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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
Wang Yu-Ping
Xidian University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Coverage Repair Strategies for Wireless Sensor Networks using Mobile Actor Based on Evolutionary Computing Ye Miao; Wang Yu-Ping
Bulletin of Electrical Engineering and Informatics Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (398.001 KB) | DOI: 10.11591/eei.v3i3.285

Abstract

A standard traveling salesman problem(TSP) under dual-objective strategy constrained is proposed in this paper, characterized by the fact that the demand of both as many as possible the numbers of nodes be visited in time and minimum trajectory distance. The motivation for this TSP problem under dual-objective strategy constrain stems from the coverage repair strategies for wireless sensor networks using mobile actor based on energy analysis, wherein a mobile robot replenishes sensors energy when it reaches the sensor node location. The Evolutionary Algorithm (EA) meta-heuristic elegantly solves this problem by the reasonable designed operators of crossover, mutation and local search strategy,which can accelerate convergence of the optimal solution. The global convergence of the proposed algorithm is proved, and the simulation results show the effectiveness of the proposed algorithm.
Coverage Repair Strategies for Wireless Sensor Networks using Mobile Actor Based on Evolutionary Computing Ye Miao; Wang Yu-Ping
Bulletin of Electrical Engineering and Informatics Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v3i3.285

Abstract

A standard traveling salesman problem(TSP) under dual-objective strategy constrained is proposed in this paper, characterized by the fact that the demand of both as many as possible the numbers of nodes be visited in time and minimum trajectory distance. The motivation for this TSP problem under dual-objective strategy constrain stems from the coverage repair strategies for wireless sensor networks using mobile actor based on energy analysis, wherein a mobile robot replenishes sensors energy when it reaches the sensor node location. The Evolutionary Algorithm (EA) meta-heuristic elegantly solves this problem by the reasonable designed operators of crossover, mutation and local search strategy,which can accelerate convergence of the optimal solution. The global convergence of the proposed algorithm is proved, and the simulation results show the effectiveness of the proposed algorithm.
Coverage Repair Strategies for Wireless Sensor Networks using Mobile Actor Based on Evolutionary Computing Ye Miao; Wang Yu-Ping
Bulletin of Electrical Engineering and Informatics Vol 3, No 3: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (398.001 KB) | DOI: 10.11591/eei.v3i3.285

Abstract

A standard traveling salesman problem(TSP) under dual-objective strategy constrained is proposed in this paper, characterized by the fact that the demand of both as many as possible the numbers of nodes be visited in time and minimum trajectory distance. The motivation for this TSP problem under dual-objective strategy constrain stems from the coverage repair strategies for wireless sensor networks using mobile actor based on energy analysis, wherein a mobile robot replenishes sensors energy when it reaches the sensor node location. The Evolutionary Algorithm (EA) meta-heuristic elegantly solves this problem by the reasonable designed operators of crossover, mutation and local search strategy,which can accelerate convergence of the optimal solution. The global convergence of the proposed algorithm is proved, and the simulation results show the effectiveness of the proposed algorithm.
Co-Authors Ye Miao