A survey of movement strategies for improving network coverage in wireless sensor networks

2009 ◽  
Vol 32 (13-14) ◽  
pp. 1427-1436 ◽  
Author(s):  
Bang Wang ◽  
Hock Beng Lim ◽  
Di Ma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Movement Strategies

scholarly journals Improved whale optimization algorithm and its application in heterogeneous wireless sensor networks

2021 ◽  
Vol 17 (5) ◽  
pp. 155014772110181
Author(s):  
Yinggao Yue ◽  
Hairong You ◽  
Shuxin Wang ◽  
Li Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Algorithm ◽  
Whale Optimization Algorithm ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Coverage Optimization ◽  
Network Cost ◽  
Whale Optimization ◽  
Heterogeneous Wireless Sensor Networks

Aiming at the problems of node redundancy and network cost increase in heterogeneous wireless sensor networks, this article proposes an improved whale optimization algorithm coverage optimization method. First, establish a mathematical model that balances node utilization, coverage, and energy consumption. Second, use the sine–cosine algorithm to improve the whale optimization algorithm and change the convergence factor of the original algorithm. The linear decrease is changed to the nonlinear decrease of the cosine form, which balances the global search and local search capabilities, and adds the inertial weight of the synchronous cosine form to improve the optimization accuracy and speed up the search speed. The improved whale optimization algorithm solves the heterogeneous wireless sensor network coverage optimization model and obtains the optimal coverage scheme. Simulation experiments show that the proposed method can effectively improve the network coverage effect, as well as the utilization rate of nodes, and reduce network cost consumption.

Path coverage enhancement in wireless sensor networks based on CVT model

2021 ◽  
pp. 1-13
Author(s):  
Guangxu Yu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Probability ◽  
Coverage Rate ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Current Path ◽  
Coverage Model ◽  
Path Coverage ◽  
Low Coverage

In order to overcome the problems of low detection probability, low coverage uniformity and low coverage of current path coverage enhancement methods in wireless sensor networks, a new path coverage enhancement method based on CVT model is proposed in this paper. Firstly, the node perception model and network coverage model are constructed. On the basis of the node awareness model and network coverage model, CVT model is used to adjust the connection mode, density and location of nodes in wireless sensor networks, so as to improve the coverage performance of nodes in the detection area in wireless sensor networks, and realize the effective enhancement of path coverage in wireless sensor networks. Experimental results show that, compared with the traditional methods, the proposed method has high detection probability, high coverage uniformity and coverage rate, and the highest coverage rate reaches 97%, which has higher practical application performance.

scholarly journals Bioinspired Evolutionary Algorithm Based for Improving Network Coverage in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Mohammadjavad Abbasi ◽  
Muhammad Shafie Bin Abd Latiff ◽  
Hassan Chizari
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Evolutionary Algorithm ◽  
Sensor Node ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Area ◽  
Network Coverage ◽  
Detection Model

Wireless sensor networks (WSNs) include sensor nodes in which each node is able to monitor the physical area and send collected information to the base station for further analysis. The important key of WSNs is detection and coverage of target area which is provided by random deployment. This paper reviews and addresses various area detection and coverage problems in sensor network. This paper organizes many scenarios for applying sensor node movement for improving network coverage based on bioinspired evolutionary algorithm and explains the concern and objective of controlling sensor node coverage. We discuss area coverage and target detection model by evolutionary algorithm.

scholarly journals Method for Patching Three-Dimensional Surface Coverage Loopholes of Hybrid Nodes in Wireless Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Zhanjun Hao ◽  
Hongwen Xu ◽  
Xiaochao Dang ◽  
Nanjiang Qu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Three Dimensional ◽  
Wireless Sensor ◽  
Utilization Rate ◽  
Network Coverage ◽  
Mobile Nodes ◽  
Research Information ◽  
Information Monitoring ◽  
Dimensional Surface

