2009 · 13 citations · 15 references
ComputingCommunicationComputer SystemsDistributed SystemsMobile ComputingMobile SystemsInformation SharingMobile NetworksSocial Network AnalysisCapacity OptimizationConsistencyContent DistributionInformation Diffusion ModelsMultiple-access ChannelsNetwork CapacityOpportunistic NetworkingSocial Connectivity
Contacts between mobile users provide opportunities for data updates that supplement infrastructure-based mechanisms. While the benefits of such opportunistic sharing are intuitive, quantifying the capacity increase they give rise to is challenging because both contact rates and contact graphs depend on the structure of the social networks users belong to. Furthermore, social connectivity influences not only users' interests, i.e., the content they own, but also their willingness to share data with others. All these factors can have a significant effect on the capacity gains achievable through opportunistic contacts. This paper's main contribution is in developing a tractable model for estimating such gains in a content update system, where content originates from a server along multiple channels, with blocks of information in each channel updated at a certain rate, and users differ in their contact graphs, interests, and willingness to share content, e.g., only to the members of their own social networks. We establish that the added capacity available to improve content consistency through opportunistic sharing can be obtained by solving a convex optimization problem. The resulting optimal policy is evaluated using traces reflecting contact graphs in different social settings and compared to heuristic policies. The evaluation demonstrates the capacity gains achievable through opportunistic sharing, and the impact on those gains of the structure of the underlying social network.
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