A Virtual Potential Field Based Coverage-Enhancing Algorithm for Directional Sensor Networks

Tao, Dan

doi:10.1360/jos181152

Cited by 73 publications

(73 citation statements)

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“…We set the threshold , and when > , the target is perceived, whereas the target is perceived loss. Here is set to the initial probability 0 [23,24]:…”

Section: Coverage Modelmentioning

confidence: 99%

Directional Probability Perceived Nodes Deployment Based on Particle Swarm Optimization

Zhang

Lei

Chen

et al. 2016

International Journal of Distributed Sensor Networks

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Node deployment is the key problem of wireless sensor network technology. For a directional sensor network, the perceived probability model reflects the quality of the network. The problem of the probability node deployment is too little of the distribution of the nodes asymmetrical. In this paper, we study the probability model of directional perceived nodes and propose an improved deterministic deployment algorithm based on particle swarm optimization to increase perceived probability. By analyzing the coverage probability of the monitoring area with different deployment models to obtain more serviceable environmental data of the monitoring areas, experimental results demonstrate that, compared with random deployment, sixteen percent is improved by the proposed algorithm.

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“…We set the threshold , and when > , the target is perceived, whereas the target is perceived loss. Here is set to the initial probability 0 [23,24]:…”

Section: Coverage Modelmentioning

confidence: 99%

Directional Probability Perceived Nodes Deployment Based on Particle Swarm Optimization

Zhang

Lei

Chen

et al. 2016

International Journal of Distributed Sensor Networks

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show abstract

“…In order to get effective quality information of the monitoring area, we set the threshold  , when    i p , the target is perceived, vice versa, the target is perceived loss. Here  is set to the initial probability p 0 [25]:…”

Section: Figure 1 the Rotatable Fan Modelmentioning

confidence: 99%

Deterministic Deployment for Directional Sensor Nodes

Lei

Wen

Xuan

et al. 2016

International Journal on Smart Sensing and Intelligent Systems

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Abstract-Node deployment is the key problem of wireless sensor network technology in application.The existing study on deployment of deterministic perceived nodes is simplified to the randomly deployment. In this paper, we take the effective coverage , connectivity and probability threshold as the evaluation indices to analyze the different deployment models. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes; and if the probability is less than limits, tile deployment does not need to increase the node to ensure coverage. The research results of this paper provide an important reference for the deployment of the directional sensor networks with the given parameters.

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“…For given region, several algorithms have been presented to optimize network coverage based on virtual force. Tao et al translated the coverage problem into the centroid points' uniform distribution problem [5] . Each node adjusted direction with same angle to reduce the overlapping regions and increase the coverage of sensing blanks.…”

Section: Related Workmentioning

confidence: 99%

Coverage-enhancing Algorithm Based on Priority in WMSN

Xiong¹,

Nie²,

Zhang³

et al. 2016

Proceedings of the 2016 International Conference on Computer Engineering and Information Systems

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Abstract-Coverage area and network lifetime are major problems in wireless multimedia sensor networks (WMSN). In order to optimize the network coverage and maximize the network's lifetime, we propose a coverage-enhancing algorithm based on sensors' priority. To increase the lifetime of the network, the density of distributed sensors could be such that a subset of sensors can cover the required air space. The sensors are prioritized based on their visual and Communicative properties and the selection is performed according to the prioritizing function. Simulation results show that the proposed algorithm achieves more effective enhancement on network coverage compared to the existing algorithm.

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A Virtual Potential Field Based Coverage-Enhancing Algorithm for Directional Sensor Networks

Cited by 73 publications

References 0 publications

Directional Probability Perceived Nodes Deployment Based on Particle Swarm Optimization

Directional Probability Perceived Nodes Deployment Based on Particle Swarm Optimization

Deterministic Deployment for Directional Sensor Nodes

Coverage-enhancing Algorithm Based on Priority in WMSN

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