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Cost of Guessing: Applications to Data Repair

机译:猜测成本:数据修复应用

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In this paper, we introduce the notion of cost of guessing and provide an optimal strategy for guessing a random variable taking values on a finite set whereby each choice may be associated with a positive finite cost value. Moreover, we drive asymptotically tight upper and lower bounds on the moments of cost of guessing problem. Similar to previous studies on the standard guesswork, established bounds on moments quantify the accumulated cost of guesses required for correctly identifying the unknown choice and are expressed in terms of the Rényi’s entropy. A new random variable is introduced to bridge between cost of guessing and the standard guesswork and establish the guessing cost exponent on the moments of the optimal guessing. Furthermore, these bounds are shown to serve quite useful for finding repair latency cost for distributed data storage in which sparse graph codes may be utilized.
机译:在本文中,我们介绍了猜测成本的概念,并提供了一种猜测随机变量的最佳策略,该随机变量采用有限集上的值,从而使每个选择都可能与正的有限成本值相关联。此外,我们在猜测问题代价的时刻上渐近地逼近上下界。与先前关于标准猜测的研究类似,确定的力矩界限量化了正确识别未知选择所需的猜测累积成本,并以Rényi的熵表示。引入了一个新的随机变量,以在猜测成本和标准猜测工作之间架起桥梁,并在最佳猜测的时刻建立猜测成本指数。此外,显示这些边界对于寻找分布式数据存储的修复等待时间成本非常有用,在分布式数据存储中可以使用稀疏的图形代码。

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