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Please use this identifier to cite or link to this item: http://hdl.handle.net/10023/1812
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Title: On the selection of connectivity-based metrics for WSNs using a classification of application behaviour
Authors: Boyd, Alan
Balasubramaniam, Dharini
Dearle, Alan
Morrison, Ronald
Keywords: QA76 Computer software
Issue Date: 7-Jun-2010
Citation: Boyd , A , Balasubramaniam , D , Dearle , A & Morrison , R 2010 , ' On the selection of connectivity-based metrics for WSNs using a classification of application behaviour ' . in 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing : SUTC 2010 . IEEE Computer Society , pp. 268-275 , 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing , Newport Beach, California , United States , 7-9 June .
conference
Abstract: This paper addresses a subset of Wireless Sensor Network (WSN) applications in which data is produced by a set of resource-constrained source nodes and forwarded to one or more sink nodes. The performance of such applications is affected by the connectivity of the WSN, since nodes must remain connected in order to transfer data from sources to sinks. Designers use metrics to measure and improve the efficacy of WSN applications. We aim to facilitate the choice of connectivity-based metrics by introducing a classification of WSN applications based on their data collection behaviour and indicating the metrics best suited to the evaluation of particular application classes. We argue that no suitable metric currently exists for a significant class of applications with the following characteristics: 1) application data is periodically routed or disseminated from source nodes to one or more sink nodes, and 2) the application can continue to function with the loss of source nodes although its useful network lifetime diminishes as a result. We present a new metric, known as Connectivity Weighted Transfer, which may be used to evaluate WSN applications with these characteristics.
Version: Preprint
URI: http://hdl.handle.net/10023/1812
DOI: http://dx.doi.org/10.1109/SUTC.2010.44
ISBN: 978-1-4244-7087-7
Type: Conference item
Rights: ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Publisher: IEEE Computer Society
Appears in Collections:University of St Andrews Research
Computer Science Research



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