Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/122851
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Type: Journal article
Title: Optimizing the sensor movement for barrier coverage in a sink-based deployed mobile sensor network
Author: Li, S.
Shen, H.
Huang, Q.
Guo, L.
Citation: IEEE Access, 2019; 7:156301-156314
Publisher: IEEE
Issue Date: 2019
ISSN: 2169-3536
2169-3536
Statement of
Responsibility: 
Shuangjuan Li, Hong Shen, Qiong Huang, Longkun Guo
Abstract: Barrier coverage is an important coverage model for intrusion detection. Clearly energy consumption of sensors is a critical issue to the design of a sensor deployment scheme. In mobile sensor network, it costs the sensors much energy to move. In this paper, we study how to optimize the sensor movement while scheduling the mobile sensors to achieve barrier coverage. Given a line barrier and $n$ sink stations that can supply a required number of mobile sensors, we study how to find the mobile sensors' final positions on the line barrier so that the barrier is covered and the total sensor movement is minimized. We first propose a fast algorithm for determining the nearest sink for the given point on the barrier. We then propose a greedy algorithm and an optimal polynomial-time algorithm for calculating the optimal sensor movement. To obtain an optimal algorithm, we first introduce a notion of the virtual-cluster which represents a subset of sensors covering a specified line segment of the barrier and their sensor movements are minimized. Then we construct a weighted barrier graph with the virtual-clusters modeled as vertexes and the weight of each vertex as the total sensor movements of the virtual-cluster. We also prove that the minimum total sensor movements for achieving barrier coverage is the minimum total weights of the path between the two endpoints of the line barrier in this graph. We also solve this barrier coverage problem for the case when the barrier is a cycle by extending the techniques used for the line barrier. Finally, we demonstrate the effectiveness and efficiency of our algorithms by simulations.
Keywords: Barrier coverage; MinSum; mobile sensors; sink-based deployment
Rights: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/
DOI: 10.1109/ACCESS.2019.2949025
Grant ID: http://purl.org/au-research/grants/arc/DP150104871
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