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首页> 外文会议>4th ACM workshop on challenged networks 2009 >Quantifying Content Consistency Improvements Through Opportunistic Contacts
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Quantifying Content Consistency Improvements Through Opportunistic Contacts

机译：通过机会性联系量化内容一致性改进

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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.
机译：移动用户之间的联系为补充基于基础架构的机制的数据更新提供了机会。尽管这种机会共享的好处是直观的，但要量化它们带来的容量增加却是具有挑战性的，因为联系率和联系图都取决于用户所属的社交网络的结构。此外，社交连接不仅影响用户的兴趣，即他们拥有的内容，而且还影响他们与他人共享数据的意愿。所有这些因素都可能对通过机会性联系而实现的能力提升产生重大影响。本文的主要贡献在于开发了一种易于处理的模型，用于估算内容更新系统中的此类收益，其中，内容来自服务器上的多个通道，每个通道中的信息块均以一定速率更新，并且用户的联系方式有所不同，兴趣和共享内容的意愿，例如仅向其自己的社交网络的成员共享。我们建立了可以通过解决凸优化问题来获得通过机会共享来提高内容一致性的可用附加容量。使用反映不同社会环境中的联系图的迹线评估生成的最佳策略，并将其与启发式策略进行比较。该评估证明了通过机会共享可以实现的能力提升，以及对基础社交网络结构的这些提升的影响。

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