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Performance, Computing, and Communications Conference, 2002. 21st IEEE International (2006)
Phoenix, AZ, USA
Apr. 10, 2006 to Apr. 12, 2006
ISBN: 1-4244-0198-4
pp: 52
J. Chen , Dependable Comput.&Networking Lab., Iowa State Univ., Ames, IA, USA
S. Kher , Dependable Comput.&Networking Lab., Iowa State Univ., Ames, IA, USA
A.K. Somani , Dependable Comput.&Networking Lab., Iowa State Univ., Ames, IA, USA
ABSTRACT
Wireless sensor networks consist of a group of nodes, each equipped with sensing, actuating, computation, communication, and storage resources. These sensor nodes are powered by batteries, which are considered as limited resources. Many applications of sensor networks, such as surveillance systems in both civil and military area, habitual monitoring etc., won't allow the replacement of battery supplies. Therefore, to reduce the energy consumption is the key to prolong the lifetime of sensor networks. In this paper, we present two energy efficient data gathering models to achieve longer lifetime in a structured multiclustered topology. The local homogeneous sensor nodes are grouped together to form clusters and a special processing and relaying node is designated to be responsible for communication among local groups. Such models are developed for power transmission line monitoring systems. The goal is to achieve uninterrupted monitoring over a long time using power constrained sensor nodes because the replacement of battery is a major issue in such applications. We use Markov chain process to analyse the proposed two models and comparison shows that the two level communication model consumes less power and is more suitable than single level communication model on the power transmission line monitoring systems.
INDEX TERMS
Markov chain process, energy efficient data gathering model, wireless sensor network, energy consumption, multicluster topology, power transmission line, monitoring system
CITATION
J. Chen, S. Kher, A.K. Somani, "Energy efficient model for data gathering in structured multiclustered wireless sensor network", Performance, Computing, and Communications Conference, 2002. 21st IEEE International, vol. 00, no. , pp. 52, 2006, doi:10.1109/.2006.1629430
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