scholarly journals Research on Wireless Sensor Network Coverage Path Optimization Based on Biogeography-Based Optimization Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Guojun Chen ◽  
Xiangdong Qin ◽  
Ningsheng Fang ◽  
Wenbo Xu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Path Selection ◽  
Wireless Sensor ◽  
Particle Swarm Algorithm ◽  
Network Coverage ◽  
Simulation Experiments ◽  
Reasonable Choice ◽  
Better Than

Path selection is one of the key technologies of wireless sensor network (WSN). A reasonable choice of coverage path can improve the service quality of WSN and extend the life cycle of WSN. Biogeography-based optimization (BBO) is widely used in the field of cluster intelligent optimization because its search method has a better incentive mechanism for population evolution. In this paper, the move-in and move-out operation and mutation operation of the BBO algorithm enable WSN to find an efficient routing path. In this paper, simulation experiments are carried out in two scenarios of regular deployment and random deployment of WSN nodes. The experimental results show that the quality of the WSN coverage path solution optimized by the BBO algorithm in the two scenarios is better than that of the particle swarm algorithm and genetic algorithm.

scholarly journals Analysis of the Deployment Quality for Intrusion Detection in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Noureddine Assad ◽  
Brahim Elbhiri ◽  
Moulay Ahmed Faqihi ◽  
Mohamed Ouadou ◽  
Driss Aboutajdine
Keyword(s):  
Wireless Sensor Network ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Node Density ◽  
Major Question ◽  
Sensing Range

The intrusion detection application in a homogeneous wireless sensor network is defined as a mechanism to detect unauthorized intrusions or anomalous moving attackers in a field of interest. The quality of deterministic sensor nodes deployment can be determined sufficiently by a rigorous analysis before the deployment. However, when random deployment is required, determining the deployment quality becomes challenging. An area may require that multiple nodes monitor each point from the sensing area; this constraint is known ask-coverage wherekis the number of nodes. The deployment quality of sensor nodes depends directly on node density and sensing range; mainly a random sensor nodes deployment is required. The major question is centred around the problem of network coverage, how can we guarantee that each point of the sensing area is covered by the required number of sensor nodes and what a sufficient condition to guarantee the network coverage? To deal with this, probabilistic intrusion detection models are adopted, called single/multi-sensing detection, and the deployment quality issue is surveyed and analysed in terms of coverage. We evaluate the capability of our probabilistic model in homogeneous wireless sensor network, in terms of sensing range, node density, and intrusion distance.

scholarly journals Enhancing Network Coverage Using Sensing Models in Wireless Sensor Network

2021 ◽  
Vol 1717 ◽  
pp. 012062
Author(s):  
J Vidhya ◽  
P Prasanna ◽  
M Margarat ◽  
S Jayalakshmy
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Coverage

scholarly journals Performance metrics in wireless sensor networks :a survey and outlook

2018 ◽  
Vol 7 (2.26) ◽  
pp. 25
Author(s):  
E Ramya ◽  
R Gobinath
Keyword(s):  
Wireless Sensor Networks ◽  
Quality Of Service ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Performance Metrics ◽  
Resource Constraints ◽  
Sensor Data ◽  
Wireless Sensor

Data mining plays an important role in analysis of data in modern sensor networks. A sensor network is greatly constrained by the various challenges facing a modern Wireless Sensor Network. This survey paper focuses on basic idea about the algorithms and measurements taken by the Researchers in the area of Wireless Sensor Network with Health Care. This survey also catego-ries various constraints in Wireless Body Area Sensor Networks data and finds the best suitable techniques for analysing the Sensor Data. Due to resource constraints and dynamic topology, the quality of service is facing a challenging issue in Wireless Sensor Networks. In this paper, we review the quality of service parameters with respect to protocols, algorithms and Simulations. 

scholarly journals Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network

2019 ◽  
Vol 15 (8) ◽  
pp. 155014771986987 ◽  
Author(s):  
Zhanjun Hao ◽  
Nanjiang Qu ◽  
Xiaochao Dang ◽  
Jiaojiao Hou
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Particle Swarm Optimization Algorithm ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Swarm Optimization ◽  
Passive Monitoring ◽  
Link Model

3D coverage is not only closer to the actual application environment, but also a research hotspot of sensor networks in recent years. For this reason, a node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network is proposed in this article. According to wireless link-aware area, the link coverage model in three-dimensional wireless sensor network is constructed, and the cube-based network coverage is used to represent the quality of service of the network. This model takes advantage of the principle that the presence of human beings can change the transmission channel of the link. On this basis, the intruder is detected by the data packets transmitted between the wireless links, and then the coverage area is monitored by monitoring the received signal strength of the wireless signal. Based on this new link awareness model, the problem of optimal coverage deployment of the receiving node is solved, that is, how to deploy the receiving node to achieve the optimal coverage of the monitoring area when the location of the sending node is given. In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. Based on the genetic algorithm, the particle swarm optimization algorithm which integrates the idea of simulated annealing is regarded as an important operator of the genetic algorithm, which can converge to the optimal solution quickly. The simulation results show that the proposed method can improve the network coverage, converge quickly, and reduce the network energy consumption. In addition, we set up a real experimental environment for coverage verification, and the experimental results verify the feasibility of the proposed method.

Analyzing And Improving Quality Of Sensing In Wireless Sensor Network

2019 ◽  
Author(s):  
Edwin F. Palacios Melendez ◽  
Luis O. Philco Asqui ◽  
Luis S. Cordova ◽  
Tomas G. Bastidas Cabrera ◽  
Miguel A. Franco Bayas
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor
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