National Natural Science Foundation of China (No.61173153, No.60903159, No.61070162, No.71071028);National Natural Science Foundation of China for Distinguished Young Schoolars (No.61225012);Supported by Fundamental Research Funds for the Central Universities (No.N110404014, No.N110318001, No.N110204003, No.N120104001);China Postdoctoral Science Foundation (No.20110491508, No.2012T50248);Ph.D. Programs Foundation of Higher Education Institutions of China Priority Development Fields (No.20120042130003);Supported by the Open Foundation for Computer Application Technology of Shenyang Ligong University (No.4771004kfx06)
JIA Jie, ZHANG Gui-yuan, CHEN Jian, et al. Distributed Node Localization Based on Potential Game in Wireless Sensor Networks[J]. Acta Electronica Sinica, 2014, 42(9): 1724-1730.
DOI:
JIA Jie, ZHANG Gui-yuan, CHEN Jian, et al. Distributed Node Localization Based on Potential Game in Wireless Sensor Networks[J]. Acta Electronica Sinica, 2014, 42(9): 1724-1730. DOI: 10.3969/j.issn.0372-2112.2014.09.010.
Distributed Node Localization Based on Potential Game in Wireless Sensor Networks
Distributed node localization is an important issue in wireless sensor networks.However
traditional distributed localization algorithms have the drawback of low localization accuracy and high processing complexity.In response to these problems
a distributed localization model based on game theory is presented
where the utility function for each participant is defined as the sum of neighbor distance error.Formally
the proposed localization game is proved as a type of potential game.Through theoretical analysis
the existence of Nash Equilibrium and the validity of the final converged solution are testified.Furthermore
a distributed localization algorithm based on game theory is proposed
where each sensor exchanging information only with its neighbors.Finally
to avoid converging in local optimum and accelerate the convergence speed
the strategy space determination and unknown nodes elevation are developed.Extensive simulation results are performed to demonstrate the effectiveness of our proposed algorithm.