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Multi-Threshold Based Data Gathering Algorithms for Wireless Sensor Networks
Journal Title Journal of Networks
Journal Abbreviation jnw
Publisher Group Academy Publisher
Website http://ojs.academypublisher.com
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Title Multi-Threshold Based Data Gathering Algorithms for Wireless Sensor Networks
Authors Sun, Jun-Zhao
Abstract Sensor networks have recently attracted significant attention for many military and civil applications, such as environment monitoring, target tracking, and surveillance. A high-level abstraction of sensor networks forms the distributed database view, in which query is adopted to retrieve data from the network. Continuous query is an important approach that is commonly used for collecting real-time data. Sensor nodes have limited energy resources and their functionality continues until their energy drains. Therefore, query for sensor networks, and especially continuous query, should be wisely designed to extend the lifetime of sensors. This paper presents a query optimization method for continuous data gathering in sensor networks. The method is based on the flexible setting of thresholds and the analysis on the content to be sent over the network. Thresholds represent the accuracy requirement of the application issuing the queries. Thus at each single sensor node, instead of direct delivery of each result data, data communication is needed only when the current data is out of the range constrained by the thresholds. A series of static and dynamic algorithms are proposed for the flexible setting of threshold values. In particular, the paper studies deeply the situation where phenomena under monitoring appear a periodical feature. An initiative data model is first created, and then at each single sensor node, instead of direct delivery of each result data, data communication is needed only when the current data is out of the range constrained by the periodical data model. The performance of the proposed algorithms shows that the proposed methods can achieve better performance than without performing the optimization.
Publisher ACADEMY PUBLISHER
Date 2009-02-01
Source Journal of Networks Vol 4, No 1 (2009)
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