Opportunistic mobile social networks: From mobility and Facebook friendships to structural analysis of user social behavior

Abstract In the last few years, several real-world mobility traces for opportunistic networks have been collected in order to explore node mobility and evaluate the performance of opportunistic networking protocols. These datasets, often including online social data of the mobile users involved, are increasingly driving the research towards the analysis of user social behavior. Within these challenged infrastructureless networks where connectivity is highly intermittent and contact opportunities are exploited to allow communication, node mobility is basically driven by human sociality. As such, understanding node sociality is of paramount importance, especially for finding suitable relays in message forwarding. This paper presents a detailed analysis of a set of six different mobility traces for opportunistic network environments including nodes’ Facebook friendships. Using a multi-layer social network approach and defining several similarity classes between layers, we analyze egocentric and sociocentric node behaviors on the two-layer social graph constructed on offline mobility and online social data. Results show that online and offline centralities are not significantly correlated on most datasets. Also online and offline community structures are different. On the contrary, most of the offline strong social ties correspond to online social ties and in some cases, online and offline brokerage roles show high similarity.

[1]  Andrea Passarella,et al.  Egocentric online social networks: Analysis of key features and prediction of tie strength in Facebook , 2013, Comput. Commun..

[2]  Shaojie Tang,et al.  COUPON: A Cooperative Framework for Building Sensing Maps in Mobile Opportunistic Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[3]  Salvatore Marano,et al.  Exploring user sociocentric and egocentric behaviors in online and detected social networks , 2012, 2012 2nd Baltic Congress on Future Internet Communications.

[4]  Salvatore Marano,et al.  Exploiting online and offline activity-based metrics for opportunistic forwarding , 2014, Wireless Networks.

[5]  Annalisa Socievole,et al.  CRAWDAD dataset unical/socialblueconn (v.2015-02-08) , 2015 .

[6]  Anna Monreale,et al.  Foundations of Multidimensional Network Analysis , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[7]  Xingshe Zhou,et al.  Opportunistic IoT: Exploring the social side of the internet of things , 2012, Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[8]  Saleem N. Bhatti,et al.  Exploiting Self-Reported Social Networks for Routing in Ubiquitous Computing Environments , 2008, 2008 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications.

[9]  Jon Crowcroft,et al.  ML-SOR: Message routing using multi-layer social networks in opportunistic communications , 2015, Comput. Networks.

[10]  Vinton G. Cerf,et al.  Delay-Tolerant Networking Architecture , 2007, RFC.

[11]  Marco Conti,et al.  The structure of online social networks mirrors those in the offline world , 2015, Soc. Networks.

[12]  Thrasyvoulos Spyropoulos,et al.  Collection and analysis of multi-dimensional network data for opportunistic networking research , 2012, Comput. Commun..

[13]  Christophe Diot,et al.  CRAWDAD dataset thlab/sigcomm2009 (v.2012-07-15) , 2012 .

[14]  Paolo Santi,et al.  Social-aware stateless forwarding in pocket switched networks , 2011, 2011 Proceedings IEEE INFOCOM.

[15]  Alex Pentland,et al.  Modeling the co-evolution of behaviors and social relationships using mobile phone data , 2011, MUM.

[16]  Ciprian Dobre,et al.  CRAWDAD dataset upb/mobility2011 (v.2012-06-18) , 2012 .

[17]  Matteo Magnani,et al.  The ML-Model for Multi-layer Social Networks , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[18]  Paolo Santi,et al.  Social-Aware Stateless Routingin Pocket Switched Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

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

[20]  Mark S. Granovetter The Strength of Weak Ties , 1973, American Journal of Sociology.

[21]  C. Dangalchev Residual closeness in networks , 2006 .

[22]  Marco Conti,et al.  Opportunistic networking: data forwarding in disconnected mobile ad hoc networks , 2006, IEEE Communications Magazine.

[23]  Saleem N. Bhatti,et al.  CRAWDAD dataset st_andrews/sassy (v.2011-06-03) , 2011 .

[24]  Annalisa Socievole,et al.  Routing approaches and performance evaluation in delay tolerant networks , 2011, 2011 Wireless Telecommunications Symposium (WTS).

[25]  J. Nieminen On the centrality in a graph. , 1974, Scandinavian journal of psychology.

[26]  Salvatore Marano,et al.  Face-to-face with facebook friends: Using online friendlists for routing in opportunistic networks , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[27]  Albert Y. Zomaya,et al.  OmniSuggest: A Ubiquitous Cloud-Based Context-Aware Recommendation System for Mobile Social Networks , 2014, IEEE Transactions on Services Computing.

[28]  Annalisa Socievole,et al.  Wireless contacts, Facebook friendships and interests: Analysis of a multi-layer social network in an academic environment , 2014, 2014 IFIP Wireless Days (WD).

[29]  Xia Wang,et al.  Analyzing the potential of mobile opportunistic networks for big data applications , 2015, IEEE Network.

[30]  Mostafa H. Ammar,et al.  PeopleRank: Social Opportunistic Forwarding , 2010, 2010 Proceedings IEEE INFOCOM.

[31]  Mads Haahr,et al.  Social Network Analysis for Information Flow in Disconnected Delay-Tolerant MANETs , 2009, IEEE Transactions on Mobile Computing.

[32]  Przemyslaw Kazienko,et al.  Multi-layered Social Networks , 2012, ArXiv.

[33]  Ciprian Dobre,et al.  SPRINT: Social prediction-based opportunistic routing , 2013, 2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).

[34]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[35]  Leon Danon,et al.  Comparing community structure identification , 2005, cond-mat/0505245.

[36]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[37]  Gert Sabidussi,et al.  The centrality index of a graph , 1966 .

[38]  Aravind Srinivasan,et al.  Mobile Data Offloading through Opportunistic Communications and Social Participation , 2012, IEEE Transactions on Mobile Computing.

[39]  Gian Paolo Rossi,et al.  Facencounter: Bridging the Gap between Offline and Online Social Networks , 2012, 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems.

[40]  Greg Bigwood,et al.  Bootstrapping opportunistic networks using social roles , 2011, 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks.

[41]  L. Freeman Centrality in social networks conceptual clarification , 1978 .

[42]  George Varghese,et al.  MobiClique: middleware for mobile social networking , 2009, WOSN '09.

[43]  Ciprian Dobre,et al.  Interest-awareness in data dissemination for opportunistic networks , 2015, Ad Hoc Networks.

[44]  Ciprian Dobre,et al.  Social Aspects to Support Opportunistic Networks in an Academic Environment , 2012, ADHOC-NOW.

[45]  P. Bonacich Factoring and weighting approaches to status scores and clique identification , 1972 .

[46]  Roger V. Gould,et al.  Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks , 1989 .

[47]  Leonard M. Freeman,et al.  A set of measures of centrality based upon betweenness , 1977 .

[48]  Katarzyna Musial,et al.  Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks , 2012, Int. J. Comput. Intell. Syst..