Meta-optimization for Charger Deployment in Wireless Rechargeable Sensor Networks
| Autor: | Yen-Chung Chen, 陳彥仲 |
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| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 In Wireless Rechargeable Sensor Networks (WRSNs), wireless chargers can recharge batteries of sensor nodes so that they can operate sustainably to provide WRSNs with the property of sustainability. Since wireless chargers are costly, how to apply as few as possible chargers to cover all sensor nodes and fulfill their charging demands for making WRSNs sustainable is thus an important problem. This paper proposes the GPSCD (Genetic Particle Swarm Charger Deployment) algorithm trying to optimize WRSN charger deployment. We use the genetic algorithm (GA) to encode the parameters of the particle swarm charger deployment (PSCD), which is an algorithm based on the particle swarm optimization (PSO). PSCD estimates a charger’s charging efficiency according to the distance and angle between the charger and sensor nodes and then utilizes PSO individual memory of the local optimum and PSO group memory of global optimum to adjust locations and antenna orientations of chargers. In this way, PSCD algorithm tries to use the minimum number of chargers to fulfill the demands of all sensor nodes. The number of chargers derived by the PSCD algorithm is the fitness value of the GA chromosome. Based on the fitness value of every chromosome, GA can then find out, through chromosome duplication, crossover, and mutation, the chromosome with the highest fitness value to reach the goal of using the minimum number of chargers to fulfill the charging demands of all sensor nodes. We perform experiments by using Powercast P2110-EVAL-02 wireless chargers to obtain charging efficiency for different distances and angles between chargers and sensor nodes. Based on the charging efficiency data, we simulate GPSCD and two related heuristic greedy algorithms, namely the Greedy Cone Covering (GCC) algorithm and the Adaptive Cone Covering (ACC) algorithm. The simulation results show that GPSCD indeed outperforms the other two algorithms in sense that it uses fewer chargers to fulfill the charging requirements of all sensor nodes to make WRSNs sustainable. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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