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Issue No.01 - Jan. (2014 vol.25)
pp: 234-243
Linghe Kong , Xidian University, China and Shanghai Jiao Tong University, Shanghai
Mingchen Zhao , University of Pennsylvania, Phladelphia and Shanghai Jiao Tong University, Shanghai
Xiao-Yang Liu , Huazhong University of Science and Technology, China and Shanghai Jiaotong University, Shanghai
Jialiang Lu , INSA, Lyon and Shanghai Jiaotong University, Shanghai
Yunhuai Liu , Tsinghua University, Hong Kong University of Science and Technology, Shenzhen Institutes of Advanced Echnology, and Chinese Academy of Sciences
Min-You Wu , Graduate School of Academia Sinica, Beijing, Santa Clara University, Santa Clara, University of New Mexico, Albuquerque and Shanghai Jiaotong University, Shanghai
Wei Shu , University of Illinois, Urbana-Champaign, Yale University, New Haven, State University of New York, Buffalo, University of Central Florida, Orlando, and University of New Mexico, Albuquerque
ABSTRACT
Coverage is a fundamental problem in wireless sensor networks (WSNs). Conventional studies on this topic focus on 2D ideal plane coverage and 3D full space coverage. The 3D surface of a field of interest (FoI) is complex in many real-world applications. However, existing coverage studies do not produce practical results. In this paper, we propose a new coverage model called surface coverage. In surface coverage, the field of interest is a complex surface in 3D space and sensors can be deployed only on the surface. We show that existing 2D plane coverage is merely a special case of surface coverage. Simulations point out that existing sensor deployment schemes for a 2D plane cannot be directly applied to surface coverage cases. Thus, we target two problems assuming cases of surface coverage to be true. One, under stochastic deployment, what is the expected coverage ratio when a number of sensors are adopted? Two, if sensor deployment can be planned, what is the optimal deployment strategy with guaranteed full coverage with the least number of sensors? We show that the latter problem is NP-complete and propose three approximation algorithms. We further prove that these algorithms have a provable approximation ratio. We also conduct extensive simulations to evaluate the performance of the proposed algorithms.
INDEX TERMS
Surface treatment, Sensors, Stochastic processes, Wireless sensor networks, Approximation algorithms, Approximation methods, Volcanoes,optimal coverage strategy, Wireless sensor networks, surface coverage, expected coverage ratio
CITATION
Linghe Kong, Mingchen Zhao, Xiao-Yang Liu, Jialiang Lu, Yunhuai Liu, Min-You Wu, Wei Shu, "Surface Coverage in Sensor Networks", IEEE Transactions on Parallel & Distributed Systems, vol.25, no. 1, pp. 234-243, Jan. 2014, doi:10.1109/TPDS.2013.35
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