由於手機，平板電腦等具備網路功能的智慧型可攜式裝置之日益普及，由人類或其他實體裝置共同形成的新型態網路已日漸成為可能。由於此類型網路的連接是間歇性的(intermittent)，亦即不穩定的連線，文獻中將此種新型網路稱之為人群接觸網路(human contact network)[21]或延遲容忍網路(delay tolerant network)[22,9,23]或機會性行動網路(opportunistic mobile network)[24]。由於此類的網路連線的不穩定性，使得傳統建立和更新路由表的方法已失去效用。在這樣的網路上，資訊從發送端傳輸到目的地，只能先傳輸到其他中間節點，作為到目的地的中繼站，透過中繼站與下一中繼站或與目的地接觸的機會達到資訊傳輸的目的。因此，建構此類系統的關鍵，是下一個中繼站選擇的策略，以有效地進行資料傳送。
文獻中，針對此類系統的設計，已有非常多的方法被發表，分別提出各種不同的演算法與效能評估。近來，一些根據社會網路分析(social network analysis)的設計，顯示較之前方法更優異的效能。社會網路分析是一種研究社會結構、組織系統、人際關係、團體互動的概念與方法，是在社會計量學基礎上所發展出來的分析方法。由於人們在社會結構中具有特定與功能，並依此地位和與其他人們互動，文獻中針對社會結構在資訊流通與影響力的傳播的分析，也是一個熱門的議題[25]。因此，人群接觸網路的設計，也希望透過捕捉人們的社會特徵，建立社群的資訊，並利用這些社群的資訊設計路由演算法，可據以設計網路傳輸演算法，達到高效率的資料傳輸。

In recent years, it has become prevalent for people to carry a multitude of mobile devices. These devices can be networked to forms a novel, infra-structureless network that is called human contact network, or delay tolerant Networks. For such scenarios, end-to-end delivery through traditional routing algorithms is generally not applicable, because mobility is often unpredictable, and topology structure is highly dynamic.
A number of recent works have proposed to exploit the social behavior inherent with human beings for data dissemination. Two important social metrics, community and centrality, have been extensively studied to characterize human social behavior in social network analysis literature. These metrics have been exploited by the information dissemination systems to select forwarding paths, and have achieved good success. However, there is still much room for improvement for these early social-based approaches. For example, most of the systems operate based on social metrics calculated using a summarization of the contact history. These calculations do not reflect the dynamic and temporal nature of the human contacts.

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