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Li J, Serpen G. Adaptive and intelligent wireless sensor networks through neural networks: an illustration for infrastructure adaptation through Hopfield network. APPL INTELL 2016. [DOI: 10.1007/s10489-016-0761-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Yu X, Liu N, Qian X, Zhang T. A Deployment Method Based on Spring Force in Wireless Robot Sensor Networks. INT J ADV ROBOT SYST 2014. [DOI: 10.5772/58427] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Robotic sensor deployment is fundamental for the effectiveness of wireless robot sensor networks-a good deployment algorithm leads to good coverage and connectivity with low energy consumption for the whole network. Virtual force-based algorithms (VFAs) is one of the most popular approaches to this problem. In VFA, sensors are treated as points subject to repulsive and attractive forces exerted among them-sensors can move according to imaginary force generated in algorithms. In this paper, a virtual spring force-based algorithm with proper damping is proposed for the deployment of sensor nodes in a wireless sensor network (WSN). A new metric called Pair Correlation Diversion (PCD) is introduced to evaluate the uniformity of the sensor distribution. Numerical simulations showed that damping can affect the network coverage, energy consumption, convergence time and general topology in the deployment. Moreover, it was found that damping effect (imaginary friction force) has significant influence on algorithm outcomes. In addition, when working under approximate critical-damping condition, the proposed approach has the advantage of a higher coverage rate, better configurational uniformity and less energy consumption.
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Affiliation(s)
- Xiangyu Yu
- School of Electronic and Information Engineering, South China University of Technology, China
| | - Ninghao Liu
- School of Electronic and Information Engineering, South China University of Technology, China
| | | | - Tao Zhang
- School of Electronic and Communication Engineering, Guiyang University, China
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