ASAP: An Advertisement-based Search Algorithm for Unstructured Peer-to-peer Systems

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

  • Affiliations:
  • University of Central Florida, USA;University of Central Florida, USA;Google Inc., USA

  • Venue:
  • ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
  • Year:
  • 2007

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Abstract

Most of existing search algorithms for unstructured peer-to-peer (P2P) systems share one common approach: the requesting node sends out a 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 easily overloaded when the query traffic becomes intensive or bursty. In this paper, we present a novel content-pushing, Advertisement-based Search Algorithm for unstructured P2P systems called ASAP. An advertisement (ad in brief) 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 store 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 1 at a low level with small variances. In addition, ASAP works well under node churn.