感測半徑大小對監控生命週期及品質的影響

在這裡從表 7 中可以看出模擬參數是多少，並且有圖 34 和圖 35 顯示模擬出來的 生存時間還有接收訊息數量是多少。

參數 值

區域大小(m²) 500x500 感測點(Sensor Node)數量 200

感測點能量全滿(J) 1000

能量標準值(Threshold) 500 傳送封包頻率消耗比率(J/min) 30 移動載具速度(hop/min) 1 充電速度比率(J/min) 50

移動式載具數量 20

感測半徑 10、20、30

表 7. 改變感測半徑模擬參數

圖 34. 改變感測半徑生存時間的改變

圖 35. 改變感測半徑接收訊息的改變

從圖 34 中改變感測點感測點半徑，感測半徑越大鄰居數就會越多，鄰居數越多 收到的訊息量會變大，但生存時間不太會有太大變化。

圖 35 由於感測半徑變大，訊息量就會增多，鄰居變多訊息量就會變多，因此會 有明顯提升的傾向。

第6章 結論與未來展望

本篇論文的主要動機是要設計出最佳充電排程演算法以派遣移動式充電載具前 往進行充電。先前的研究沒有考慮連接強度，因此在這方面我們設計了兩個方法經由 這些方法有效改善了前人的缺點，無論在生存期限或是訊息的接收都有較好的結果。

不過由於我們方法裡有做切割感測網路的部分，在此部分發現切割也是一個很 重要的因素，由於感測點會把訊息傳送給基地台，因此會有越前面的感測點會越耗損 電力的狀況。因此如果有好的分割方法提出，是可以提升更佳的結果。此外感測網路 進行切割，每個區塊有各自移動式載具，可能發生此區塊沒有任何感測點需要執行充 電的需求，導致此移動式載具沒有任務可以執行。如果可以使空閒的移動式載具幫助 其它區塊，或許也是個提升感測網路生存週期的方法。

未來將考慮無定位系統(GPS-free)下自動充電排程演算法之設計及無定位系統下 自動充電排程演算法之分散式演算法設計。

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