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Reordering Buffer Management for Non-uniform Cost Models

机译:用于非统一成本模型的重新排序缓冲管理

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A sequence of objects which are characterized by their color has to be processed. Their processing order influences how efficiently they can be processed: Each color change between two consecutive objects produces non-uniform cost. A reordering buffer which is a random access buffer with storage capacity for k objects can be used to rearrange this sequence in such a way that the total cost are minimized. This concept is useful for many applications in computer science and economics. We show that a reordering buffer reduces the cost of each sequence by a factor of at most 2k - 1. This result even holds for cost functions modeled by arbitrary metric spaces. In addition, a matching lower bound is presented. Prom this bound follows that each strategy that does not increase the cost of a sequence is at least (2k - l)-competitive. As main result, we present the deterministic Maximum Adjusted Penalty (MAP) strategy which is O(log k)-competitive. Previous strategies only achieve a competitive ratio of k in the non-uniform model. For the upper bound on MAP, we introduce a basic proof technique. We believe that this technique can be interesting for other problems.
机译:必须处理其特征的对象序列。它们的处理订单影响如何有效地处理它们:两个连续对象之间的每个颜色变化产生不均匀的成本。作为K对象存储容量的随机接入缓冲器的重新排序缓冲区可用于重新排列该序列,使得总成本最小化。这一概念对于计算机科学和经济学中的许多应用是有用的。我们表明重新排序缓冲区将每个序列的成本降低至最多2K - 1.该结果甚至用于由任意度量空间建模的成本函数。此外,呈现匹配的下限。 PROM这一界限遵循的是,不增加序列成本的每个策略至少(2k-L) ​​- 竞争力。作为主要结果,我们介绍了确定的最大调整惩罚(MAP)策略,其是O(log k) - 竞争力。以前的策略仅在非统一模型中达到k的竞争比率。对于地图上限,我们介绍了一种基本证明技术。我们认为这种技术对于其他问题可能很有趣。

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