Approximate and on-line algorithms for list update problem

H. Mahanta, Phalguni Gupta, Sajal K. Das
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引用次数: 0

Abstract

In this paper we present two algorithms for solving the list update problem which is to maintain a list of items to support such basic operations as access, insert and delete. The first algorithm proposed is an approximation to the optimal off-line algorithm. Knowing the complete request sequence, it provides a good approximation to the lower bound of the optimum cost and finds an approximately optimum service sequence in polynomial time of the list and the size of the request sequence. The underlying idea is to maintain the pairwise optimal ordering of the items except for the case of conflicts, when no exchange takes place. The approximate off-line algorithm takes O(n/sup 3/ m) time and O(1) space, where n is the length of the list and m is the number of requests. Our second algorithm is a deterministic on-line algorithm which is shown to be 2-competitive under any sequence of access requests. It can be efficiently implemented compared to the best known deterministic online algorithms such as MTF and TS (0). We also show that using the proposed on-line algorithm as a procedure in data compression techniques, it is possible to obtain better compression ratio.
列表更新问题的近似和在线算法
本文提出了两种解决列表更新问题的算法,该问题是为了维护一个项目列表,以支持诸如访问、插入和删除等基本操作。提出的第一种算法是最优离线算法的近似。知道完整的请求序列,它提供了一个很好的最优成本下界的近似值,并在列表和请求序列大小的多项式时间内找到一个近似最优的服务序列。其基本思想是保持物品的成对最优排序,除非在没有交换的情况下发生冲突。近似离线算法需要O(n/sup 3/ m)时间和O(1)空间,其中n为列表长度,m为请求数。我们的第二种算法是一种确定性在线算法,它在任何访问请求序列下都是2竞争的。与最著名的确定性在线算法(如MTF和TS(0))相比,它可以有效地实现。我们还表明,将所提出的在线算法作为数据压缩技术中的一个过程,可以获得更好的压缩比。
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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