Barrier Coverage Mechanism Using Adaptive Sensing Range for Renewable WSNs

被引:8
作者
Dong, Zaixiu [1 ]
Shang, Cuijuan [2 ]
Chang, Chih-Yung [2 ]
Roy, Diptendu Sinha [3 ]
机构
[1] Chuzhou Univ, Sch Comp & Informat Engn, Chuzhou 239000, Peoples R China
[2] Tamkang Univ, Dept Comp Sci & Informat Engn, New Taipei 25137, Taiwan
[3] Natl Inst Technol Meghalaya, Dept Comp Sci & Engn, Shillong 793003, Meghalaya, India
来源
IEEE ACCESS | 2020年 / 8卷 / 08期
关键词
Solar-powered sensor; probabilistic sensing model; adjustable sensing radius; barrier coverage; wireless sensor networks; WIRELESS; LIFETIME;
D O I
10.1109/ACCESS.2020.2992867
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Barrier coverage aims at constructing defense barriers to detect the intruder crossing the predefined boundary in a given wireless sensor network. In literature, most studies considered the battery-powered sensors and applied the Boolean Sensing Model (BSM). The battery-powered sensors have the constraint of limited lifetime while the BSM will affect the actual surveillance quality evaluation because it cannot reflect the physical features of sensing. This paper applies the Probabilistic Sensing Model (PSM) and proposes an algorithm, called BSAS, which considers the solar-powered sensors with adjustable sensing radius to construct the defense barriers. Two main challenges should be overcome. The first one is the cooperative working between sensors to achieve the highest intruder detection probability for a given boundary curve. The BSAS identifies the bottleneck segment with the minimal surveillance quality and schedules as many as possible sensors to improve the bottleneck segment. In addition, a space-time transformation scheme which further adjusts the sensing radius of some sensors is proposed, aiming at improving the detection probability of the bottleneck segment. Consequently, the minimal surveillance quality of the barrier can be maximized. The second challenge is to maintaining the perpetual lifetime of WSNs. The BSAS takes into account the recharging and discharging ratio and time length of daytime in a day in its energy management which guarantees that the sensor energy can always satisfy the energy consumption for sensor working even in the nighttime. Experimental studies reveal that the proposed algorithm outperforms the existing studies in terms of surveillance quality and stability.
引用
收藏
页码:86065 / 86080
页数:16
相关论文
共 19 条
[1]   Probabilistic Sensing Model for Sensor Placement Optimization Based on Line-of-Sight Coverage [J].
Akbarzadeh, Vahab ;
Gagne, Christian ;
Parizeau, Marc ;
Argany, Meysam ;
Mostafavi, Mir Abolfazl .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2013, 62 (02) :293-303
[2]  
[Anonymous], 2004, ACM Trans. Embed. Comput. Syst., DOI DOI 10.1145/972627.972631
[3]   Energy-efficient coverage problems in wireless ad-hoc sensor networks [J].
Cardei, M ;
Wu, J .
COMPUTER COMMUNICATIONS, 2006, 29 (04) :413-420
[4]   SRA: A Sensing Radius Adaptation Mechanism for Maximizing Network Lifetime in WSNs [J].
Chang, Chao-Tsun ;
Chang, Chih-Yung ;
Zhao, Shenghui ;
Chen, Jian-Cheng ;
Wang, Tzu-Lin .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 65 (12) :9817-9833
[5]   A Reinforcement Learning-Based Sleep Scheduling Algorithm for Desired Area Coverage in Solar-Powered Wireless Sensor Networks [J].
Chen, Hongbin ;
Li, Xueyan ;
Zhao, Feng .
IEEE SENSORS JOURNAL, 2016, 16 (08) :2763-2774
[6]   Maximizing Surveillance Quality of Boundary Curve in Solar-Powered Wireless Sensor Networks [J].
Dong, Zaixiu ;
Chang, Chih-Yung ;
Chen, Guilin ;
Chang, I-Hsiung ;
Xu, Pei .
IEEE ACCESS, 2019, 7 :77771-77785
[7]   Cost Effective Directional Barrier Construction Based on Zooming and United Probabilistic Detection [J].
Fan, Xinggang ;
Hu, Fengdan ;
Liu, Tao ;
Chi, Kaikai ;
Xu, Jinshan .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2020, 19 (07) :1555-1569
[8]   Maximum Lifetime Combined Barrier-Coverage of Weak Static Sensors and Strong Mobile Sensors [J].
Kim, Donghyun ;
Wang, Wei ;
Son, Junggab ;
Wu, Weili ;
Lee, Wonjun ;
Tokuta, Alade O. .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2017, 16 (07) :1956-1966
[9]  
Kumar S., 2005, P ANN INT C MOB COMP, P284
[10]   Multi-Source Energy Harvesting and Storage for Floating Wireless Sensor Network Nodes With Long Range Communication Capability [J].
Lee, Wai-Kong ;
Schubert, Martin J. W. ;
Ooi, Boon-Yaik ;
Ho, Stanley Jian-Qin .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2018, 54 (03) :2606-2615