SOCIAL POPULARITY BASED ROUTING IN DELAY TOLERANT NETWORKS

Due to node’s mobility, Delay Tolerant Networks (DTNs) feature the nonexistence of end-toend path between source and destination, frequent topology partitions and extremely high delivery latency, thus posing great challenges to successful message transmission. To improve routing performance and provide high quality communication service, nodes’ social characteristics are exploited to routing design recently. Hence, a social popularity based routing algorithm is proposed, named SPBR which takes the inter-contact time and multi-hop neighbor information into consideration. In this paper, we first introduce a method to detect the quality of relation between pair of nodes accurately. Used the reliable relationships, social popularity is proposed to evaluate the social power of node in the network. SPBR makes the routing decisions based on the popularity, leading message closer to destinations with low hops of routing and network resources. Extensive simulations are conducted and the results show that the proposed algorithm significantly improves routing performances compared to Epidemic, Prophet and First Contact (FC), especially SPBR is lower by about 55.1% in overhead ratio and higher by about 22.2% in delivery rate than Epidemic when there are 40 nodes in the networks.

[1]  Rabin K. Patra,et al.  Routing in a delay tolerant network , 2004, SIGCOMM '04.

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

[3]  Amin Vahdat,et al.  Epidemic Routing for Partially-Connected Ad Hoc Networks , 2009 .

[4]  K. J. Ray Liu,et al.  Cooperation Stimulation Strategies for Peer-to-Peer Wireless Live Video-Sharing Social Networks , 2010, IEEE Transactions on Image Processing.

[5]  Wanlei Zhou,et al.  Multidimensional Routing Protocol in Human-Associated Delay-Tolerant Networks , 2013, IEEE Transactions on Mobile Computing.

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

[7]  Sagar Naik,et al.  SGBR: A Routing Protocol for Delay Tolerant Networks Using Social Grouping , 2013, IEEE Transactions on Parallel and Distributed Systems.

[8]  Jörg Ott,et al.  The ONE simulator for DTN protocol evaluation , 2009, SIMUTools 2009.

[9]  Jie Wu,et al.  Community-Aware Opportunistic Routing in Mobile Social Networks , 2014, IEEE Transactions on Computers.

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

[11]  Li Su,et al.  Contact duration aware evaluation for content dissemination delay in mobile social network , 2015, Wirel. Commun. Mob. Comput..

[12]  Marco Conti,et al.  Human mobility models for opportunistic networks , 2011, IEEE Communications Magazine.

[13]  J. Ott.  DELAY TOLERANCE AND THE FUTURE INTERNET , 2008 .

[14]  Kun Yang,et al.  Mobile Social Networks: Architectures, Social Properties, and Key Research Challenges , 2013, IEEE Communications Surveys & Tutorials.

[15]  Joel J. P. C. Rodrigues,et al.  GeoSpray: A geographic routing protocol for vehicular delay-tolerant networks , 2014, Inf. Fusion.

[16]  Xu Jia,et al.  Adaptive Spray Routing For Opportunistic Networks , 2013 .

[17]  Joan Triay,et al.  From Delay-Tolerant Networks to Vehicular Delay-Tolerant Networks , 2012, IEEE Communications Surveys & Tutorials.

[18]  Zheng Guo,et al.  Generic prediction assisted single-copy routing in underwater delay tolerant sensor networks , 2013, Ad Hoc Networks.

[19]  Ke Xu,et al.  Distribution of inter-contact time: An analysis-based on social relationships , 2013, Journal of Communications and Networks.

[20]  Wu Lei,et al.  UTILITY BASED DATA GATHERING IN MOBILE SENSOR NETWORK , 2013 .