Worst-case analysis of memory allocation algorithms

M. Garey, R. Graham, J. Ullman
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引用次数: 184

Abstract

Various memory allocation problems can be modeled by the following abstract problem. Given a list A = (&agr;1,&agr;2,...&agr;n,) of real numbers in the range (0, 1], place these in a minimum number of “bins” so that no bin holds numbers summing to more than 1. We let A* be the smallest number of bins into which the numbers of list A may be placed. Since a general placement algorithm for attaining A* appears to be impractical, it is important to determine good heuristic methods for assigning numbers of bins. We consider four such simple methods and analyze the worst-case performance of each, closely bounding the maximum of the ratio of the number of bins used by each method applied to list A to the optimal quantity A*.
内存分配算法的最坏情况分析
各种内存分配问题可以通过以下抽象问题来建模。给定一个列表a = (&agr;1,&agr;2,…&agr;n,),包含范围为(0,1)的实数,将这些实数放入最小数量的“箱子”中,这样没有一个箱子存放总和大于1的数字。我们设A*为列表A可以放置的最小箱子数。由于获得a *的一般放置算法似乎不切实际,因此确定分配箱子数量的良好启发式方法非常重要。我们考虑了四种这样的简单方法,并分析了每种方法的最坏情况性能,并将每种方法用于列表A的箱数与最优数量A*之比的最大值紧密地限定在一起。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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