Localization Algorithm Based on a Spring Model (LASM) for Large Scale Wireless Sensor Networks

Sensors

Wanming Chen²  Tao Mei²  Max Q.-H. Meng²  Huawei Liang²  Yumei Liu¹  Yangming Li² 

[1]Department of Automation, University of Science and Technology of China, Hefei, 230027, P.R. China

[2]Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, 230031, P. R. China

[3] E-mail:

关键词: Localization algorithm;    spring model;    large scale wireless sensor networks;    robot navigation;   

DOI  :  10.3390/s8031797

来源: mdpi

【 摘 要 】

A navigation method for a lunar rover based on large scale wireless sensor networks is proposed. To obtain high navigation accuracy and large exploration area, high node localization accuracy and large network scale are required. However, the computational and communication complexity and time consumption are greatly increased with the increase of the network scales. A localization algorithm based on a spring model (LASM) method is proposed to reduce the computational complexity, while maintaining the localization accuracy in large scale sensor networks. The algorithm simulates the dynamics of physical spring system to estimate the positions of nodes. The sensor nodes are set as particles with masses and connected with neighbor nodes by virtual springs. The virtual springs will force the particles move to the original positions, the node positions correspondingly, from the randomly set positions. Therefore, a blind node position can be determined from the LASM algorithm by calculating the related forces with the neighbor nodes. The computational and communication complexity are O(1) for each node, since the number of the neighbor nodes does not increase proportionally with the network scale size. Three patches are proposed to avoid local optimization, kick out bad nodes and deal with node variation. Simulation results show that the computational and communication complexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps are almost unrelated with the network scale size.

【 授权许可】

Unknown   
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