TY - GEN
T1 - Decentralized optimization of wireless sensor network lifetime based on neural network dynamics
AU - Hasegawa, Mikio
AU - Kawamura, Tetsuo
AU - Tran, Ha Nguyen
AU - Miyamoto, Goh
AU - Murata, Yoshitoshi
AU - Harada, Hiroshi
AU - Kato, Shuzo
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - The wireless sensor networks, which collect various data from a physical environment, are usually defined as an ad hoc network consisted of a huge number of tiny wireless sensor nodes whose computing power and battery capacity are limited. Because it is difficult to replace all of batteries on such a huge number of sensor nodes, maximization of the lifetime of the network has been one of the important research issues. To optimize such a network with a huge number of the sensor nodes, autonomous and decentralized computing and reconfiguration schemes can be considered suitable. Therefore, in this paper, we propose a routing reconfiguration method based on an autonomous optimization dynamics of the mutually connected neural network which minimizes its own energy function with autonomous and distributed computing. We show that the proposed method can optimize the routes for maximizing the lifetime of the sensor network, without any centralized computing nodes.
AB - The wireless sensor networks, which collect various data from a physical environment, are usually defined as an ad hoc network consisted of a huge number of tiny wireless sensor nodes whose computing power and battery capacity are limited. Because it is difficult to replace all of batteries on such a huge number of sensor nodes, maximization of the lifetime of the network has been one of the important research issues. To optimize such a network with a huge number of the sensor nodes, autonomous and decentralized computing and reconfiguration schemes can be considered suitable. Therefore, in this paper, we propose a routing reconfiguration method based on an autonomous optimization dynamics of the mutually connected neural network which minimizes its own energy function with autonomous and distributed computing. We show that the proposed method can optimize the routes for maximizing the lifetime of the sensor network, without any centralized computing nodes.
KW - Lifetime
KW - Mutually connected neural networks
KW - Optimization
KW - Routing
KW - Sensor networks
UR - http://www.scopus.com/inward/record.url?scp=69949158974&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=69949158974&partnerID=8YFLogxK
U2 - 10.1109/PIMRC.2008.4699900
DO - 10.1109/PIMRC.2008.4699900
M3 - Conference contribution
AN - SCOPUS:69949158974
SN - 9781424426447
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
BT - 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2008
T2 - 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2008
Y2 - 15 September 2008 through 18 September 2008
ER -