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An advertisement-based peer-to-peer search algorithm

机译:一种基于广告的对等搜索算法

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摘要

Most of the existing search algorithms for unstructured peer-to-peer (P2P) systems share one common approach: the requesting node sends out a keyword search query and the query message is repeatedly routed and forwarded to other peers in the overlay network. Due to multiple hops involved in query forwarding, the search may result in a long delay before it is answered. Furthermore, some incapable nodes may be overloaded when the query traffic becomes intensive or bursty.rnIn this paper, we present a novel content-pushing, Advertisement-based Search Algorithm for unstructured Peer-to-peer systems (ASAP). An advertisement (ad) is a synopsis of contents a peer tends to share, and appropriately distributed and selectively cached by other peers in the system. In ASAP, nodes proactively advertise their contents by delivering ads, and selectively storing interesting ads received from other peers. Upon a request, a node can locate the destination nodes by looking up its local ads repository, and thus obtain a one-hop search latency with modest search cost. Comprehensive experimental results show that, compared with traditional query-based search algorithms, ASAP achieves much better search efficiency, and maintains system load at a low level with small variations. In addition, ASAP works well under node churn.
机译:非结构化对等(P2P)系统的大多数现有搜索算法共享一种通用方法:请求节点发出关键字搜索查询,并且查询消息被重复路由并转发到覆盖网络中的其他对等节点。由于查询转发涉及多个跃点,因此搜索可能会导致很长的延迟才能被回答。此外,当查询流量变得密集或突发时,一些无法运行的节点可能会过载。本文针对非结构化对等系统(ASAP),提出了一种基于内容推送,基于广告的新颖搜索算法。广告(ad)是对等体倾向于共享的内容的提要,并由系统中的其他对等体适当地分发和选择性地缓存。在ASAP中,节点通过投放广告并有选择地存储从其他对等方收到的有趣广告来主动地发布其内容。根据请求,节点可以通过查找其本地广告存储库来定位目标节点,从而以适度的搜索成本获得单跳搜索延迟。综合的实验结果表明,与传统的基于查询的搜索算法相比,ASAP实现了更好的搜索效率,并且将系统负载保持在较低的水平上且变化很小。另外,ASAP在节点搅动下也能很好地工作。

著录项

  • 来源
    《Journal of Parallel and Distributed Computing》 |2009年第7期|638-651|共14页
  • 作者

    Jun Wang; Peng Gu; Hailong Cai;

  • 作者单位

    School of Electrical Engineering and Computer Science. University of Central Florida, 4000 Central Florida Blvd., Orlando, FL 32816-2450, United States;

    School of Electrical Engineering and Computer Science. University of Central Florida, 4000 Central Florida Blvd., Orlando, FL 32816-2450, United States;

    Google Inc., 1600 Amphitheatre Pkwy, US-MTV-42 Room 229C, Mountain View, CA 94043, United States;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    peer-to-peer; unstructured; advertisement; search algorithm;

    机译:点对点;非结构化广告;搜索算法;

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