Developing energy-efficient protocol for wireless sensor networks
Al-Chelabi, M 2010, Developing energy-efficient protocol for wireless sensor networks , PhD thesis, University of Salford.
Restricted to Repository staff only until 03 October 2014.
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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.
|Item Type:||Thesis (PhD)|
|Schools:||Colleges and Schools > College of Science & Technology|
Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering
|Depositing User:||Institutional Repository|
|Date Deposited:||03 Oct 2012 14:34|
|Last Modified:||17 Feb 2014 11:43|
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