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Algorithmic Mechanisms for Reliable Crowdsourcing Computation under Collusion

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  • Antonio Fernández Anta
  • Chryssis Georgiou
  • Miguel A Mosteiro
  • Daniel Pareja

Abstract

We consider a computing system where a master processor assigns a task for execution to worker processors that may collude. We model the workers’ decision of whether to comply (compute the task) or not (return a bogus result to save the computation cost) as a game among workers. That is, we assume that workers are rational in a game-theoretic sense. We identify analytically the parameter conditions for a unique Nash Equilibrium where the master obtains the correct result. We also evaluate experimentally mixed equilibria aiming to attain better reliability-profit trade-offs. For a wide range of parameter values that may be used in practice, our simulations show that, in fact, both master and workers are better off using a pure equilibrium where no worker cheats, even under collusion, and even for colluding behaviors that involve deviating from the game.

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  • Antonio Fernández Anta & Chryssis Georgiou & Miguel A Mosteiro & Daniel Pareja, 2015. "Algorithmic Mechanisms for Reliable Crowdsourcing Computation under Collusion," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-22, March.
    • Handle: RePEc:plo:pone00:0116520
    DOI: 10.1371/journal.pone.0116520
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    References listed on IDEAS

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