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Developing energy-efficient protocol for wireless sensor networks

Al-Chelabi, M

Authors

M Al-Chelabi



Contributors

Abstract

Buildings are subjected to natural and man-made hazard such as earthquake, fires, etc. during their long-term use. To examine the effects of these hazards, certain types of
physical values are necessary to be monitored. Recently, a smart sensor based on the Berkeley Mote platform was introduced; the mote has on-board microprocessor and
ready-made wireless communication capabilities.
In wireless sensor networks, individual sensor nodes are inherently unreliable because of their limited energy, which hinders the capacity of the network. This thesis
focuses on the design, the implementation, and the testing of a clustered-based Transmission Power Control protocol at the Medium Access Control and the Network layer in Wireless Sensor Networks (WSN). The network under investigation is an
integration between infrastructure (cluster heads) and an ad hoc (sensor nodes) network.
The main considerations on sensor nodes level are resource constraints namely energy consumption, congestion and synchronisation among clusters, and on system level whether it is a real-time or long-term monitoring system. The deployment of the sensor nodes is considered to be random and non-uniform across a heterogeneous indoor environment. Because high node density is typical in WSN, controlling the size of clusters and managing their duty cycle are crucial to meet the research primary considerations. To do so, new control and routing messages were developed and
implemented in the standard packet in order to sustain code legacy.
The presented results show that the designed protocol satisfies the objectives of extending clusters life-time, optimising channel utilisation of the entire network, and
most importantly shows no performance degradation when the number of nodes in the network increases considerably.

Citation

Al-Chelabi, M. Developing energy-efficient protocol for wireless sensor networks. (Thesis). University of Salford

Thesis Type Thesis
Deposit Date Oct 3, 2012
Award Date Jan 1, 2010