Randomized Memoryless Algorithms for the Weighted and the Generalized k-server Problems

作     者：Chiplunkar, Ashish Vishwanathan, Sundar 

作者机构：Indian Inst Technol Delhi New Delhi 110016 India Indian Inst Technol Mumbai 400076 Maharashtra India 

出 版 物：《ACM TRANSACTIONS ON ALGORITHMS》 (运算法则学报)

年 卷 期：2020年第16卷第1期

页      面：14-14页

核心收录：

学科分类：07[理学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学] 

主　　题：Design and analysis of algorithms Caching and paging algorithms k-server algorithms 

摘      要：The weighted k-server problem is a generalization of the k-server problem wherein the cost of moving a server of weight A through a distance d is beta(i ). d. On uniform metric spaces, this models caching with caches having different page replacement costs. A memoryless algorithm is an online algorithm whose behavior is independent of the history given the positions of its k servers. In this article, we develop a framework to analyze the competitiveness of randomized memoryless algorithms. The key technical contribution is a method for working with potential functions defined implicitly as the solution of a linear system. Using this, we establish tight bounds on the competitive ratio achievable by randomized memoryless algorithms for the weighted k-server problem on uniform metrics. We first prove that there is an alpha(k)-competitive memoryless algorithm for this problem, where alpha(k) = alpha(2)(k-)(1) + 3 alpha(k-1 )+1 alpha(1)= 1. We complement this result by proving that no randomized memoryless algorithm can have a competitive ratio less than alpha(k). Finally, we prove that the above bounds also hold for the generalized k-server problem on weighted uniform metrics.