Target sensing and information monitoring using wireless sensor networks have become an important research field. Based on two-dimensional plane research, information monitoring, and transmission for three-dimensional curved target events, due to the uneven deployment of nodes and failures in sensor networks, there are a lot of coverage loopholes in the network. In this paper, a method of detecting and repairing loopholes in monitoring the coverage of three-dimensional surface targets with hybrid nodes is proposed. In the target monitoring area where the hybrid nodes are randomly deployed, the three-dimensional surface cube is meshed, and the coverage loopholes are gradually detected according to the method of computational geometry, and then, the redundant mobile nodes around the coverage loopholes are selected. According to the calculated distance to cover the moving direction and distance of the loophole, the virtual force is used to adjust the mobile nodes to repair the coverage loopholes. Simulation results show that compared with other algorithms, this algorithm has a higher utilization rate of mobile nodes, uses fewer nodes to complete coverage, reduces network coverage costs, meets the overall network coverage requirements, and has lower mobile energy consumption and longer network life. The actual scene further verifies the good connectivity and high coverage of the whole network.

Coverage Optimization of Hybrid Wireless Sensor Networks Based on Modified Particle Swarm Algorithm

2013 ◽  
Vol 846-847 ◽  
pp. 914-917
Author(s):  
Su Fen Yao ◽  
Jian Qiang Zhao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Pso Algorithm ◽  
Wireless Sensor ◽  
Particle Swarm Algorithm ◽  
Local Optimum ◽  
Network Coverage ◽  
Mobile Nodes ◽  
Coverage Optimization ◽  
Adaptive Neighborhood

A strategy for controlling mobile nodes based on PSO algorithm with neighborhood disturbance was proposed for improving the network coverage rate in wireless sensor networks. The non-dominated sorting strategy was led into basic PSO algorithm to seek best particle and adaptive neighborhood disturbance operation was used to conquer the drawback of PSO falling into local optimum. Therefore, the effect of network coverage had been improved and the network energy consumption can be reduced.

scholarly journals Genetic Algorithm Application in Optimization of Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Ali Norouzi ◽  
A. Halim Zaim
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Fitness Function ◽  
Optimization Methods ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Final Formula ◽  
Nonlinear Optimization Methods

There are several applications known for wireless sensor networks (WSN), and such variety demands improvement of the currently available protocols and the specific parameters. Some notable parameters are lifetime of network and energy consumption for routing which play key role in every application. Genetic algorithm is one of the nonlinear optimization methods and relatively better option thanks to its efficiency for large scale applications and that the final formula can be modified by operators. The present survey tries to exert a comprehensive improvement in all operational stages of a WSN including node placement, network coverage, clustering, and data aggregation and achieve an ideal set of parameters of routing and application based WSN. Using genetic algorithm and based on the results of simulations in NS, a specific fitness function was achieved, optimized, and customized for all the operational stages of WSNs.

scholarly journals ACO-Based Sweep Coverage Scheme in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Peng Huang ◽  
Feng Lin ◽  
Chang Liu ◽  
Jian Gao ◽  
Ji-liu Zhou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Sensors ◽  
Wireless Sensor ◽  
Data Delivery ◽  
Network Coverage ◽  
Coverage Problem ◽  
Points Of Interest ◽  
Novel Algorithm

Coverage problem is one of the major issues in wireless sensor networks (WSN). In order to optimize the network coverage, different coverage formulations have been proposed. Recently, a newly emerging coverage scheme in wireless sensor networks, sweep coverage, which uses mobile sensors to monitor certain points of interest (POIs), is proposed. However, the data delivery to sink, an important problem in WSN, is not considered in original sweep coverage and many of the existing works did not consider it yet. In this work, a novel algorithm named ACOSC (ACO-based sweep coverage) to solve the sweep coverage problem considering periodical coverage of POIs and delivery of data simultaneously is proposed. The evaluation results show that our algorithm has better performance than existing schemes.

Sign in / Sign up

Export Citation Format

Share Document