Amortized efficiency of list update and paging rules
Communications of the ACM
Amortized analyses of self-organizing sequential search heuristics
Communications of the ACM - Lecture notes in computer science Vol. 174
ACM Computing Surveys (CSUR)
A locally adaptive data compression scheme
Communications of the ACM
Self-organizing sequential search and Hilbert's inequalities
STOC '85 Proceedings of the seventeenth annual ACM symposium on Theory of computing
Two results on the list update problem
Information Processing Letters
Randomized algorithms
Improved Randomized On-Line Algorithms for the List Update Problem
SIAM Journal on Computing
Online computation and competitive analysis
Online computation and competitive analysis
On self-organizing sequential search heuristics
Communications of the ACM
SIAM Journal on Computing
Toward self-organizing linear search
SFCS '79 Proceedings of the 20th Annual Symposium on Foundations of Computer Science
On List Update with Locality of Reference
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
An Application of Self-organizing Data Structures to Compression
SEA '09 Proceedings of the 8th International Symposium on Experimental Algorithms
List update with locality of reference
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
List factoring and relative worst order analysis
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Parameterized analysis of paging and list update algorithms
WAOA'09 Proceedings of the 7th international conference on Approximation and Online Algorithms
A new perspective on list update: probabilistic locality and working set
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
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In this paper we study the performance of list update algorithms under arbitrary distributions that exhibit strict locality of reference and prove that Move-To-Front (MTF) is the best list update algorithm under any such distribution. We also show that the performance of MTF depends on the amount of locality of reference, while the performance of any static list update algorithm is independent of the amount of locality.