可充電無線感測網路最佳化充電器佈置; Optimized Charger Deployment for Wireless Rechargeable Sensor Networks

NCU Institutional Repository > 資訊電機學院 > 資訊工程研究所 > 博碩士論文 > Item 987654321/61007

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题名:	可充電無線感測網路最佳化充電器佈置;Optimized Charger Deployment for Wireless Rechargeable Sensor Networks
作者:	廖基豪;Liao,Ji-Hau
贡献者:	資訊工程學系
关键词:	充電器佈置;工作週期;永續性;Charger Deployment;Duty Cycle;Sustainability
日期:	2013-07-26
上传时间:	2013-08-22 12:09:37 (UTC+8)
出版者:	國立中央大學
摘要:	可充電無線感測網路(Wireless Rechargeable Sensor Network, WRSN)中，可適時利用無線充電技術(Wireless Charging Technology)補充感測節點(Sensor Node)的電力，使整個感測網路得以持續運行，而具有永續性(Sustainability)。在WRSN中，有兩個重要問題 (1) 如何有效的佈置充電器而能以最少的充電器覆蓋所有的感測節點 (2) 如何制定合宜的充電器工作週期(Duty Cycle)。本論文針對可佈置於固定高度格子點(Grid Point)上具指向性天線(Directional Antenna)的無線充電器(Wireless Charger)，提出解決上述問題的三個演算法: (1)基於節點的貪婪圓錐選擇NB-GCS (Node Based Greedy Cone Selecting)演算法: 嘗試以個別節點相關聯圓錐為基礎，以貪婪方式選擇最小數量的充電器。(2) 基於點對的貪婪圓錐選擇 PB-GCS(Pair Based Greedy Cone Selecting) 演算法: 嘗試以每對節點相關聯圓錐為基礎，以貪婪方式選擇最小數量的充電器。(3) DCS(Duty Cycle Scheduling)演算法: 為了節省無線充電器的電力消耗，我們以感測節點的工作負載來推算其耗電率，並根據感測節點回報的充電效益來制定出各個無線充電器的工作週期。我們使用兩組Powercast P2110-EVAL-02充電器設備進行充電效益實測，以得到較貼近真實的模擬參數進行模擬，並另外進行時間複雜度分析，藉以比較NB-GCS演算法與PB-GCS演算法的效能，結果顯示PB-GCS演算法最佳化充電器數量的效果優於NB-GCS演算法，但NB-GCS有較低的時間複雜度。 In wireless rechargeable sensor networks (WRSNs), the power of sensor nodes can be supplied via wireless charging technology, such that the WRSNs operate sustainably. There are two important problems in WRSNs. (1) How to deploy the chargers as few as possible. (2) How to save the power consumption of these chargers. In this paper, we focus on the wireless chargers which equip a directional antenna which can be deployed on grid points at a fix height, and propose three algorithms to solve above problems. (1) Greedy heuristic algorithm node based greedy cone selecting (NB-GCS) algorithm: try to optimize the number of chargers based on node positions. (2) Greedy heuristic algorithm pair based greedy cone selecting (PB-GCS) algorithm try to optimize the number of chargers based on pairs of nodes. (3) Duty cycle scheduling (DCS) algorithm to formulate the duty cycle via charging efficiency information report from the sensor nodes for each charger to save its power consumption. We bought two Powercast P2110-EVAL-02 wireless charging equipment and measured the charging efficiency for obtaining the near reality simulation arguments. Then we took the simulation and analyzed the time complexity of NB-GCS and PB-GCS algorithm. According to the simulation result, PB-GCS is better than NB-GCS in optimizing the number of chargers, but NB-GCS has lower time complexity than PB-GCS.
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