Statistical Analysis of Wireless Sensor Network Monitoring Quality

Abstract

Abstract: As a new network technology, wireless sensor network is a hot research field at home and abroad. It is a new network technology, which can collect the data information distributed on the network in real time, and transmit the information to the gateway node, and finally complete the complex network monitoring and tracking work. In order to solve the challenges faced by wireless sensor networks, for the problem of target coverage in wireless sensor networks, considering the exponential distribution of unknown random event parameters, the monitoring quality of random events is statistically analyzed, and the coverage problem is optimized under the background of wireless sensor networks. Firstly, the background and current situation of wireless sensor network are introduced. The purpose of this paper is to analyze the monitoring quality of wireless sensor network. Secondly, the coverage of wireless sensor network is optimized, the corresponding network model is established, and the optimized simulated annealing algorithm is designed. Combined with statistical knowledge analysis, the monitoring quality is studied by parameter estimation. Finally, the rationality and effectiveness of the method proposed in this paper are verified by the simulation experiment, and the purpose of prolonging the network lifetime is finally achieved.

Key words: wireless sensor network, monitoring quality, parameter estimation, simulated annealing algorithm

BAI Xue, CHENG Zong-mao. Statistical Analysis of Wireless Sensor Network Monitoring Quality[J]. Computer and Modernization, 2021, 0(08): 1-5.

References ［21］

［1］	齐世霞. 无线传感器网络数据安全融合技术的优化［J］. 电子技术与软件工程, 2019(18)：202-203.
［2］	张海辉. 无线传感器网络在环境监测中的应用探析［J］. 农家参谋, 2019(19):175.
［3］	李益鸣. 无线传感器网络在煤矿安全监测中的应用［J］. 工程技术研究, 2019,4(16):140-141.
［4］	于文杰. 基于人工蜂群算法的无线传感器网络部署问题研究［D］. 成都:电子科技大学, 2018.
［5］	PHAM C. Low cost wireless image sensor networks for visual surveillance and intrusion detection applications［C］// 2015 IEEE 12th International Conference on Networking, Sensing and Control. 2015:376-381.
［6］	LI H B, MIAO D, CHEN J M, et al. Networked ultrasonic sensors for target tracking: An experimental study［C］// Proceedings of the 28th IEEE Conference on Global Telecommunications. 2009:3581-3586.
［7］	MAHERIN I, LIANG Q L. Multistep information fusion for target detection using UWB radar sensor network［J］. IEEE Sensors Journal, 2015,15(10):5927-5937.
［8］	WANG X, WANG S, BI D W. Distributed visual-target-surveillance system in wireless sensor networks［J］. IEEE Transactions on Systems, Man, and Cybernetics, Part B(Cybernetics), 2009,39(5):1134-1146.
［9］	HATANAKA T, WASA Y, FUJITA M. Game theoretic cooperative control of PTZ visual sensor networks for environmental change monitoring［C］// The 52nd IEEE Conference on Decision and Control. 2013:7634-7640.
［10］	AZNOLI F, NAVIMIPOUR N J. Deployment strategies in the wireless sensor networks: Systematic literature review, classifification, and current trends［J］. Wireless Personal Communications, 2017,95(2):819-846.
［11］	KAMAL A T, BAPPY J H, FARRELL J A, et al. Distributed multi-target tracking and data association in vision networks［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016,38(7):1397-1410.
［12］	HE S B, CHEN J N, YAU D K Y, et al. Energy-efficient capture of stochastic events under periodic network coverage and coordinated sleep［J］. IEEE Transactions on Parallel and Distributed Systems, 2012,23(6):1090-1102.
［13］	ZHAO Q, GURUSAMY M. Lifetime maximization for connected target coverage in wireless sensor network［J］. IEEE/ACM Transactions on Networking, 2008,16(6):1378-1391.
［14］	WANG D X, WANG H B, BAN X J, et al. An adaptive, discrete space oriented wolf pack optimization algorithm for a movable wireless sensor network［J］. Sensors, 2019,19(19):4320.
［15］	SRINIVAS J, MISHRA D, MUKHOPADHYAY S. A mutual authentication framework for wireless medical sensor networks［J］. Journal of Medical Systems, 2017,41(5):80.
［16］	王振. 无线自组织网络自适应算法研究［D］. 北京:北京邮电大学, 2019.
［17］	TSENG H W, WANG Y B, YANG Y. An adaptive channel hopping and dynamic superframe selection scheme with QoS considerations for emergency traffic transmission in IEEE 802.15.6-based wireless body area networks［J］. IEEE Sensors Journal, 2020,20(7):3914-3929.
［18］	PHAM C. Low cost wireless image sensor networks for visual surveillance and intrusion detection applications［C］// 2015 IEEE 12th International Conference on Networking, Sensing and Control. 2015:376-381.
［19］	MAHERIN I, LIANG Q L. Multistep information fusion for target detection using UWB radar sensor network［J］. IEEE Sensors Journal, 2015,15(10):5827-5937.
［20］	DU Z Q, CUI S G. Innovative application for the wind farm control system with multi communication protocol converter［J］. Journal of Intelligent & Fuzzy Systems, 2020,38(1):327-335.
［21］	VATAMBETI R, SUPRIYA K S, SANSHI S. Detecting black hole and gray hole attack in manet using gray wolf optimization［J］. International Journal of Communication Systems, 2020,33(18).

