Luo T, Tan HP, Xia L (2014) Profit-maximizing incentive for participatory sensing. Peer-to-Peer Networking and Applications, pp.1–20 Liu X, Ota K, Liu A, Chen Z (2015) An incentive game based evolutionary model for crowd sensing networks. ACM SIGOPS Operating Systems Review 43(4):84–89 Ledlie J, Odero B, Minkov E, Kiss I, Polifroni J (2010) Crowd translator: on building localized speech recognizers through micropayments. Karlin AR, Kempe D (2005) Beyond VCG: Frugality of truthful mechanisms. Pervasive Computing and Communications,IEEE International Conference on, pp. Jaimes LG, Vergara-Laurens I, Labrador M.A (2012) A location-based incentive mechanism for participatory sensing systems with budget constraints. Society for Industrial and Applied Mathematicsįeng Z, Zhu Y, Zhang Q, Ni ML, Vasilakos AV (2014) TRAC: Truthful auction for location-aware collaborative sensing in mobile crowdsourcing, INFOCOM, Proceedings IEEE Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms, pp. 1701–1709Įlkind E, Sahai A, Steiglitz K (2004) Frugality in path auctions. MIT pressĭuan L, Kubo T, Sugiyama K, Huang J, Hasegawa T, Walrand J (2012) Incentive mechanisms for smartphone collaboration in data acquisition and distributed computing. Science China Information Sciences 56(2):1–13Ĭormen TH (2009) Introduction to algorithms. Mobile Networks and Applications 19(1):88–100Ĭhai R, Wang X, Chen Q, Svensson T (2013) Utility-based bandwidth allocation algorithm for heterogeneous wireless networks. Idc worldwide smartphone growth forecast toslow from a boil to a simmer as prices drop and market mature., Īmintoosi H, Kanhere SS (2014) A reputation framework for social participatory sensing systems. Through both rigid theoretical analysis and extensive simulations, we demonstrate that the proposed mechanisms have good performance and high computational efficiency in real world applications. Moreover, online incentive mechanisms are further proposed for real time tasks. Considering the information of users’ costs and the types of tasks, four incentive mechanisms are presented for various cases to the above problem, which are proved to have the Nash equilibrium solutions in all cases for maximizing the utility of the server. Specifically, participants would consider task priority and the server would design suitable reward functions to allocate the total payment. In this paper, we focus on the common realistic scenario with multiple collaborative tasks, where each task requires a group of users to perform collaboratively. Traditional incentive mechanisms are applied for either single task or multiple dependent tasks, which fails to consider the interrelation among various tasks. To address this problem, we propose an incentive framework based on Stackelberg game to model the interaction between the server and users. However, it is a challenge to motivate sufficient users to provide their resource of personal devices for achieving good quality of service. Wireless personal networks facilitate to exploit the communication opportunity and makes diverse spare-resource of personal devices utilized. In this paper, we tackle the problem of stimulating users to join mobile crowdsourcing applications with personal devices such as smartphones and tablets.
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