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Scalable Grouping Based on Neuro-Fuzzy Clustering for P2P Networks

机译:基于神经模糊聚类的P2P网络可扩展分组

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摘要

In this paper, we present a scalable grouping based on the proposed neuro-fuzzy clustering (NFC) which is a combination of fuzzy clustering and neuro-fuzzy classification for P2P networks. Fuzzy clustering is used to construct the classifier structure for the grouping technique and neuro-fuzzy algorithm is used to adjust the fuzzy system in creating the accurate classifier. After the adjustment, each peer is processed in multi-ring algorithm using the fuzzy membership function of NFC. The scalable peer grouping contributes on load distribution by forwarding incoming request to the least loaded peer. Performance result showed that the proposed scalable peer grouping classifies more peers in a group for availability of resources and accurately classifies peer group.
机译:在本文中,我们提出了一种基于提议的神经模糊聚类(NFC)的可扩展分组,它是对P2P网络进行模糊聚类和神经模糊分类的组合。模糊聚类用于构造分组技术的分类器结构,神经模糊算法用于调整模糊系统以创建准确的分类器。调整后,使用NFC的模糊隶属函数,以多环算法处理每个对等体。可伸缩对等方分组通过将传入请求转发到负载最小的对等方来促进负载分配。性能结果表明,所提出的可扩展对等体分组对组中的更多对等体进行分类以获取资源,并准确地对等体组进行分类。

著录项

  • 来源
  • 会议地点 Uppsala(SE);Uppsala(SE)
  • 作者单位

    School of Electronic and Information Engineering, Kunsan National University 68 Miryong-dong, Kunsan, Chonbuk 573-701, South Korea;

    rnSchool of Electronic and Information Engineering, Kunsan National University 68 Miryong-dong, Kunsan, Chonbuk 573-701, South Korea;

    rnSchool of Electronic and Information Engineering, Kunsan National University 68 Miryong-dong, Kunsan, Chonbuk 573-701, South Korea;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工智能理论;
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