Structural Vulnerability Assessment of Community-Based Routing in Opportunistic Networks

Opportunistic networks enable mobile devices to communicate with each other through routes that are built dynamically, while messages are en route between the sender and the destination(s). The social structure and interaction of users of such devices dictate the performance of routing protocols in those networks. Community structures, commonly exhibited by social networks, is also observed in the encounter patterns in opportunistic networks and has an astounding impact in designing forwarding algorithms for such types of networks. In this paper, we explore the structural vulnerability of social-based forwarding and routing methods in opportunistic networks. In particular, we introduce Community Vulnerability Assessment (CVA), a new problem on assessing the performance reliability of opportunistic routing strategies in Delay Tolerant Networks (DTN) from a community structure point of view. Given a positive number k, CVA aims to find out the k most vulnerable devices in the network whose non-participation (due to out-of-service or permanent out-of-range) transforms the current network community structure to a totally different one. As the first study in this direction, we analyze and provide key insights into the separation of network communities, evaluated via the Normalized Mutual Information (NMI). Based on these findings, we suggest an approximation algorithm for the special case when k 1/4 1, and a heuristic, genEdge, for the general case. To certify the effectiveness of our proposed approaches, we first test them on synthesized data with known community structures, and then we show the impact of node removal on community structures in real social networks. Finally we evaluate the performance via different forwarding and routing strategies in multiple real-world DTN traces. Our results indicate that, in many forwarding and routing methods, the nonparticipation of only some important devices is significant enough to degrade the entire network's performance.

[1]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[2]  Elizabeth M. Belding-Royer,et al.  A review of current routing protocols for ad hoc mobile wireless networks , 1999, IEEE Wirel. Commun..

[3]  Réka Albert,et al.  Structural vulnerability of the North American power grid. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

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

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

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

[7]  P. Tan,et al.  Node roles and community structure in networks , 2007, WebKDD/SNA-KDD '07.

[8]  Pan Hui,et al.  How Small Labels Create Big Improvements , 2006, Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07).

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

[10]  Alan T. Murray,et al.  Comparative Approaches for Assessing Network Vulnerability , 2008 .

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

[12]  Krishna P. Gummadi,et al.  On the evolution of user interaction in Facebook , 2009, WOSN '09.

[13]  Andrea Lancichinetti,et al.  Community detection algorithms: a comparative analysis: invited presentation, extended abstract , 2009, VALUETOOLS.

[14]  Boleslaw K. Szymanski,et al.  Friendship Based Routing in Delay Tolerant Mobile Social Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[15]  Santo Fortunato,et al.  Finding Statistically Significant Communities in Networks , 2010, PloS one.

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

[17]  Ying Fan,et al.  Identifying and Characterizing Nodes Important to Community Structure Using the Spectrum of the Graph , 2011, PloS one.

[18]  Nam P. Nguyen,et al.  Overlapping communities in dynamic networks: their detection and mobile applications , 2011, MobiCom.

[19]  Qinghua Li,et al.  Social-Aware Multicast in Disruption-Tolerant Networks , 2012, IEEE/ACM Transactions on Networking.

[20]  Nam P. Nguyen,et al.  Assessing network vulnerability in a community structure point of view , 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

[21]  Ying Zhu,et al.  A Survey of Social-Based Routing in Delay Tolerant Networks: Positive and Negative Social Effects , 2013, IEEE Communications Surveys & Tutorials.

[22]  Bruno Simeone,et al.  The maximum vertex coverage problem on bipartite graphs , 2014, Discret. Appl. Math..

[23]  My T. Thai,et al.  Are communities as strong as we think? , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[24]  Nam P. Nguyen,et al.  Structural Vulnerability Analysis of Overlapping Communities in Complex Networks , 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).