在廣大的延遲網路中，節點往往都分散成多個不同獨立的叢集。因此，透過長距離傳輸技術來協助散播訊息是一種非常有效率的做法。但同時因為長距離傳輸技術的成本較高，所以更需要謹慎的來選擇對應的傳輸節點。為了解決這個問題，我們提出一個對應傳輸節點選擇演算法，使用使用者位置等歷史紀錄作為預測的基準，來確保我們所選擇的對應傳輸節點能有效地將訊息再次散播。由於訊息的散播率取決於每次廣播時收到訊息的節點的多寡，因此重複廣播節點的選擇將奠定我們所提出的方法的效能。為了檢驗我們所提出之演算法的效能，我們架構了兩種不同的模擬方式來驗證：重複廣播節點選擇模擬以及整體訊息散播率模擬。模擬數據證實我們所提出的對應傳輸節點選擇演算法，在大範圍的耐延遲網路傳輸中能顯著的使網路涵蓋能力上升。同時模擬數據更進一步顯示我們的演算法能夠減少傳播時間，且同時傳輸成本並未明顯的增加。

DTN is an intermittently connected wireless ad hoc network with high error rates and long or variable delay caused by the traditional store-carry-forward message dissemination protocol. In this work, we propose a Social-Based Broadcasting message dissemination protocol which incorporates long range communication with broadcasting to reduce the end-to-end delay and increase reliability. To reduce delay, the long range communication enables the message to simultaneously disseminate from various locations. To increase reliability, we proposed a rebroadcast node selection mechanism to disseminate the message to as many nodes as possible per rebroadcast. To investigate the performance of our proposed method, we constructed two simulations: rebroadcast node selection performance simulation and overall message dissemination performance simulation. The extensive simulation results demonstrate that our proposed method is practical, scalable and cost-effective for message dissemination in a DTN.

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