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Improving data forwarding in mobile social networks with infrastructure support: a space-crossing community approach

Li, Zhong, Wang, Cheng, Yang, Siqian, Jiang, Changjun and Stojmenovic, Ivan 2014, Improving data forwarding in mobile social networks with infrastructure support: a space-crossing community approach, in IEEE INFOCOM 2014 : Proceedings of the IEEE Conference on Computer Communications, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 1941-1949, doi: 10.1109/INFOCOM.2014.6848134.

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Title Improving data forwarding in mobile social networks with infrastructure support: a space-crossing community approach
Author(s) Li, Zhong
Wang, Cheng
Yang, Siqian
Jiang, Changjun
Stojmenovic, Ivan
Conference name IEEE Conference on Computer Communications. Conference (2014 : Toronto, Ontario)
Conference location Toronto, Ontario
Conference dates 27 Apr. - 02 May. 2014
Title of proceedings IEEE INFOCOM 2014 : Proceedings of the IEEE Conference on Computer Communications
Editor(s) [Unknown]
Publication date 2014
Conference series IEEE Conference on Computer Communications
Start page 1941
End page 1949
Total pages 9
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Summary In this paper, we study two tightly coupled issues: space-crossing community detection and its influence on data forwarding in Mobile Social Networks (MSNs) by taking the hybrid underlying networks with infrastructure support into consideration. The hybrid underlying network is composed of large numbers of mobile users and a small portion of Access Points (APs). Because APs can facilitate the communication among long-distance nodes, the concept of physical proximity community can be extended to be one across the geographical space. In this work, we first investigate a space-crossing community detection method for MSNs. Based on the detection results, we design a novel data forwarding algorithm SAAS (Social Attraction and AP Spreading), and show how to exploit the space-crossing communities to improve the data forwarding efficiency. We evaluate our SAAS algorithm on real-life data from MIT Reality Mining and University of Illinois Movement (UIM). Results show that space-crossing community plays a positive role in data forwarding in MSNs in terms of delivery ratio and delay. Based on this new type of community, SAAS achieves a better performance than existing social community-based data forwarding algorithms in practice, including Bubble Rap and Nguyen's Routing algorithms. © 2014 IEEE.
ISBN 9781479933600
ISSN 0743-166X
Language eng
DOI 10.1109/INFOCOM.2014.6848134
Field of Research 080502 Mobile Technologies
089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30073086

Document type: Conference Paper
Collection: School of Information Technology
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