Profit-maximizing incentive for participatory sensing

Profit-maximizing incentive for participatory sensing
Title:
Profit-maximizing incentive for participatory sensing
Other Titles:
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
Keywords:
Publication Date:
27 April 2014
Citation:
T. Luo, H. P. Tan and L. Xia, "Profit-maximizing incentive for participatory sensing," IEEE INFOCOM 2014 - IEEE Conference on Computer Communications, Toronto, ON, 2014, pp. 127-135. doi: 10.1109/INFOCOM.2014.6847932
Abstract:
We design an incentive mechanism based on all-pay auctions for participatory sensing. The organizer (principal) aims to attract a high amount of contribution from participating users (agents) while at the same time lowering his payout, which we formulate as a profit-maximization problem. We use a contribution-dependent prize function in an environment that is specifically tailored to participatory sensing, namely incomplete information (with information asymmetry), risk-averse agents, and stochastic population. We derive the optimal prize function that induces the maximum profit for the principal, while satisfying strict individual rationality (i.e., strictly have incentive to participate at equilibrium) for both risk-neutral and weakly risk-averse agents. The thus induced profit is demonstrated to be higher than the maximum profit induced by constant (yet optimized) prize. We also show that our results are readily extensible to cases of risk-neutral agents and deterministic populations.
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PublisherCopyrights
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(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
ISSN:
0743-166X
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