Finding self-similarities in opportunistic people networks

Ling Jyh Chen*, Yung Chih Chen, Tony Sun, Paruvelli Sreedevi, Kuan Ta Chen, Chen Hung Yu, Hao Hua Chu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)


Opportunistic network is a type of Delay Tolerant Networks (DTN) where network communication opportunities appear opportunistic. In this study, we investigate opportunistic network scenarios based on public network traces, and our contributions are the following: First, we identify the censorship issue in network traces that usually leads to strongly skewed distribution of the measurements. Based on this knowledge, we then apply the Kaplan-Meier Estimator to calculate the survivorship of network measurements, which is used in designing our proposed censorship removal algorithm (CRA) that is used to recover censored data. Second, we perform a rich set of analysis illustrating that UCSD and Dartmouth network traces show strong self-similarity, and can be modeled as such. Third, we pointed out the importance of these newly revealed characteristics in future development and evaluation of opportunistic networks.

Original languageEnglish
Title of host publicationProceedings - IEEE INFOCOM 2007
Subtitle of host publication26th IEEE International Conference on Computer Communications
Number of pages5
Publication statusPublished - 2007
Externally publishedYes
EventIEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications - Anchorage, AK, United States
Duration: 2007 May 62007 May 12

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


OtherIEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications
Country/TerritoryUnited States
CityAnchorage, AK

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


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