Amortized efficiency of list update and paging rules
Communications of the ACM
Journal of Algorithms
Competitive paging with locality of reference
Selected papers of the 23rd annual ACM symposium on Theory of computing
Strongly Competitive Algorithms for Paging with Locality of Reference
SIAM Journal on Computing
Online computation and competitive analysis
Online computation and competitive analysis
The working set model for program behavior
Communications of the ACM
On paging with locality of reference
Journal of Computer and System Sciences
On adequate performance measures for paging
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
On the separation and equivalence of paging strategies
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
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
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The competitive ratio is the most common metric in online algorithm analysis. Unfortunately, it produces pessimistic measures and often fails to distinguish between paging algorithms that have vastly differing performance in practice. An apparent reason for this is that the model does not take into account the locality of reference evidenced by actual input sequences. Therefore many alternative measures have been proposed to overcome the observed shortcomings of competitive analysis in the context of paging algorithms. While a definitive answer to all the concerns has yet to be found, clear progress has been made in identifying specific flaws and possible fixes for them. In this paper we consider two previously proposed models of locality of reference and observe that even if we restrict the input to sequences with high locality of reference in them the performance of every on-line algorithm in terms of the competitive ratio does not improve. Then we prove that locality of reference is useful under some other cost models, which suggests that a new model combining aspects of both proposed models can be preferable. We also propose a new model for locality of reference and prove that the randomized marking algorithm has better fault rate on sequences with high locality of reference. Finally we generalize the existing models to several variants of the caching problem.