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Sensors 2016, 16(2), 261; doi:10.3390/s16020261

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

1
School of Engineering, Sun Yat-sen University, Guangzhou 510006, China
2
Lawrence Berkeley National Laboratory, University of California, Oakland, CA 94612, USA
3
Department of Mathematics and Computer Science, Valdosta State University, Dartmouth, MA 02747, USA
4
Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Neal N. Xiong and Xuefeng Liang
Received: 22 December 2015 / Revised: 4 February 2016 / Accepted: 12 February 2016 / Published: 19 February 2016
(This article belongs to the Special Issue Mobile Sensor Computing: Theory and Applications)
View Full-Text   |   Download PDF [2189 KB, uploaded 19 February 2016]   |  

Abstract

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain. View Full-Text
Keywords: mobile environments; mobile sensing schemes; collaborative weighted clustering algorithm; weighted clustering algorithm; oil leakage monitoring mobile environments; mobile sensing schemes; collaborative weighted clustering algorithm; weighted clustering algorithm; oil leakage monitoring
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Tang, C.; Shokla, S.K.; Modhawar, G.; Wang, Q. An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks. Sensors 2016, 16, 261.

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