Cellular traffic offloading through community-based opportunistic dissemination

With the growing demands for accessing mobile applications, the cellular network is currently overloaded. Recent work has proposed to exploit opportunistic networks to offload cellular traffic for mobile content dissemination services. The basic idea is to distribute the content object to only part of subscribers (called initial sources) via the cellular network, and allow initial sources to propagate the object through opportunistic communications. The preliminary study focused on selecting a given number of initial sources only based on the probability of encounters between users. However, without consideration of social relationships between users, the selected sources might not be able to propagate the object across different social communities opportunistically. In addition, there exists a dilemma of selecting a suitable number of sources to take the trade-off between offloading cellular traffic and reducing the latency. Hence, in this paper, we propose community-based opportunistic dissemination, which automatically selects a sufficient number of initial sources to propagate the object across disjointed communities in parallel. The trace-based evaluation shows that, compared to encounter-based dissemination, our community-based scheme improves the amount of offloaded cellular traffic up to 29%. In addition, users experience a significantly shorter latency.

[1]  Pan Hui,et al.  Pocket Switched Networks: Real-world mobility and its consequences for opportunistic forwarding , 2005 .

[2]  Vikram Srinivasan,et al.  PeopleNet: engineering a wireless virtual social network , 2005, MobiCom '05.

[3]  Mads Haahr,et al.  Social network analysis for routing in disconnected delay-tolerant MANETs , 2007, MobiHoc '07.

[4]  Alex Pentland,et al.  Reality mining: sensing complex social systems , 2006, Personal and Ubiquitous Computing.

[5]  Aravind Srinivasan,et al.  Cellular traffic offloading through opportunistic communications: a case study , 2010, CHANTS '10.

[6]  Kang-Won Lee,et al.  RelayCast: Scalable multicast routing in Delay Tolerant Networks , 2008, 2008 IEEE International Conference on Network Protocols.

[7]  Jie Wu,et al.  Making Many People Happy: Greedy Solutions for Content Distribution , 2011, 2011 International Conference on Parallel Processing.

[8]  Qinghua Li,et al.  Multicasting in delay tolerant networks: a social network perspective , 2009, MobiHoc '09.

[9]  Pan Hui,et al.  Pocket switched networks and human mobility in conference environments , 2005, WDTN '05.

[10]  Wei Tsang Ooi,et al.  Analysis and implications of student contact patterns derived from campus schedules , 2006, MobiCom '06.

[11]  Vinton G. Cerf,et al.  Delay-tolerant networking: an approach to interplanetary Internet , 2003, IEEE Commun. Mag..

[12]  Robin Kravets,et al.  Encounter-Based Routing in DTNs , 2009, INFOCOM.

[13]  Anders Lindgren,et al.  Probabilistic Routing in Intermittently Connected Networks , 2004, SAPIR.

[14]  Stephen P. Boyd,et al.  Randomized gossip algorithms , 2006, IEEE Transactions on Information Theory.

[15]  Kevin R. Fall,et al.  A delay-tolerant network architecture for challenged internets , 2003, SIGCOMM '03.

[16]  Pan Hui,et al.  BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks , 2008, IEEE Transactions on Mobile Computing.