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An Autonomy Oriented Computing (AOC) Approach to Distributed Network Community Mining

机译:面向自治的计算(AOC)方法用于分布式网络社区挖掘

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A network community is a special sub-network that contains a group of nodes sharing similar linked patterns. A distributed network community mining problem (D-NCMP) is concerned with finding all such communities from a distributed network. A variety of applications in WWW and ad-hoc networks such as P2P and sensor networks can be formulated into DNCMPs, in which both resources and controls are distributed and/or decentralized. The problem is difficult for some existing methods to deal with because of the fact that their required global topological representations of distributed networks are hard to obtain. In this paper, we present an autonomy oriented computing (AOC) approach [15], in which the nodes and links of a distributed network are distributed among a group of autonomous agents that collectively find global communities hidden in the network. In doing so, the agents maintain only their respective local views and update them through a proposed self-organization process. The effectiveness of the AOC based approach has been validated using network examples.
机译:网络社区是一个特殊的子网,其中包含一组共享相似链接模式的节点。分布式网络社区挖掘问题(D-NCMP)与从分布式网络中查找所有此类社区有关。可以将WWCMP和ad-hoc网络(例如P2P和传感器网络)中的各种应用程序表述为DNCMP,在其中分发和/或分散资源和控制权。对于某些现有方法而言,由于很难获得分布式网络所需的全局拓扑表示,因此该问题很难解决。在本文中,我们提出了一种面向自治的计算(AOC)方法[15],其中分布式网络的节点和链接分布在一组自治代理之间,这些代理共同找到隐藏在网络中的全局社区。这样,代理仅维护其各自的本地视图,并通过提议的自组织过程对其进行更新。使用网络示例已验证了基于AOC的方法的有效性。

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    《》|2007年|151-160|共10页
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    Yang; Bo; Liu; Jiming;

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