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Improved Randomized On-Line Algorithms for the List Update Problem
 

Summary: Improved Randomized On-Line Algorithms for the
List Update Problem
Susanne Albers
Abstract
The best randomized on-line algorithms known so far for the list update problem achieve
a competitiveness of
p
3 1:73. In this paper we present a new family of randomized on-line
algorithms that beat this competitive ratio. Our improved algorithms are called TIMESTAMP
algorithms and achieve a competitiveness of maxf2 p;1 + p(2 p)g, for any real number
p 2 0;1]. Setting p = (3
p
5)=2, we obtain a -competitive algorithm, where = (1+
p
5)=2
1:62 is the Golden Ratio. TIMESTAMP algorithms coordinate the movements of items using
some information on past requests. We can reduce the required information at the expense
of increasing the competitive ratio. We present a very simple version of the TIMESTAMP
algorithms that is 1:68-competitive. The family of TIMESTAMP algorithms also includes a
new deterministic 2-competitive on-line algorithm that is di erent from the MOVE-TO-FRONT

  

Source: Albers, Susanne - Institut für Informatik, Humboldt-Universität zu Berlin

 

Collections: Computer Technologies and Information Sciences