TCR: a trustworthy and churn-resilient academic distribution and retrieval system in P2P networks

Yung-Ting Chuang*, Feng Wei Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

As the number of people using the internet has surged over the past few years, more and more people are choosing to share and retrieve information online. There are several decentralized retrieval applications that provide file-sharing platforms for exactly this purpose. However, these applications cannot guarantee churn resilience, trustworthiness, or low cost of retrieval. Therefore, in this paper, we present a system called trustworthy and churn-resilient academic distribution and retrieval system in P2P networks, or TCR, which: (1) ensures that information will not be centralized by central network administrators; (2) utilizes LSH to classify nodes with similar research topics into a local subnetwork, and applies routing algorithms with trust score equations to determine the next trustworthy node to forward the message, thus ensuring each node can accurately and efficiently find its trustworthy nodes within only a few hops; (3) provides a trustworthy management system that itself deals in trustworthiness, ensuring that even when there is a large proportion of malicious nodes, the system can still detect and punish misbehaving nodes; (4) guarantees that nodes can still retrieve the desired files even when in high-churn networks. We finally demonstrate that our TCR entails low message costs, provides high match rates, detects malicious nodes, and ensures churn resilience and search efficiency when compared to other P2P retrieval systems.

Original languageEnglish
Pages (from-to)7107-7139
Number of pages33
JournalJournal of Supercomputing
Volume76
Issue number9
DOIs
StatePublished - Sep 2020

Keywords

  • Distributed search and retrieval
  • Network churn
  • Peer-to-peer
  • Trustworthy management

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