Replacing Failed Sensor Nodes by Mobile Robots

Sensor replacement is important for sensor networks to provide continuous sensing services. Existing approaches relocate redundant nodes to fill the holes created by failed sensors and require all or most sensor nodes to have mobility. However, mobility equipment is expensive while technology trends...

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Bibliographic Details
Published in26th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'06) p. 87
Main Authors Yongguo Mei, Changjiu Xian, Das, S., Hu, Y.C., Yung-Hsiang Lu
Format Conference Proceeding
LanguageEnglish
Published IEEE 2006
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ISBN0769525415
9780769525419
ISSN1545-0678
DOI10.1109/ICDCSW.2006.90

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Summary:Sensor replacement is important for sensor networks to provide continuous sensing services. Existing approaches relocate redundant nodes to fill the holes created by failed sensors and require all or most sensor nodes to have mobility. However, mobility equipment is expensive while technology trends are scaling sensors to be smaller and cheaper. In this paper, we propose to use a small number of mobile robots to replace failed sensors in a large-scale static sensor network. We study algorithms for detecting and reporting sensor failures and coordinating the movement of robots that minimize the motion energy of mobile robots and the messaging overhead incurred to the sensor network. A manager receives failure reports and determines which robot to handle a failure. We study three algorithms: a centralized manager algorithm, a fixed distributed manager algorithm, and a dynamic distributed manager algorithm. Our simulations show that: (a) The centralized and the dynamic distributed algorithms have lower motion overhead than the fixed distributed algorithm. (b) The centralized algorithm is less scalable than the two distributed manager algorithms. (c) The two distributed algorithms have higher messaging cost than the centralized algorithm. Hence, the optimal choice of the coordination algorithm depends on the specific scenarios and objectives being optimized.
ISBN:0769525415
9780769525419
ISSN:1545-0678
DOI:10.1109/ICDCSW.2006.90