Better algorithms for unfair metrical task systems and applications

Amos Fiat; Manor Mendel

doi:10.1145/335305.335408

Better algorithms for unfair metrical task systems and applications

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Unfair metrical task systems are a generalization of online metrical task systems. In this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain the following results: 1. Better randomized algorithms for unfair metrical task systems on the uniform metric space. 2. Better randomized algorithms for metrical task systems on general metric spaces, O(log² n(log log n)²) competitive, improving on the best previous result of O(log⁵ n log log n). 3. A tight randomized competitive ratio for the k-weighted caching problem on k+1 points, O(log k), improving on the best previous result of O(log² k).

Original language	English
Title of host publication	Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000
Pages	725-734
Number of pages	10
DOIs	https://doi.org/10.1145/335305.335408
State	Published - 2000
Externally published	Yes
Event	32nd Annual ACM Symposium on Theory of Computing, STOC 2000 - Portland, OR, United States Duration: 21 May 2000 → 23 May 2000

Publication series

Name	Proceedings of the Annual ACM Symposium on Theory of Computing
ISSN (Print)	0737-8017

Conference

Conference	32nd Annual ACM Symposium on Theory of Computing, STOC 2000
Country/Territory	United States
City	Portland, OR
Period	21/05/00 → 23/05/00

Access to Document

10.1145/335305.335408

Cite this

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title = "Better algorithms for unfair metrical task systems and applications",

abstract = "Unfair metrical task systems are a generalization of online metrical task systems. In this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain the following results: 1. Better randomized algorithms for unfair metrical task systems on the uniform metric space. 2. Better randomized algorithms for metrical task systems on general metric spaces, O(log2 n(log log n)2) competitive, improving on the best previous result of O(log5 n log log n). 3. A tight randomized competitive ratio for the k-weighted caching problem on k+1 points, O(log k), improving on the best previous result of O(log2 k).",

author = "Amos Fiat and Manor Mendel",

year = "2000",

doi = "10.1145/335305.335408",

language = "אנגלית",

isbn = "1581131844",

series = "Proceedings of the Annual ACM Symposium on Theory of Computing",

pages = "725--734",

booktitle = "Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000",

}

Fiat, A & Mendel, M 2000, Better algorithms for unfair metrical task systems and applications. in Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, STOC 2000. Proceedings of the Annual ACM Symposium on Theory of Computing, pp. 725-734, 32nd Annual ACM Symposium on Theory of Computing, STOC 2000, Portland, OR, United States, 21/05/00. https://doi.org/10.1145/335305.335408

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N2 - Unfair metrical task systems are a generalization of online metrical task systems. In this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain the following results: 1. Better randomized algorithms for unfair metrical task systems on the uniform metric space. 2. Better randomized algorithms for metrical task systems on general metric spaces, O(log2 n(log log n)2) competitive, improving on the best previous result of O(log5 n log log n). 3. A tight randomized competitive ratio for the k-weighted caching problem on k+1 points, O(log k), improving on the best previous result of O(log2 k).

AB - Unfair metrical task systems are a generalization of online metrical task systems. In this paper we introduce new techniques to combine algorithms for unfair metrical task systems and apply these techniques to obtain the following results: 1. Better randomized algorithms for unfair metrical task systems on the uniform metric space. 2. Better randomized algorithms for metrical task systems on general metric spaces, O(log2 n(log log n)2) competitive, improving on the best previous result of O(log5 n log log n). 3. A tight randomized competitive ratio for the k-weighted caching problem on k+1 points, O(log k), improving on the best previous result of O(log2 k).

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Better algorithms for unfair metrical task systems and applications

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