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Enhanced Resource Discovery Mechanisms for Unstructured Peer-to-Peer Network Environments

机译:针对非结构化点对点网络环境的增强资源发现机制

摘要

This study explores novel methods for resource discovery in unstructured peerto-peer (P2P) networks. The objective of this study is to develop a lightweight resource discovery mechanism suitable to be used in unstructured P2P networks.udResource discovery techniques are examined and implemented in a simulator with high scalability in order to imitate real-life P2P environments. Simulated topologyudgenerator models are reviewed and compared, the most suitable topology generator model is then chosen to test the novel resource discovery techniques.udResource discovery techniques in unstructured P2P networks usually rely on forwarding as many query messages as possible onto the network. Even though this approach was able to return many resources, the flooding of the network with query messages have an adverse effect on the network. Flooding the network has undesirable consequences such as degenerative performance of the network, waste of network resources, and network downtime. This study has developed alpha multipliers, a method of controlling query message forwarding to deal with the flooding effect of most resource discovery techniques in unstructured P2P networks.udThe combination of alpha multipliers and breadth-first search (BFS), ↵-BFS, was able to avoid the flooding effect that usually occurs with BFS. The ↵-BFS technique also increases the combined query efficiency compared to the original BFS.udAside from improving a uninformed search technique such as the BFS, this study also examines the network communication cost of several informed resource discovery techniques. Several issues that arise in informed resource discovery techniques, such as false positive errors, and high network communication costs for queries to update search results are discussed. This detailed analysis forms the basis of a lightweight resource discovery mechanism (LBRDM) that reduces the network communication cost by reducing the number of backward updates inside the network when utilising the blackboard resource discovery mechanism (BRDM). Simulations of BRDM and LBRDM show that the lightweight version can also return an almost identical combined query efficiency than the BRDM.udThe solution to control query message forwarding in ↵-BFS, and the removal of unnecessary exchange of information in LBRDM open a new perspective on simplifying resource discovery techniques. These approaches can be implementedudon other techniques to improve the performance of resource discovery.
机译:这项研究探索了非结构化对等(P2P)网络中资源发现的新方法。这项研究的目的是开发一种适用于非结构化P2P网络的轻量级资源发现机制。 ud资源发现技术已在具有高度可扩展性的模拟器中进行了检查和实现,以模仿现实生活中的P2P环境。审查并比较了模拟的拓扑算子模型,然后选择最合适的拓扑生成器模型来测试新颖的资源发现技术。 ud非结构化P2P网络中的资源发现技术通常依赖于将尽可能多的查询消息转发到网络上。即使这种方法能够返回许多资源,查询消息对网络的泛滥也对网络造成不利影响。泛洪网络会带来不良后果,例如网络性能下降,网络资源浪费和网络停机。这项研究开发了alpha乘法器,这是一种控制查询消息转发以应对非结构化P2P网络中大多数资源发现技术的泛洪影响的方法。 udalpha乘法器和广度优先搜索(BFS)↵-BFS的组合是能够避免BFS通常会发生的洪泛效应。与原始BFS相比,-BFS技术还提高了组合查询效率。 ud除了改进了诸如BFS之类的无信息搜索技术之外,本研究还研究了几种知情资源发现技术的网络通信成本。讨论了在明智的资源发现技术中出现的一些问题,例如误报错误和用于查询以更新搜索结果的高网络通信成本。此详细分析构成了轻量级资源发现机制(LBRDM)的基础,该轻量级资源发现机制通过减少使用黑板资源发现机制(BRDM)时网络内部的反向更新次数来降低网络通信成本。对BRDM和LBRDM的仿真表明,轻量级版本还可以返回与BRDM几乎相同的组合查询效率。 ud在↵-BFS中控制查询消息转发的解决方案以及在LBRDM中消除不必要的信息交换的方式打开了一个新的视角关于简化资源发现技术。可以在其他技术上实施这些方法以提高资源发现的性能。

著录项

  • 作者

    Jamal Azrul Amri bin;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

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