An advertisement-based peer-to-peer search algorithm

  • Authors:
  • Jun Wang;Peng Gu;Hailong Cai

  • Affiliations:
  • 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

  • Venue:
  • Journal of Parallel and Distributed Computing
  • Year:
  • 2009

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Abstract

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. In 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.