Multi-round Master-Worker Computing: a Repeated Game Approach

We consider a computing system where a master processor assigns tasks for execution to worker processors through the Internet. 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 mixed extension of a strategic game among workers. That is, we assume that workers are rational in a game-theoretic sense, and that they randomize their strategic choice. Workers are assigned multiple tasks in subsequent rounds. We model the system as an infinitely repeated game of the mixed extension of the strategic game. In each round, the master decides stochastically whether to accept the answer of the majority or verify the answers received, at some cost. Incentives and/or penalties are applied to workers accordingly. Under the above framework, we study the conditions in which the master can reliably obtain tasks results, exploiting that the repeated games model captures the effect of long-term interaction. That is, workers take into account that their behavior in one computation will have an effect on the behavior of other workers in the future. Indeed, should a worker be found to deviate from some agreed strategic choice, the remaining workers would change their own strategy to penalize the deviator. Hence, being rational, workers do not deviate. We identify analytically the parameter conditions to induce a desired worker behavior, and we evaluate experi- mentally the mechanisms derived from such conditions. We also compare the performance of our mechanisms with a previously known multi-round mechanism based on reinforcement learning.Comment: 21 pages, 3 figure

Algorithmic mechanisms for reliable master-worker internet-based computing

We consider Internet-based master-worker computations, where a master processor assigns, across the Internet, a computational task to a set of untrusted worker processors, and collects their responses. Examples of such computations are the @home projects such as SETI. In this work, various worker behaviors are considered. Altruistic workers always return the correct result of the task, malicious workers always return an incorrect result, and rational workers act based on their self-interest. In a massive computation platform, such as the Internet, it is expected that all three type of workers coexist. Therefore, in this work, we study Internet-based master-worker computations in the presence of malicious, altruistic, and rational workers. A stochastic distribution of the workers over the three types is assumed. In addition, we consider the possibility that the communication between the master and the workers is not reliable, and that workers could be unavailable. Considering all the three types of workers renders a combination of game-theoretic and classical distributed computing approaches to the design of mechanisms for reliable Internet-based computing. Indeed, in this work, we design and analyze two algorithmic mechanisms to provide appropriate incentives to rational workers to act correctly, despite the malicious workers\u27 actions and the unreliability of the communication. Only when necessary, the incentives are used to force the rational players to a certain equilibrium (which forces the workers to be truthful) that overcomes the attempt of the malicious workers to deceive the master. Finally, the mechanisms are analyzed in two realistic Internet-based master-worker settings, a SETI-like one and a contractor-based one, such as Amazon\u27s mechanical turk. We also present plots that illustrate the tradeoffs between reliability and cost, under different system parameters. © 2013 IEEE