穿戴式裝置網路逐漸興起,為一般人提供健康照護、訊息通知、及資料傳遞等服務。在穿戴式裝置網路中,智慧型手機成為一個合適的閘道器協助轉發穿戴式裝置與後端伺服器之間的資料傳遞。我們觀察到人類移動性與其姿勢改變會對網路效能產生一些影響。人類的移動性會造成從存取點到手機之間的資料傳輸失誤;而人體姿勢改變則有可能使得手機與穿戴式裝置之間連線發生短暫中斷的情形,使感測資料有可能會永久遺失。在此篇論文中,我們利用人類移動的規律性,來提高資料傳遞的成功率,降低人類移動對網路效能的影響;我們提出了一個佈點與路由樹生成的框架,並透過 NS2 模擬器基於兩個真實世界的環境展示所提出之框架的高效性。接著,我們提出了利用周遭 Wi-Fi 網路來暫存感測資料的方法來避免因為人體姿勢改變所造成的連線中斷而資料遺失之問題。我們在控制及實際世界兩個情境進行了一連串基於原型系統的實驗來驗證所提出之方法的可行性與成效。最後,我們利用人類移動性與穿戴式裝置會發生無線電波兩個特性,提出了一套利用都普勒效應之救難協助系統,並將此系統實作成一個 Android 手機程式進行實驗。
Wearable networks have emerged recently to provide notification, news update, and health monitoring for normal people. In a wearable network, the human's smartphone is deemed an appropriate gateway to help forward the sensing/update data to/from back-end servers. We observe that human mobility and postural changes can cause great impact on the network. Delivery failures from APs to the smartphone occur constantly due to human mobility, while temporary disconnection between sensors and the smartphone can happen frequently due to postural changes, causing a significant amount of data to be lost forever. In this thesis, to deal with the human mobility, we exploit the regularity in human mobility patterns to increase the data delivery ratio and mitigate the effects of packet loss caused by the human mobility. We propose a node deployment and tree construction framework; the effectiveness of network topologies constructed under the framework is demonstrated via comprehensive NS2 simulations based on two real-world scenarios. Then, to deal with the postural changes, we propose a scheme to parasitize the data in surrounding Wi-Fi networks whenever temporary disconnection occurs. To evaluate our scheme, we conduct a series of experiments with the prototype system in controlled and real-world environments. Finally, with the mobility issues appropriately addressed, we propose a rescue system which uses the Doppler effect to determine the direction of Wi-Fi signals emitted from disaster survivors' mobile devices, to help the rescuers find those people in need more quickly. We implement the rescue system in a mobile application for Android smartphones and conduct extensive experiments.
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