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Social-Aware Computing based Congestion Control in Delay Tolerant Networks

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Abstract

The routing efficiency in Delay Tolerant Networks (DTN) with social characteristics degrades owing to intermittent connection and high latency. Additionally, congestion is another issue because of the limited resources of nodes. To solve these problems, an improved Socially Aware Congestion Control algorithm (SACC) is proposed. In this algorithm, the social features and the congestion level of the node are utilized to construct a Social Congestion Metric (SCM). In the forwarding process, messages are forwarded to the nodes with higher SCM. When the congestion occurs, the node calculates the social links of itself with every message’s destination node, and then drops the message with minimum social link rather than random dropping. Simulation results show that in the acceptable range of delay tolerance, the proposed algorithm improves the delivery probability, decreases the dropping probability and reduces the overhead.

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Acknowledgment

This work is supported by NSFC (61572262); NSF of Jiangsu Province (BK20141427), NUPT (NY214097); Open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education (NYKL201507), Qinlan Project of Jiangsu Province.

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Authors and Affiliations

  1. College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, Jiangsu, 210009, China

    Yan Liu

  2. Key Lab of Broadband Wireless Communications Sensor Network Technology, Nanjing University of Posts Telecommunications, Nanjing, Jiangsu, 210003, China

    Kun Wang, Huang Guo, Qing Lu & Yanfei Sun

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  1. Yan Liu
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  2. Kun Wang
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  3. Huang Guo
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  4. Qing Lu
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  5. Yanfei Sun
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Correspondence to Kun Wang.

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Liu, Y., Wang, K., Guo, H. et al. Social-Aware Computing based Congestion Control in Delay Tolerant Networks. Mobile Netw Appl 22, 174–185 (2017). https://doi.org/10.1007/s11036-016-0759-8

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  • DOI: https://doi.org/10.1007/s11036-016-0759-8

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