Improving the Search Mechanism for Unstructured Peer-to-Peer Networks Using the Statistical Matrix Form

Chia Hung Lin, Jing Jia Zseng, Sun Yuan Hsieh

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In a traditional file search mechanism, such as flooding, a peer broadcasts a query to its neighbors through an unstructured peer-to-peer (P2P) network until the time-to-live decreases to zero. A major disadvantage of flooding is that, in a large-scale network, this blind-choice strategy usually incurs an enormous traffic overhead. In this paper, we propose a method, called the statistical matrix form (SMF), which improves the flooding mechanism by selecting neighbors according to their capabilities. The SMF measures the following peer characteristics: 1) the number of shared files; 2) the content quality; 3) the query service; and 4) the transmission distance between neighbors. Based on these measurements, appropriate peers can be selected, thereby reducing the traffic overhead significantly. Our experimental results demonstrate that the SMF is effective and efficient. For example, compared with the flooding search mechanism in dynamic unstructured P2P networks, the SMF reduces the traffic overhead by more than 80%. Moreover, it achieves a good success rate and shorter response times.

Original languageEnglish
Article number7122855
Pages (from-to)926-941
Number of pages16
JournalIEEE Access
Volume3
DOIs
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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