Transient Community Detection and Its Application to Data Forwarding in Delay Tolerant Networks

Xiaomei Zhang, Guohong Cao

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Community detection has received considerable attention because of its applications to many practical problems in mobile networks. However, when considering temporal information associated with a community (i.e., transient community), most existing community detection methods fail due to their aggregation of contact information into a single weighted or unweighted network. In this paper, we propose a contact-burst-based clustering method to detect transient communities by exploiting pairwise contact processes. In this method, we formulate each pairwise contact process as a regular appearance of contact bursts, during which most contacts between the pair of nodes happen. Based on this formulation, we detect transient communities by clustering the pairs of nodes with similar contact bursts. Since it is difficult to collect global contact information at individual nodes, we further propose a distributed method to detect transient communities. In addition to transient community detection, we also propose a new data forwarding strategy for delay tolerant networks, in which transient communities serve as the data forwarding unit. Evaluation results show that our strategy can achieve a much higher data delivery ratio than traditional community-based strategies with comparable network overhead.

Original languageEnglish (US)
Article number7945481
Pages (from-to)2829-2843
Number of pages15
JournalIEEE/ACM Transactions on Networking
Volume25
Issue number5
DOIs
StatePublished - Oct 2017

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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