Exploiting Social Relationship for Opportunistic Routing in Mobile Social Networks

Zhenxiang GAO; Yan SHI; Shanzhi CHEN; Qihan LI

doi:10.1587/transcom.E98.B.2040

Exploiting Social Relationship for Opportunistic Routing in Mobile Social Networks

Zhenxiang GAO, Yan SHI, Shanzhi CHEN, Qihan LI

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Routing is a challenging issue in mobile social networks (MSNs) because of time-varying links and intermittent connectivity. In order to enable nodes to make right decisions while forwarding messages, exploiting social relationship has become an important method for designing efficient routing protocols in MSNs. In this paper, we first use the temporal evolution graph model to accurately capture the dynamic topology of the MSN. Based on the model, we introduce the social relationship metric for detecting the quality of human social relationship from contact history records. Utilizing this metric, we propose social relationship based betweenness centrality metric to identify influential nodes to ensure messages forwarded by the nodes with stronger social relationship and higher likelihood of contacting other nodes. Then, we present SRBet, a novel social-based forwarding algorithm, which utilizes the aforementioned metric to enhance routing performance. Simulations have been conducted on two real world data sets and results demonstrate that the proposed forwarding algorithm achieves better performances than the existing algorithms.

Publication: IEICE TRANSACTIONS on Communications Vol.E98-B No.10 pp.2040-2048

Publication Date: 2015/10/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E98.B.2040

Type of Manuscript: PAPER

Category: Network

Authors

Zhenxiang GAO
  Beijing University of Posts and Telecommunications (BUPT)
Yan SHI
  Beijing University of Posts and Telecommunications (BUPT)
Shanzhi CHEN
  China Academy of Telecommunications Technology (CATT) and Datang Telecom Technology & Industry Group
Qihan LI
  University of Southern California

Keyword

mobile social networks, opportunistic routing, social relationship exploration, social relationship based betweenness centrality

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Zhenxiang GAO, Yan SHI, Shanzhi CHEN, Qihan LI, "Exploiting Social Relationship for Opportunistic Routing in Mobile Social Networks" in IEICE TRANSACTIONS on Communications, vol. E98-B, no. 10, pp. 2040-2048, October 2015, doi: 10.1587/transcom.E98.B.2040.
Abstract: Routing is a challenging issue in mobile social networks (MSNs) because of time-varying links and intermittent connectivity. In order to enable nodes to make right decisions while forwarding messages, exploiting social relationship has become an important method for designing efficient routing protocols in MSNs. In this paper, we first use the temporal evolution graph model to accurately capture the dynamic topology of the MSN. Based on the model, we introduce the social relationship metric for detecting the quality of human social relationship from contact history records. Utilizing this metric, we propose social relationship based betweenness centrality metric to identify influential nodes to ensure messages forwarded by the nodes with stronger social relationship and higher likelihood of contacting other nodes. Then, we present SRBet, a novel social-based forwarding algorithm, which utilizes the aforementioned metric to enhance routing performance. Simulations have been conducted on two real world data sets and results demonstrate that the proposed forwarding algorithm achieves better performances than the existing algorithms.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E98.B.2040/_p

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@ARTICLE{e98-b_10_2040,
author={Zhenxiang GAO, Yan SHI, Shanzhi CHEN, Qihan LI, },
journal={IEICE TRANSACTIONS on Communications},
title={Exploiting Social Relationship for Opportunistic Routing in Mobile Social Networks},
year={2015},
volume={E98-B},
number={10},
pages={2040-2048},
abstract={Routing is a challenging issue in mobile social networks (MSNs) because of time-varying links and intermittent connectivity. In order to enable nodes to make right decisions while forwarding messages, exploiting social relationship has become an important method for designing efficient routing protocols in MSNs. In this paper, we first use the temporal evolution graph model to accurately capture the dynamic topology of the MSN. Based on the model, we introduce the social relationship metric for detecting the quality of human social relationship from contact history records. Utilizing this metric, we propose social relationship based betweenness centrality metric to identify influential nodes to ensure messages forwarded by the nodes with stronger social relationship and higher likelihood of contacting other nodes. Then, we present SRBet, a novel social-based forwarding algorithm, which utilizes the aforementioned metric to enhance routing performance. Simulations have been conducted on two real world data sets and results demonstrate that the proposed forwarding algorithm achieves better performances than the existing algorithms.},
keywords={},
doi={10.1587/transcom.E98.B.2040},
ISSN={1745-1345},
month={October},}

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TY - JOUR
TI - Exploiting Social Relationship for Opportunistic Routing in Mobile Social Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 2040
EP - 2048
AU - Zhenxiang GAO
AU - Yan SHI
AU - Shanzhi CHEN
AU - Qihan LI
PY - 2015
DO - 10.1587/transcom.E98.B.2040
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E98-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2015
AB - Routing is a challenging issue in mobile social networks (MSNs) because of time-varying links and intermittent connectivity. In order to enable nodes to make right decisions while forwarding messages, exploiting social relationship has become an important method for designing efficient routing protocols in MSNs. In this paper, we first use the temporal evolution graph model to accurately capture the dynamic topology of the MSN. Based on the model, we introduce the social relationship metric for detecting the quality of human social relationship from contact history records. Utilizing this metric, we propose social relationship based betweenness centrality metric to identify influential nodes to ensure messages forwarded by the nodes with stronger social relationship and higher likelihood of contacting other nodes. Then, we present SRBet, a novel social-based forwarding algorithm, which utilizes the aforementioned metric to enhance routing performance. Simulations have been conducted on two real world data sets and results demonstrate that the proposed forwarding algorithm achieves better performances than the existing algorithms.
ER -