資訊世代的來臨，手機、筆記型電腦、iPod、iPad不勝枚舉的手持行動裝置充斥在我們的生活周遭。這些裝置上都擁有一種以上的無線網路介面，例如:紅外線、藍芽、WiFi，及行動網路介面等。由於手持裝置的盛行，構成行動隨意網路(Mobile Ad Hoc Network)的傳輸空間越來越普遍，伴隨而來的問題如節點可能任意移動，拓樸不斷改變等，造成傳輸中斷。而在有網路的環境下如何從較信任的人(節點)獲取較可信任的資訊，將是重要的議題。因此本論文導入目前炙手可熱與我們生活密不可分的社群網路(social network)，利用社會網路分析(social network analysis)將人與人之間關係數據化，做為轉傳依據。我們提出Ego-Centric Social Network Routing中繼節點 (relay node) 選擇的策略，簡稱ECSNR。除了利用社會網路分析的方法外也加入候選清單，使負載過重的節點直接由清單中之候選節點協助轉傳、推薦清單，讓路由中繼的位置更靠近負載過重之節點，加速訊息的傳遞，也可藉由緊密度高且較可信任之節點協助傳送。另外當訊息無法藉由社會網路輔助(social networking aided)傳輸時，便會利用興趣導向(interest-based)傳輸，依照節點興趣相似性判別興趣區間，將訊息傳遞出去。最後，由實驗模擬結果得知，當網路節點數量增加時，封包送達率能有7.4%~15.8%的改善。End to end delay有10%~15.2%的改善；control overhead雖然較遜色，但依然平均控制在9.4%內。Average hop count平均減少1.7 個hops數。網路移動速度比較的實驗中，封包送達率能有8%~24.2%的改善；control overhead雖然較遜色，但依然平均控制在8.8%內。End to end delay有約4.7%~15.2%的改善；average hop count平均減少2.4個hops數。 / With the coming of information era, our lives have been filled with varied mobile devices, such as cell phones, notebooks, iPods, and iPads. All these devices are equipped with more than one wireless network interface, including Infrared, Bluetooth, WiFi, mobile network interface etc. Due to the popularity of mobile devices, Mobile Ad Hoc Networks have been more widespread than ever. However, movable nodes and the constantly changing topology could cause transmission interruption. Therefore, “how to obtain trustworthy information from trusty nodes” is a significant issue. This thesis geared toward the social network which is inseparable from our lives at this moment. In this thesis, social network analysis is employed, and the relationship data is used as the base of relay. We propose a relay-node selection strategy of Ego-Centric Social Network Routing (ECSNR), and apply the method of using candidate list. All these can be used to speed up the transmission process. Because the candidate nodes are the closest ones to the overloaded nodes, the relay process can be more efficient and speedy. The transmission can also be done through the stable and trustworthy nodes. When a message can not be transmitted through the social network aided nodes, the interest based nodes can help to transmit according to the interest similarity. The results of experiment simulations show that along with the increase of network nodes, the packet delivery ratio can be improved by 7.4% ~ 15.8%. The end to end delay can be improved by 10% ~ 15.2%, and the average control overhead is within 9.4%. The average hop count can be reduced by 1.7 hops. Given the nodes are moving, the packet delivery ratio can be improved by 8%~24.2%, and the average control overhead is within 8.8%. The end to end delay can be improved by 4.7% ~ 15.2%, and the average hop count can be reduced by 2.4 hops.