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Piggyback Game: Efficient Event Stream Dissemination in Online Social Network Systems

机译:搭载游戏:在线社交网络系统中的有效事件流传播

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摘要

Event stream dissemination dominates the workloads in large-scale Online Social Network (OSN) systems. Based on the de facto per-user view data storage, event stream dissemination raises a large amount of inter-server traffic due to the complex interconnection among OSN users. The state-of-the-art schemes mainly explore the structure features of social graphs to reduce the inter-server communications for event stream dissemination. Different sub-graph structures are exploited for achieving approximated optimal solutions. However, such schemes incur prohibitively high cost of either computation or communication. In this work, we follow a different design philosophy by using a game theoretic approach, which decomposes the highly complex graph computation problem into rational decision making of every individual social link. Specifically, we propose a novel social piggyback game to achieve a more efficient solution. We mathematically prove the existence of the Nash Equilibrium of the social piggyback game. Moreover, we propose an efficient best response dynamic algorithm to achieve the Nash Equilibrium, which quickly converges in a small number of iterations for large-scale OSNs. We further show that the communication cost of this design achieves a 1.5-approximation of the theoretical social optimum. We conduct comprehensive experiments using large-scale real-world traces from popular OSN systems as well as implement a prototype system to evaluate the performance of this design. Results show that the social piggyback game achieves a significant 302x improvement in system efficiency compared to existing schemes.
机译:事件流的传播控制着大型在线社交网络(OSN)系统中的工作负载。基于事实上的每用户视图数据存储,由于OSN用户之间的复杂互连,事件流的传播会增加大量的服务器间流量。最新的方案主要探索社交图的结构特征,以减少用于事件流分发的服务器间通信。利用不同的子图结构来获得近似的最佳解。但是,这样的方案导致计算或通信的成本过高。在这项工作中,我们通过使用博弈论方法遵循不同的设计理念,该方法将高度复杂的图形计算问题分解为每个社交环节的理性决策。具体来说,我们提出了一种新颖的社交游戏,以实现更有效的解决方案。我们从数学上证明了社交背game游戏的纳什均衡的存在。此外,我们提出了一种有效的最佳响应动态算法来实现Nash均衡,对于大型OSN,Nash均衡可以快速收敛于少量迭代中。我们进一步表明,这种设计的通讯成本达到了理论社会最优值的1.5倍。我们使用来自流行的OSN系统的大规模真实世界的痕迹进行全面的实验,并实施原型系统来评估该设计的性能。结果表明,与现有方案相比,社交搭载游戏在系统效率方面实现了302倍的显着提高。

著录项

  • 来源
  • 作者

    Zhang Fan; Chen Hanhua; Jin Hai;

  • 作者单位

    Huazhong Univ Sci & Technol, Big Data Technol & Syst Lab, Cluster & Grid Comp Lab, Serv Comp Technol & Syst Lab,Sch Comp Sci & Techn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Big Data Technol & Syst Lab, Cluster & Grid Comp Lab, Serv Comp Technol & Syst Lab,Sch Comp Sci & Techn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Big Data Technol & Syst Lab, Cluster & Grid Comp Lab, Serv Comp Technol & Syst Lab,Sch Comp Sci & Techn, Wuhan 430074, Hubei, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Online social network; event stream dissemination; piggyback;

    机译:在线社交网络;事件流传播;带;

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