scholarly journals Addressing Non-linear Hardware Limitations and Extending Network Coverage Area for Power Aware Wireless Sensor Networks

10.5772/38726 ◽  
2011 ◽  
Author(s):  
Michael Walsh ◽  
Martin Hayes
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Coverage Area ◽  
Non Linear

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.

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 A Route Map for Wireless Sensor Networks over Large Coverage Area

2018 ◽  
Author(s):  
Rishabh Jain ◽  
Partha Saha Adhikary ◽  
Guillermo Ramirez-Prado ◽  
Bashar Barmada ◽  
Iman Ardekani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Coverage Area

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.

An Improved Clustering Algorithm Based on Coverage Area for Wireless Sensor Networks

2012 ◽  
Vol 542-543 ◽  
pp. 643-646
Author(s):  
Li Jun Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Topology Control ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Control Approach ◽  
Cluster Heads ◽  
Network Scalability

Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. A clustering algorithm based on the total number of neighbor nodes is proposed to maximize the lifetime of the network. The larger amount of neighbor nodes, the more chance a node has to be selected as a cluster head. Therefore, it can ensure the minimum cluster heads in the whole network. By closing the communication parts of cluster head to avoid selecting as cluster head in next epoch, the energy of the whole system is consumed symmetrically. The simulations demonstrate the effectiveness of the 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.

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