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AntiCheetah: Trustworthy computing in an outsourced (cheating) environment

机译:AntiCheetah:外包(作弊)环境中的可信赖计算

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The increasing need for performing expensive computations has motivated outsourced computing, as in crowdsourced applications leveraging worker cloud nodes. However, these outsourced computing nodes can potentially misbehave or fail. Exploiting the redundancy of nodes can help guaranteeing correctness and availability of results. This entails that reliable distributed computing can be achieved at the expense of convenience. In this paper, we provide a solution for a generic class of problems that distribute a parallel computation over a set of nodes where trustworthiness of the outsourced computation is important. In particular, we discuss AntiCheetah, an approach modeling the assignment of input elements to cloud nodes as a multi-round system. AntiCheetah is resilient to node cheating, even in scenarios where smart cheaters return the same fake values. To this end, cost-efficient redundancy is used to detect and correct anomalies. Furthermore, we discuss the benefits and pitfalls of the proposed approach over different scenarios, especially with respect to cheaters' behavior. Extensive experimental results are analyzed, showing the effectiveness and viability of our approach.
机译:对执行昂贵的计算的需求不断增长,促使了外包计算的发展,例如在利用工作者云节点的众包应用中。但是,这些外包的计算节点可能会出现异常或故障。利用节点的冗余可以帮助保证结果的正确性和可用性。这需要以便利为代价来实现可靠的分布式计算。在本文中,我们为通用类问题提供了一种解决方案,该类问题将并行计算分布在一组节点上,其中外包计算的可信赖性很重要。特别是,我们讨论了AntiCheetah,这是一种将输入元素分配给云节点作为多轮系统的方法。即使在智能作弊者返回相同假值的情况下,AntiCheetah仍能​​抵抗节点作弊。为此,使用经济高效的冗余来检测和纠正异常。此外,我们讨论了在不同情况下,特别是在作弊者行为方面,所提出的方法的优点和陷阱。分析了广泛的实验结果,显示了我们方法的有效性和可行性。

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