Amortized efficiency of list update and paging rules
Communications of the ACM
Competitive paging with locality of reference
Selected papers of the 23rd annual ACM symposium on Theory of computing
Online computation and competitive analysis
Online computation and competitive analysis
Best-fit bin-packing with random order
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
Bounding the diffuse adversary
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
On-line paging against adversarially biased random inputs
Journal of Algorithms
The working set model for program behavior
Communications of the ACM
SIAM Journal on Computing
SIAM Journal on Computing
On paging with locality of reference
Journal of Computer and System Sciences
The relative worst order ratio applied to paging
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
On adequate performance measures for paging
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
The relative worst order ratio for on-line algorithms
CIAC'03 Proceedings of the 5th Italian conference on Algorithms and complexity
Paging and list update under bijective analysis
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
On the relative dominance of paging algorithms
Theoretical Computer Science
A Comparison of Performance Measures for Online Algorithms
WADS '09 Proceedings of the 11th International Symposium on Algorithms and Data Structures
Introduction to the SIGACT news online algorithms column
ACM SIGACT News
On Developing New Models, with Paging as a Case Study
ACM SIGACT News
On the relative dominance of paging algorithms
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
Closing the gap between theory and practice: new measures for on-line algorithm analysis
WALCOM'08 Proceedings of the 2nd international conference on Algorithms and computation
On certain new models for paging with locality of reference
WALCOM'08 Proceedings of the 2nd international conference on Algorithms and computation
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
Outperforming LRU via competitive analysis on parametrized inputs for paging
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Parameterized analysis of paging and list update algorithms
WAOA'09 Proceedings of the 7th international conference on Approximation and Online Algorithms
On the absolute approximation ratio for First Fit and related results
Discrete Applied Mathematics
A new variable-sized bin packing problem
Journal of Scheduling
A comparison of performance measures via online search
FAW-AAIM'12 Proceedings of the 6th international Frontiers in Algorithmics, and Proceedings of the 8th international conference on Algorithmic Aspects in Information and Management
Paging and list update under bijective analysis
Journal of the ACM (JACM)
Relative interval analysis of paging algorithms on access graphs
WADS'13 Proceedings of the 13th international conference on Algorithms and Data Structures
The frequent items problem in online streaming under various performance measures
FCT'13 Proceedings of the 19th international conference on Fundamentals of Computation Theory
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It has been experimentally observed that LRU and variants thereof are the preferred strategies for on-line paging. However, under most proposed performance measures for on-line algorithms the performance of LRU is the same as that of many other strategies which are inferior in practice. In this paper we first show that any performance measure which does not include a partition or implied distribution of the input sequences of a given length is unlikely to distinguish between any two lazy paging algorithms as their performance is identical in a very strong sense. This provides a theoretical justification for the use of a more refined measure. Building upon the ideas of concave analysis by Albers et al. [AFG05], we prove strict separation between LRU and all other paging strategies. That is, we show that LRU is the unique optimum strategy for paging under a deterministic model. This provides full theoretical backing to the empirical observation that LRU is preferable in practice.