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Average Case Analyses of List Update Algorithms, with Applications to Data Compression
 

Summary: Average Case Analyses of List Update Algorithms, with
Applications to Data Compression
Susanne Albers Michael Mitzenmachery
Abstract
We study the performance of the Timestamp(0) (TS(0)) algorithm for self-organizing
sequential search on discrete memoryless sources. We demonstrate that TS(0) is better
than Move-to-front on such sources, and determine performance ratios for TS(0) against
the optimal o ine and static adversaries in this situation. Previous work on such sources
compared online algorithmsonly to static adversaries. One practical motivationfor our work
is the use of the Move-to-front heuristic in various compression algorithms. Our theoretical
results suggest that in many cases using TS(0) in place of Move-to-front in schemes that use
the latter should improve compression. Tests using implementations on a standard corpus
of test documents demonstrate that TS(0) leads to improved compression.
Keywords: Online Algorithms, Competitive Analysis, List Update Problem, Prob-
ability Distribution, Data Compression, Entropy.
1 Introduction
We study deterministic online algorithms for self-organizing sequential search. Consider a set of
n items x1;x2;:::;xn that are stored in an unsorted linear linked list. At any instant of time, an
algorithm for maintaining this list is presented with a request that speci es one of the n items.
The algorithm must serve this request by accessing the requested item. That is, the algorithm

  

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

 

Collections: Computer Technologies and Information Sciences