移動式無線感測網路之適應性傳輸協定設計

Abstract

本論文探討以隨意隨選距離向量(Ad-hoc on demand distance vector, AODV)為基礎的動態通訊網路，並應用於居家生理監測系統中。生理監測產品包含人體姿態辨識模組、血氧濃度(SpO2)感測器和心電圖(ECG)感測器。由於AODV為找尋hop count數最小的路徑，但hop count數最小的路徑不一定為最佳路徑。因此本論文提出一種新的傳輸協定設計方式，結合訊號強度和電池電量為路徑選擇依據並以做模糊邏輯選擇訊號穩定且電量充足的較佳路徑，以增加傳送的成功率。發展出以AODV為基礎的動態通訊網路，考慮訊號強度與電池電量之情形下，在模擬時傳送成功率可由原來的81%提升至90%，而實作時的傳送成功率從66%上升至94%。並將此應用於家中老年人生理狀況的監測，得知家中老年人是否有異常狀況發生。

In this thesis, we developed an adaptive route selection algorithm for a Mobile Ad-hoc Network (MANET). This algorithm has been realized and implemented to health care products. The health care products include pose estimated module, SpO2 sensor and ECG sensor. Conventional Ad-hoc On-Demand Distance Vector (AODV) looks for a route which has the smallest hop count, but the route with the smallest hop count might not be the best route. In this thesis we propose a new routing protocol to combine signal strength and battery level into account, and uses fuzzy inference to search a route with stable RF signal. Simulation results show that the packet delivery ratio rises from 81% to 90%. In practical experiment on Zigbee MANET the packet delivery ratio raises from 66% to 94%. The proposed MANET has also been experimented in practical healthcare application by integrating a pose estimated module and a SpO2 sensor.