Quality, Reliability, Security and Robustness in Heterogeneous Systems. 13th International Conference, QShine 2017, Dalian, China, December 16 -17, 2017, Proceedings

Research Article

Performance Analysis for Content Distribution in Crowdsourced Content-Centric Mobile Networking

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  • @INPROCEEDINGS{10.1007/978-3-319-78078-8_14,
        author={Chengming Li and Xiaojie Wang and Shimin Gong and Zhi-Hui Wang and Qingshan Jiang},
        title={Performance Analysis for Content Distribution in Crowdsourced Content-Centric Mobile Networking},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 13th International Conference, QShine 2017, Dalian, China, December 16 -17, 2017, Proceedings},
        proceedings_a={QSHINE},
        year={2018},
        month={4},
        keywords={Information-Centric Networks Content-Centric Networking Mobile crowdsourcing In-network caching},
        doi={10.1007/978-3-319-78078-8_14}
    }
    
  • Chengming Li
    Xiaojie Wang
    Shimin Gong
    Zhi-Hui Wang
    Qingshan Jiang
    Year: 2018
    Performance Analysis for Content Distribution in Crowdsourced Content-Centric Mobile Networking
    QSHINE
    Springer
    DOI: 10.1007/978-3-319-78078-8_14
Chengming Li1,*, Xiaojie Wang2, Shimin Gong1, Zhi-Hui Wang2, Qingshan Jiang1
  • 1: Chinese Academy of Science
  • 2: Dalian University of Technology
*Contact email: cm.li@siat.ac.cn

Abstract

Content-Centric Networking emerges as a promising paradigm which has a better content distribution efficiency and mobility via named data and in-network caching compared with the IP-based network. However, providing a high quality of experience in content distribution of Content-Centric Mobile Networking (CCMN) is challenging due to the heterogeneous networks, varying wireless channel conditions and incentive strategies to mobile users. In this work, we propose a novel crowdsourced content distribution framework for CCMN. This framework enables the nearby mobile users to crowdsource their caching resources and radio links for cooperative content distribution. We formulate the problem as the maximization of the payoff of all users which considers content retrieve time and energy cost. Further, we analysis the upper bound and lower bound of the proposed system in term of user payoff, which can be a benchmark for the future scheduling algorithms and incentive mechanisms design.