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Analytical model with a novel selfishness division of mobile nodes to participate cooperation

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Abstract

With the recent increase in the use of mobile devices, mobile crowd sensing (MCS) has attracted more and more attention, where mobile individuals are encouraged to collect and contribute data for common interests for different applications. However, in the real world, some of mobile individuals may not be willing to share information with others due to selfishness. So how to make the analysis of selfish behavior to encourage participants for cooperation becomes an important issue. In this paper, we firstly divide selfishness into two new types: weak selfishness and extreme selfishness. Then we develop an analytical model to evaluate the influence of selfish behavior on the information dissemination process. Numerical results demonstrate the effects of weak selfishness and extreme selfishness, respectively. In addition, the results also show the relationship among the selfish behavior, information dissemination and users’ mobility pattern.

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Acknowledgments

This work was supported in part by the fundamental key research project of Shanghai Municipal Science and Technology Commission under grant 12JC1404201, the Ministry of Education Research Fund-China Mobile (2012) MCM20121032.

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Authors and Affiliations

  1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China

    Qichao Xu, Zhou Su, Dongfeng Fang & Zejun Xu

  2. State Key Laboratory of Integrated Services, Xidian University, Xi’an, 710071, China

    Qichao Xu

  3. Center of Information and Networks, Xi’an JiaoTong University, Xi’an, 710049, China

    Bo Han

  4. Institute of Wireless Communication, Shanghai JiaoTong University, Shanghai, 200240, China

    Xiaoying Gan

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  1. Qichao Xu
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  2. Zhou Su
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  3. Bo Han
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  4. Dongfeng Fang
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  5. Zejun Xu
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  6. Xiaoying Gan
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Correspondence to Zhou Su.

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Xu, Q., Su, Z., Han, B. et al. Analytical model with a novel selfishness division of mobile nodes to participate cooperation. Peer-to-Peer Netw. Appl. 9, 712–720 (2016). https://doi.org/10.1007/s12083-015-0330-6

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  • DOI: https://doi.org/10.1007/s12083-015-0330-6

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