The Deterministic Sensor Deployment Problem for Barrier Coverage in WSNs With Irregular Shape Areas

被引:12
作者
Cheng, Chien-Fu [1 ]
Hsu, Chu-Chiao [2 ]
机构
[1] Natl Taiwan Ocean Univ, Dept Comp Sci & Engn, Keelung 202301, Taiwan
[2] Hon Lin Technol Co Ltd, Foxconn Technol Grp, Taipei 11492, Taiwan
关键词
Wireless sensor networks; barrier coverage problem; deterministic deployment; irregular shape areas; MONITORING-SYSTEM; NETWORKS; INTERNET;
D O I
10.1109/JSEN.2021.3137626
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Most extant studies of barrier coverage in wireless sensor networks (WSNs) have assumed that the region of interest (RoI) is in a rectangular shape and sensors are randomly deployed. They construct a barriermainly by selecting appropriate sensors from randomly deployed sensors. Although these barrier construction algorithms for randomly deployed sensors in rectangular shape areas can also work for irregular shape areas, they will inevitably use a large number of sensors. In real-world scenarios, most RoIs are in an irregular shape. For example, the geographical contour of a country is irregular. To reduce the number of deployed sensors, we propose a new deterministic sensor deployment algorithm for the barrier coverage problem in WSNs with irregular shape areas. The irregular shape area was limited within an area of a L x W virtual rectangle, where L and W are constants. We focus on the problem of minimizing the number of sensorsrequiredto forma barrier. Comparedto randomdeployment of sensors, using deterministicdeployment to deploy sensors can reduce the hardware cost of sensors drastically. The proposed algorithm is based on the concept of convex hull and turning point selection. To the best of our knowledge, this paper is the first work that utilizes the inflection points of the entry side of the RoI to address the problem. Compared to other algorithms, the experimental results confirm that the proposed algorithm can effectively reduce the number of sensors required to construct a barrier in WSNs with irregular shape areas.
引用
收藏
页码:2899 / 2911
页数:13
相关论文
共 41 条
[31]   Solving the minimum convex partition of point sets with integer programming [J].
Sapucaia, Allan ;
Rezende, Pedro J. de ;
Souza, Cid C. de .
COMPUTATIONAL GEOMETRY-THEORY AND APPLICATIONS, 2021, 99
[32]   Optimal Deployment for Target-Barrier Coverage Problems in Wireless Sensor Networks [J].
Si, Pengju ;
Wang, Shuaishuai ;
Shu, Lei ;
Ning, Rui ;
Fu, Zhumu .
IEEE SYSTEMS JOURNAL, 2021, 15 (02) :2241-2244
[33]  
Srinivas M, 2021, 2021 SIXTH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET), P315, DOI [10.1109/WiSPNET51692.2021.9419463, 10.1109/WISPNET51692.2021.9419463]
[34]   A joint global and local path planning optimization for UAV task scheduling towards crowd air monitoring [J].
Tang, Yuan ;
Miao, Yiming ;
Barnawi, Ahmed ;
Alzahrani, Bander ;
Alotaibi, Reem ;
Hwang, Kai .
COMPUTER NETWORKS, 2021, 193
[35]   Energy-Efficient Military Surveillance: Coverage Meets Connectivity [J].
Thomas, Diya ;
Shankaran, Rajan ;
Orgun, Mehmet ;
Hitchens, Michael ;
Ni, Wei .
IEEE SENSORS JOURNAL, 2019, 19 (10) :3902-3911
[36]   TDMA Versus CSMA/CA for Wireless Multihop Communications: A Stochastic Worst-Case Delay Analysis [J].
Wang, Qi ;
Jaffres-Runser, Katia ;
Xu, Yongjun ;
Scharbarg, Jean-Luc ;
An, Zhulin ;
Fraboul, Christian .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2017, 13 (02) :877-887
[37]   Cost-effective barrier coverage formation in heterogeneous wireless sensor networks [J].
Wang, Zhibo ;
Cao, Qing ;
Qi, Hairong ;
Chen, Honglong ;
Wang, Qian .
AD HOC NETWORKS, 2017, 64 :65-79
[38]  
Zhang X., 2016, P IEEE ICC, P1
[39]   Fast Deployment of UAV Networks for Optimal Wireless Coverage [J].
Zhang, Xiao ;
Duan, Lingjie .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2019, 18 (03) :588-601
[40]   Target Coverage-Oriented Deployment of Rechargeable Directional Sensor Networks With a Mobile Charger [J].
Zhu, Xiaojian ;
Li, Jun ;
Zhou, MengChu .
IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (03) :5196-5208