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Location-free node scheduling schemes for energy efficient, fault tolerant and adaptive sensing in wireless sensor networks

Node scheduling is one of the most effective techniques to maximize the lifetime of a wireless sensor network. It is the process of selecting a subset of nodes to monitor the sensor field on behalf of redundant nodes. At every round of the scheduling a small group of nodes are active while the rest of the sensor nodes are in sleep mode. In this thesis, we propose a novel node scheduling solution for wireless sensor networks. The main characteristic of our approach is its independence from location information as well as distance information. Moreover, it does not rely on unrealistic circular radio propagation models. In order to have a comprehensive solution, we have considered different relations between sensing range and transmission range. When these ranges are equal in addition to the case that transmission range is higher than sensing range, we devise a node scheduling scheme based on the concept of Minimum Dominating Set. Two heuristics are presented to determine a collection of minimum dominating sets of the graph of the wireless sensor network. At each round of the scheduling only one set is active. Minimum dominating sets are scheduled to be rotated periodically. Moreover, every set is synchronized prior to the end of its active period in order to minimize the effect of clock drift of sensor nodes. Two components are considered to address node failures during the on-duty period of minimum dominating sets. These are probing environment and adaptive sleeping. The former is responsible for probing the working nodes of the active set to detect any node failure. The latter adjusts the frequency of probing for minimizing the overhead of probing while preserving an adequate level of robustness for discovery of node failure. This framework is based on the PEAS protocol that has been developed by Fan Ye et al. [98, 99]. We propose a different node scheduling scheme with a three-tier architecture for the case that sensing range is higher than transmission range. The coverage tier includes a set of nodes to monitor the region of the interest. We propose a heuristic to determine a collection of d-dominating sets of the graph of the wireless sensor network. At every round of the scheduling one d-dominating set forms the coverage tier. Connectivity tier consists of sensor nodes that relay the data collected at the coverage tier back to the base station. Finally, the coverage management tier is responsible for managing different patterns of coverage such as cyclic or uniform coverage.

Identiferoai:union.ndltd.org:ADTP/194839
Date January 2008
CreatorsPazand, Babak
PublisherUniversity of Western Australia. School of Computer Science and Software Engineering
Source SetsAustraliasian Digital Theses Program
LanguageEnglish
Detected LanguageEnglish
RightsCopyright Babak Pazand, http://www.itpo.uwa.edu.au/UWA-Computer-And-Software-Use-Regulations.html

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