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Competitive paging algorithms

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TLDR
The marking algorithm is developed, a randomized on-line algorithm for the paging problem, which it is proved that its expected cost on any sequence of requests is within a factor of 2Hk of optimum.
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This article is published in Journal of Algorithms.The article was published on 1991-12-01 and is currently open access. It has received 489 citations till now. The article focuses on the topics: Page replacement algorithm & K-server problem.

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Citations
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Can Parallel Algorithms Enhance Serial Implementation? (Extended Abstract)

Uzi Vishkin
TL;DR: The broad thesis presented in this paper suggests that the serial emulation of a parallel algorithm has the potential advantage of running on a serial machine faster than a standard serial algorithm for the same problem.
Journal ArticleDOI

The k-resource problem in uniform metric spaces

TL;DR: Asymptotically tight bounds are shown on the competitive ratio of the k-resource problem in the uniform metric space of n points: it is proved that the optimal competitive ratios are between min {k,n-1} and min{k,2(n- 1)} for deterministic algorithms and between min{H"k,H"n"-"1} for randomized ones.

On-Line caching tis Cache

Neal Young
TL;DR: Reconsider the competitiveness of on-line strategies using k servers versus the optimal off-line strategy using h S k servers for the paging, weighted cache, and k-server problems and shows that for the weighted cache prc~blem the balance algorithm is --competitive.
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The work function algorithm for the paging problem

TL;DR: In this paper , it was shown that WFA is k M / m -competitive for the k-server problem where the distances between two points are all in [ m , M ] (0 < m ≤ M ), and thus WFA was k -competitive in the paging problem.
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Adversarial Bandits with Knapsacks

- 17 Nov 2022 - 
TL;DR: In this article , a black-box reduction from bandits to knapsack problems was proposed, where the outcomes can be chosen adversarially and regret minimization is no longer feasible.
References
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Journal ArticleDOI

Amortized efficiency of list update and paging rules

TL;DR: This article shows that move-to-front is within a constant factor of optimum among a wide class of list maintenance rules, and analyzes the amortized complexity of LRU, showing that its efficiency differs from that of the off-line paging rule by a factor that depends on the size of fast memory.
Proceedings ArticleDOI

Probabilistic computations: Toward a unified measure of complexity

TL;DR: Two approaches to the study of expected running time of algoritruns lead naturally to two different definitions of intrinsic complexity of a problem, which are the distributional complexity and the randomized complexity, respectively.
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Competitive snoopy caching

TL;DR: This work presents new on-line algorithms to be used by the caches of snoopy cache multiprocessor systems to decide which blocks to retain and which to drop in order to minimize communication over the bus.
Journal ArticleDOI

Competitive algorithms for server problems

TL;DR: This paper seeks to develop on-line algorithms whose performance on any sequence of requests is as close as possible to the performance of the optimum off-line algorithm.
Proceedings ArticleDOI

Competitive algorithms for on-line problems

TL;DR: This paper presents several general results concerning competitive algorithms, as well as results on specific on-line problems.
Related Papers (5)
Frequently Asked Questions (11)
Q1. What are the contributions mentioned in the paper "Competitive paging algorithms" ?

In this paper, the authors proposed a method for the analysis of the relationship between computer science degrees and their application in the field of artificial intelligence. 

Karlin et al. [8] have shown that for two servers in a graph that is an isosceles triangle the best competitive factor that can be achieved is a constant that approaches e/(e - 1) z 1.582 as the length of the similar sides go to infinity. 

A randomized on-line algorithm may be viewed as basing its actions on the request sequence (T presented to it and on an infinite sequence p of independent unbiased random bits. 

The marking algorithm is strongly competitive (its competitive factor is Hk) if k = n - 1, but it is not strongly competitive if k < n - 1. 

They showed that LRU running with k servers performs within a factor of k/(k - h + 1) of any off-line algorithm with h 5 k servers and that this is the minimum competitive factor that can be achieved. 

They showed that no deterministic algorithm for the k-server problem can be better than k-competitive, they gave k-competitive algorithms for the case when k = 2 and k = II - 1, and they conjectured that there exists a k-competitive k-server algorithm for any graph. 

The adversary is, however, able to maintain a vector p = (pl, p2,. . . , p,) of probabilities, where pi is the probability that vertex i is not covered by a server. 

In that proof, deterministic on-line algorithms B(l), B(2), . . . , B(m) of type (k, n) were given, and the deterministic on-line algorithm A of type (k, n) was constructed to be &)-competitive against B(i) for each i. 

If the total expected cost ends up exceeding l/u, then an arbitrary request is made to an unmarked vertex, and the subphase is over. 

During this phase exactly the vertices of S were requested, so since A is lazy, the authors know that at least d’ of A’s servers were outside of S during the entire phase. 

Armed with these tools (the marking and the probability vector), the adversary can generate a sequence such that the expected cost of each phase to A is H,,-l, and the cost to the optimum off-line algorithm is 1.