Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/104377
Title: CCS-DTN : clustering and network coding-based efficient routing in social DTNs
Authors: Zhang, Zhenjing
Ma, Maode
Jin, Zhigang
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
Issue Date: 2014
Source: Zhang, Z., Ma, M., & Jin, Z. (2015). CCS-DTN : clustering and network coding-based efficient routing in social DTNs. Sensors, 15(1), 285-303.
Series/Report no.: Sensors
Abstract: With the development of mobile Internet, wireless communication via mobile devices has become a hot research topic, which is typically in the form of Delay Tolerant Networks (DTNs). One critical issue in the development of DTNs is routing. Although there is a lot research work addressing routing issues in DTNs, they cannot produce an advanced solution to the comprehensive challenges since only one or two aspects (nodes’ movements, clustering, centricity and so on) are considered when the routing problem is handled. In view of these defects in the existing works, we propose a novel solution to address the routing issue in social DTNs. By this solution, mobile nodes are divided into different clusters. The scheme, Spray and Wait, is used for the intra-cluster communication while a new forwarding mechanism is designed for the inter-cluster version. In our solution, the characteristics of nodes and the relation between nodes are fully considered. The simulation results show that our proposed scheme can significantly improve the performance of the routing scheme in social DTNs.
URI: https://hdl.handle.net/10356/104377
http://hdl.handle.net/10220/24697
ISSN: 1424-8220
DOI: 10.3390/s150100285
Rights: © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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