of the WSNs, whereby, the nodes´ unbalanced energy consumption is balanced and the network´s lifetime is prolonged. As illustrated in the paper, a WSN using the proposed optimal traffic distribution performs significantly better in conserving energy and increasing the WSN´s lifetime as compared to the energy balanced data propagation (EBDP) as suggested in C. Efthymiou, et al (2004)
Keywords :
energy conservation; stochastic processes; telecommunication network reliability; telecommunication network routing; telecommunication traffic; wireless sensor networks; data transmission; energy balanced data propagation; global energy minimization; optimal traffic distribution; parametric stochastic models; stochastic based traffic distribution; traffic control; traffic segmentation; wireless sensor networks; Biosensors; Communication system traffic control; Energy consumption; Energy efficiency; Intelligent networks; Power engineering and energy; Stochastic processes; Telecommunication traffic; Traffic control; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Telecommunications Conference, 2005. GLOBECOM '05. IEEE
Conference_Location :
St. Louis, MO
Print_ISBN :
0-7803-9414-3
Type :
conf
DOI :
10.1109/GLOCOM.2005.1578380
Filename :
1578380
Link To Document :
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