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Information Dissemination Network for Dynamic Target Location Pursuit

机译:动态目标位置追求信息传播网络

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We study a network structure for efficient information dissemination that leverages location-based real-time applications operating in a distributed system. Gossip-based information dissemination is a promising method for a large-scale system to keep nodes in the network quickly updated with new information. The information dissemination efficiency depends strongly on the underlying network structure, so it is important to analyze how the network structure is optimized to achieve agile information dissemination, especially for time-sensitive applications, e.g., for dynamic pursuit of a moving target that requires frequent information updating. To this end, we construct a continuous-space network model extended from Kleinberg's small-world model so that it is applicable to location-based services. Analytical and simulation-based study shows that excellent information dissemination efficiency is achieved when the shortcuts overlaying a mesh network are created nearly uniformly to nodes at all distance scales. We apply our model to the dynamic pursuit problem where a pursuer searches for a moving target. Monte-Carlo simulation shows that the network with well-structured shortcuts surpasses other types of networks in finding a moving target because the pursuer can steadily approach the target regardless of its location, and the network structure greatly influences the dynamic search ability in distributed systems.
机译:我们研究了一个网络结构,以实现高效信息传播,利用在分布式系统中运行的基于位置的实时应用。基于Gossip的信息传播是大规模系统的有希望的方法,以便在网络中快速更新网络中的节点。信息传播效率依赖于潜在的网络结构,因此分析网络结构的优化方式是为了实现敏捷信息传播,特别是对于时间敏感的应用,例如,用于动态追求需要频繁信息的移动目标更新。为此,我们构建了从Kleinberg的小世界模型扩展的连续空间网络模型,以便适用于基于位置的服务。基于分析和仿真的研究表明,当覆盖网状网络的快捷方式几乎均匀地到所有距离尺度的节点时,实现了出色的信息传播效率。我们将模型应用于动态追求问题,其中追求者搜索移动目标。 Monte-Carlo仿真表明,具有结构良好的快捷方式的网络超越了其他类型的网络来寻找移动目标,因为追求者可以稳定地接近目标,无论其位置如何,网络结构都会大大影响分布式系统中的动态搜索能力。

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