[1]	RAN Hao-jie, WANG Hong-zhi. Distribution Center Site Selection of Fresh Agricultural Products Based on Improved Simulated Annealing Algorithm [J]. Computer and Modernization, 2022, 0(10): 36-40.
[2]	JI Ping, GUO Ying. Underwater Localization Algorithm of Range Correction Based on Long Short-Term Memory [J]. Computer and Modernization, 2022, 0(02): 52-57.
[3]	WANG Hong. Kriging Parameter Estimation Algorithm Based on Combinatorial Optimization [J]. Computer and Modernization, 2021, 0(09): 51-56.
[4]	ZHAO Ji-ye. Routing Protocol of Cluster Tree Wireless Sensor Network Based on Cloud Security Model [J]. Computer and Modernization, 2021, 0(08): 6-10.
[5]	ZHANG Yan-hu, YAN Li-juan, KONG Shu-mei. A Routing Algorithm for Wireless Sensor Networks in Concave Mountain Terrain [J]. Computer and Modernization, 2021, 0(06): 86-90.
[6]	MA Yuan , DU Xiu-juan . Optimization and Analysis of Underwater LEER Protocol Based on NS3 [J]. Computer and Modernization, 2021, 0(03): 35-40.
[7]	CAI Wen-peng, JU Shi-guang. Sensor Network Deployment Algorithm for 3D Surface with Multiple Mobile Nodes [J]. Computer and Modernization, 2020, 0(11): 70-76.
[8]	ZHANG Lei, CUI Juan-juan, LI Jing-jing. A Clustering Data Collection Algorithm in WSN Based on Compressed Sensing [J]. Computer and Modernization, 2020, 0(09): 1-5.
[9]	YAN Li-juan, ZHANG Yan-hu. An Average Residual Energy Based Clustering Routing Algorithm for Wireless Sensor Networks [J]. Computer and Modernization, 2020, 0(07): 16-20.
[10]	YI Wen-zhou. Improved WSN Coverage Algorithms Based on Differential Evolution #br# and Particle Swarm Optimization [J]. Computer and Modernization, 2019, 0(08): 33-.
[11]	GUO Xin, YAN Lian-shan, LI Hong-zhe, ZHANG Xiao-wei. High-risk Warehouse Wireless Monitor System Based on #br# Software Defined Wireless Sensor Network [J]. Computer and Modernization, 2018, 0(10): 84-.
[12]	SUN Zongxing， CAI Liping， LI Shibao. An Optimum Routing Algorithm for Wireless Sensor Networks #br# Based on Ant Colony Optimization [J]. Computer and Modernization, 2017, 0(8): 13-.
[13]	CHEN Fang, ZHAO Yang. Mobile Health Monitoring System Based on Cloud Computing [J]. Computer and Modernization, 2017, 0(7): 68-71+90.
[14]	ZHU Shi-zhao, XUE Shan-liang. A Source Location Privacy Preserving Protocol Based on Controllable Energy Consumption in WSN [J]. Computer and Modernization, 2017, 0(7): 95-100+123.
[15]	DONG Jun1, YANG Xiu-juan1, FU Xi-hui1, LIU Fu-gang2, XIE Zi-dian3, ZHANG Yang3. Improvement on DV-hop Location Algorithm in WSN#br# [J]. Computer and Modernization, 2017, 0(5): 15-18,23.