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

研究成果: 書貢獻/報告類型會議貢獻

18 引文 (Scopus)

摘要

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.

原文英語
主出版物標題Proceedings - IEEE INFOCOM 2007
主出版物子標題26th IEEE International Conference on Computer Communications
頁面2286-2290
頁數5
DOIs
出版狀態已發佈 - 2007 九月 4
事件IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications - Anchorage, AK, 美国
持續時間: 2007 五月 62007 五月 12

出版系列

名字Proceedings - IEEE INFOCOM
ISSN(列印)0743-166X

其他

其他IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications
國家美国
城市Anchorage, AK
期間07/5/607/5/12

指紋

Delay tolerant networks
Telecommunication networks

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

引用此文

Chen, L. J., Chen, Y. C., Sun, T., Sreedevi, P., Chen, K. T., Yu, C. H., & Chu, H. H. (2007). Finding self-similarities in opportunistic people networks. 於 Proceedings - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications (頁 2286-2290). [4215848] (Proceedings - IEEE INFOCOM). https://doi.org/10.1109/INFCOM.2007.266

Finding self-similarities in opportunistic people networks. / Chen, Ling Jyh; Chen, Yung Chih; Sun, Tony; Sreedevi, Paruvelli; Chen, Kuan Ta; Yu, Chen Hung; Chu, Hao Hua.

Proceedings - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications. 2007. p. 2286-2290 4215848 (Proceedings - IEEE INFOCOM).

研究成果: 書貢獻/報告類型會議貢獻

Chen, LJ, Chen, YC, Sun, T, Sreedevi, P, Chen, KT, Yu, CH & Chu, HH 2007, Finding self-similarities in opportunistic people networks. 於 Proceedings - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications., 4215848, Proceedings - IEEE INFOCOM, 頁 2286-2290, IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications, Anchorage, AK, 美国, 07/5/6. https://doi.org/10.1109/INFCOM.2007.266
Chen LJ, Chen YC, Sun T, Sreedevi P, Chen KT, Yu CH 等. Finding self-similarities in opportunistic people networks. 於 Proceedings - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications. 2007. p. 2286-2290. 4215848. (Proceedings - IEEE INFOCOM). https://doi.org/10.1109/INFCOM.2007.266
Chen, Ling Jyh ; Chen, Yung Chih ; Sun, Tony ; Sreedevi, Paruvelli ; Chen, Kuan Ta ; Yu, Chen Hung ; Chu, Hao Hua. / Finding self-similarities in opportunistic people networks. Proceedings - IEEE INFOCOM 2007: 26th IEEE International Conference on Computer Communications. 2007. 頁 2286-2290 (Proceedings - IEEE INFOCOM).
@inproceedings{3ddec4e501604ca6a6237c09745e5994,
title = "Finding self-similarities in opportunistic people networks",
abstract = "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.",
author = "Chen, {Ling Jyh} and Chen, {Yung Chih} and Tony Sun and Paruvelli Sreedevi and Chen, {Kuan Ta} and Yu, {Chen Hung} and Chu, {Hao Hua}",
year = "2007",
month = "9",
day = "4",
doi = "10.1109/INFCOM.2007.266",
language = "English",
isbn = "1424410479",
series = "Proceedings - IEEE INFOCOM",
pages = "2286--2290",
booktitle = "Proceedings - IEEE INFOCOM 2007",

}

TY - GEN

T1 - Finding self-similarities in opportunistic people networks

AU - Chen, Ling Jyh

AU - Chen, Yung Chih

AU - Sun, Tony

AU - Sreedevi, Paruvelli

AU - Chen, Kuan Ta

AU - Yu, Chen Hung

AU - Chu, Hao Hua

PY - 2007/9/4

Y1 - 2007/9/4

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=34548305167&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548305167&partnerID=8YFLogxK

U2 - 10.1109/INFCOM.2007.266

DO - 10.1109/INFCOM.2007.266

M3 - Conference contribution

AN - SCOPUS:34548305167

SN - 1424410479

SN - 9781424410477

T3 - Proceedings - IEEE INFOCOM

SP - 2286

EP - 2290

BT - Proceedings - IEEE INFOCOM 2007

ER -