An Improved Competitive Algorithm for Reordering Buffer Management

Author:

Avigdor-Elgrabli Noa1,Rabani Yuval2

Affiliation:

1. Yahoo! Labs, Haifa, Israel

2. The Hebrew University of Jerusalem, Jerusalem, Israel

Abstract

We design and analyze an online reordering buffer management algorithm with improved O (log  k /log log  k ) competitive ratio for nonuniform costs, where k is the buffer size. This improves on the best previous result (even for uniform costs) of Englert and Westermann (2005) giving O (log  k ) competitive ratio, which was also the best (offline) polynomial time approximation guarantee for this problem. Our analysis is based on an intricate dual fitting argument using a linear programming relaxation for the problem that we introduce in this article.

Funder

Israel Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Mathematics (miscellaneous)

Reference32 articles.

1. Amjad Aboud. 2008. Correlation clustering with penalties and approximating the reordering buffer management problem. Masters thesis Computer Science Department The Technion — Israel Institute of Technology. Amjad Aboud. 2008. Correlation clustering with penalties and approximating the reordering buffer management problem. Masters thesis Computer Science Department The Technion — Israel Institute of Technology.

2. Anna Adamaszek Artur Czumaj Matthias Englert and Harald Räcke. 2011. Almost tight bounds for reordering buffer management. In STOC. 607--616. 10.1145/1993636.1993717 Anna Adamaszek Artur Czumaj Matthias Englert and Harald Räcke. 2011. Almost tight bounds for reordering buffer management. In STOC. 607--616. 10.1145/1993636.1993717

3. Anna Adamaszek Artur Czumaj Matthias Englert and Harald Räcke. 2012. Optimal online buffer scheduling for block devices. In STOC. 589--598. 10.1145/2213977.2214031 Anna Adamaszek Artur Czumaj Matthias Englert and Harald Räcke. 2012. Optimal online buffer scheduling for block devices. In STOC. 589--598. 10.1145/2213977.2214031

4. New Results on Web Caching with Request Reordering

5. The k-Client Problem

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