Emergent Mind

Abstract

Opportunistic mobile social networks (MSNs) are modern paradigms of delay tolerant networks that consist of mobile users with social characteristics. The users in MSNs communicate with each other to share data objects. In this setting, humans are the carriers of mobile devices, hence their social features such as movement patterns, similarities, and interests can be exploited to design efficient data forwarding algorithms. In this paper, an overview of routing and data dissemination issues in the context of opportunistic MSNs is presented, with focus on (1) MSN characteristics, (2) human mobility models, (3) dynamic community detection methods, and (4) routing and data dissemination protocols. Firstly, characteristics of MSNs which lead to the exposure of patterns of interaction among mobile users are examined. Secondly, properties of human mobility models are discussed and recently proposed mobility models are surveyed. Thirdly, community detection and evolution analysis algorithms are investigated. Then, a comparative review of state-of-the-art routing and data dissemination algorithms for MSNs is presented, with special attention paid to critical issues like context-awareness and user selfishness. Based on the literature review, some important open issues are finally discussed.

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