DocumentCode :
3226083
Title :
Reliability model for extending cluster lifetime using Backup Cluster Heads in cluster-based Wireless Sensor Networks
Author :
Hashmi, Shafiq U. ; Rahman, Sk Md Mizanur ; Mouftah, Hussein T. ; Georganas, Nicolas D.
Author_Institution :
Sch. of Inf. Technol. & Eng., Univ. of Ottawa, Ottawa, ON, Canada
fYear :
2010
fDate :
11-13 Oct. 2010
Firstpage :
479
Lastpage :
485
Abstract :
In cluster-based two-tier Wireless Sensor Networks (WSNs), the cluster-head nodes (CHs) gather data from sensors and then transmit to the base station. When these cluster head nodes start to die, the coverage of the respective clusters is lost and it leaves the region unmonitored. Even if the CHs are rotated and reassigned after some time, until the next rotation that cluster in question will be out of cluster head, causing a loss of information and loss of coverage. To select a Backup Cluster Head (BCH) is suggested for those CHs which are close to deplete their energy. When the CH dies, BCH takes over the responsibility and continues to work as a new cluster head. In this paper we present an analytical model of cluster reliability in cluster-based WSN using BCH, based on Markov chain model. We use non-homogeneous Markov process, along with Forward Chapman-Kolmogorov equations to illustrate the cluster monitoring period in a finite three state space model. We test the accuracy of the model by applying the probabilities of failure of CH and BCH nodes, for a fixed number of sensor nodes in a cluster. The results show that the presented model is able to match the behaviour of the cluster state transition accurately and validates the simulation results and analysis published in.
Keywords :
Markov processes; telecommunication network reliability; wireless sensor networks; Markov chain model; backup cluster heads; cluster head nodes; cluster lifetime; cluster reliability; cluster state transition; cluster-based wireless sensor networks; forward Chapman-Kolmogorov equations; reliability model; state space model; Artificial neural networks; Equations; Markov processes; Mathematical model; Protocols; Reliability; Wireless sensor networks; Markov model; Wireless Sensor Networks; non-homogeneous; reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless and Mobile Computing, Networking and Communications (WiMob), 2010 IEEE 6th International Conference on
Conference_Location :
Niagara Falls, ON
Print_ISBN :
978-1-4244-7743-2
Electronic_ISBN :
978-1-4244-7741-8
Type :
conf
DOI :
10.1109/WIMOB.2010.5645024
Filename :
5645024
Link To Document :
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