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A self-organized system improving inner topology for data sharing efficiency

机译:一种自组织系统,改善了数据分享效率的内拓

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In this paper, we present a promising multi-agent self-organizing ant inspired approach applied to unstructured peer-to-peer networks (no global or distributed map). This work shows enhancement resulting from the ability of the system to self-organize, and contribute to understand its intrinsic properties. For the selected self-improving approach, we show how the process of information search builds an inner topology deeply correlated to the network topology. Consequently, the efficiency of search algorithms is considerably enhanced, particularly for rare data. We show how ant inspired algorithms can build well adapted scale-free-like topologies for search in unstructured peer-to-peer network, and show further improvements considering the initial topology of the network.
机译:在本文中,我们提出了一个有前途的多代理自组织蚂蚁启发方法,适用于非结构化的点对点网络(没有全局或分布式地图)。这项工作显示了系统因系统自组织的能力而导致的增强,并有助于了解其内在属性。对于所选的自我提高方法,我们展示了信息搜索过程如何构建与网络拓扑相关的密切相关的内部拓扑。因此,搜索算法的效率显着增强,特别是对于罕见数据。我们展示Ant启发算法如何在非结构化的点对点网络中搜索很好的自由级别拓扑,并显示了考虑网络初始拓扑的进一步改进。

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