A Genetic Fuzzy Tree Based Moving Strategy for a Group of Nodes in Heterogeneous WSN
This paper introduces a novel moving strategy for a group of nodes in heterogeneous wireless sensor networks to improve the performance of target tracking. It employs a two-layer fuzzy tree system (FTS) constructed by two fuzzy inference systems (FISs) to decide which group of nodes move and how they move. The first FIS gives a score to each node and selects the group of moving nodes. The second FIS then controls the moving distance of the moving nodes. The Pittsburgh genetic algorithm is used to optimize the whole rule base and data base of the FTS. Simulation results show that the tracking accuracy can be improved after moving of the selected nodes.
KeywordsMoving strategy A group of nodes Target tracking Fuzzy tree system Genetic algorithm
This work was supported by the National Natural Science Foundation of China (61671138), the Fundamental Research Funds for the Central Universities Project No. ZYGX2015J021, and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.
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