SOCIAL POPULARITY BASED ROUTING IN DELAY TOLERANT NETWORKS

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 9 , ISSUE 4 (December 2016) > List of articles

SOCIAL POPULARITY BASED ROUTING IN DELAY TOLERANT NETWORKS

Youmei Song / Jianbo Li / Chenglong Li / Fushu Wang

Keywords : Delay Tolerant Networks, routing algorithm, social group, cohesion, popularity.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 9, Issue 4, Pages 1,687-1,709, DOI: https://doi.org/10.21307/ijssis-2017-935

License : (CC BY-NC-ND 4.0)

Received Date : 18-November-2015 / Accepted: 02-October-2016 / Published Online: 01-December-2016

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ABSTRACT

Due to node’s mobility, Delay Tolerant Networks (DTNs) feature the nonexistence of end-to-end 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.

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