結論

在先期的研究中，我們探討無線感測網路的拓樸控制方法，並將其方法成功的整合 於無線網路模擬器中進行實驗，進而驗證拓撲控制之成效性。二期的研究中，我們則針 對在無線感測網路環境下的同儕應用程式，利用隨機行走的方式，建立新的繞送路徑，

使物件能成功送達，提昇系統可用性。此外，我們還利用數學模型及實際模擬來驗證記 憶體消耗、通訊成本及系統收斂時間。我們得知該方法除了可以有效的修復錯誤的路 徑，提高可靠度外，同時亦具有良好的擴充性，可以應用於動態網路的應用環境。三期 研究中，為了讓社區照護能在無線隨意網路有良好的資料可讀性，我們同樣針對同儕通 訊模式，提出了一個分散式隨機資料複製演算法，分散式的特性可以維持系統的擴充 性，而隨機的特性又可以有效率地使用記憶體空間；此外我們使用了path coupling 來推 導系統的收斂時間上線，並透過模擬結果來驗證系統特性。

考慮目前現有的環境來說，由於無線設備相當普及，未來可嘗試將拓撲控制方法整 合至感測器的作業系統當中，配合上層應用程式，提供節能的運作環境。另外，由於隨 機演算法的簡單的特性，在實際的分散式系統中經常被拿來應用，然而針對演算法的機 率分析，往往非常複雜[38]。在這篇報告中，利用機率分析來推導演算法的收斂時間；

原則上，我們若是能將path coupling設計的更好，例如更適合的δ，或是更嚴謹的coupling rule，則可以得到更好的上限值。另外，若是節點可以獲得較多的資訊，不論是在容錯 能力，或是複製物件工作皆會更有效率。舉例來說，容錯系統若是能知道附近節點的電 力狀態，在隨機行走時可以避開某些電力不足的節點，降低再次發生錯誤的機率；資料 複製方面，若知道鄰節點所要複製的物件，則可避開複製相同的物件。不過有雖然這些 機制可以提昇系統效率，伴隨而來的卻是通訊成本的增加，如何在兩者之間取得平衡，

是一個相當重要的議題。另一方面，在設計同儕應用的相關程式時，同儕應用的畢需要 考慮到物件的普及性(popularity)及節點的移動問題，為了使整個系統更有效率，演算法 設計必須朝線上演算法(online algorithm)或是跨層設計的目標前進，以破除現有設計的 障礙。

總的來說，在這個計畫中我們研發了低耗能、高可靠度的解決方案，除了可以與其 他子計畫結合，應用於社區照護系統之外，我們相信這裡所提出的技術與概念，還可以 更進一步地套用在其他無線隨意網路的相關應用中。

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Because the sensors usually do not have fixed power supply, when some sensors in the network exhaust their energy, it will lower the network performance and lifetime. On the other words, this will lower the efficient and reliability, but it is not allowed by health system. This plan studies a communication protocol which can significantly lower the energy drain rate and extend the network lifetime.

可利用之產業