使用可移動的資料收集器在無線感測網路中收集資料是一個重要的研究議題。過去的作法如果不是會消耗太多的能量，就是資料傳輸成功率很低。在這篇論文中，我們針對如何在無線感測網路中，利用可移動的資料收集器以收集資料提出了兩個新的方法。第一種方法是Partial Adaptive Tree (PAT)，首先我們在無線感測網路中建立資料收集樹。當可移動的資料收集器從一個地方移動到另一個地方時，我們提出的方法可以減少資料收集樹必須更新的部分。第一種方法是Partial Adaptive Tree with Path Pruning (PAT-PP)，將路徑修剪的觀念引入PAT。模擬結果顯示，我們提出的這兩種方法都顯著地藉由降低更新的花費而減少能源消耗。此外，不論節點密度高低或是資料收集器的速度快慢，PAT-PP都可以保持更高的資料傳輸率。Data collection in wireless sensor network with a mobile sink is an important research issue. The past approaches are that either consume too much energy or produce low delivery rate. In this thesis, we propose two novel approaches to collect data for wireless sensor networks in the presence of a mobile sink. The first approach, called Partial Adaptive Tree (PAT), reduces the update portion of the tree when the mobile sink moves from one place to another. The second approach, called Partial Adaptive Tree with Path Pruning (PAT-PP), applies the concept of path pruning on top of PAT. The simulation results show that both proposed approaches reduce the energy consumption significantly. In addition, PAT-PP is able to maintain a high delivery rate regardless of the node density and the speed of the mobile sink.
