Amortized efficiency of list update and paging rules
Communications of the ACM
Self-adjusting binary search trees
Journal of the ACM (JACM)
ACM Computing Surveys (CSUR)
Journal of Algorithms
The LRU-K page replacement algorithm for database disk buffering
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
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
Improved Randomized On-Line Algorithms for the List Update Problem
SIAM Journal on 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
Online list accessing algorithms and their applications: recent empirical evidence
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Experimental studies of access graph based heuristics: beating the LRU standard?
SODA '97 Proceedings of the eighth 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
Alternatives to splay trees with O(log n) worst-case access times
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Operating System Concepts
SIAM Journal on Computing
SIAM Journal on Computing
Improved Upper Bounds for Pairing Heaps
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
Two New Families of List Update Algorithms
ISAAC '98 Proceedings of the 9th International Symposium on Algorithms and Computation
On paging with locality of reference
Journal of Computer and System Sciences
Communications of the ACM - Designing for the mobile device
On the separation and equivalence of paging strategies
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
IEEE Transactions on Software Engineering
Dynamic optimality for skip lists and B-trees
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
On List Update with Locality of Reference
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
Paging and list update under bijective analysis
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
The relative worst order ratio for on-line algorithms
CIAC'03 Proceedings of the 5th Italian conference on Algorithms and complexity
List update with locality of reference
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Theoretical evidence for the superiority of LRU-2 over LRU for the paging problem
WAOA'06 Proceedings of the 4th international conference on Approximation and Online Algorithms
Introduction to the SIGACT news online algorithms column
ACM SIGACT News
On Developing New Models, with Paging as a Case Study
ACM SIGACT News
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
Optimal strategies for the list update problem under the MRM alternative cost model
Information Processing Letters
List update with probabilistic locality of reference
Information Processing Letters
A new perspective on list update: probabilistic locality and working set
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
Optimal lower bounds for projective list update algorithms
ACM Transactions on Algorithms (TALG)
| Hi-index | 0.00 |
It is well-established that input sequences for paging and list update have locality of reference. In this paper we analyze the performance of algorithms for these problems in terms of the amount of locality in the input sequence. We define a measure for locality that is based on Denning’s working set model and express the performance of well known algorithms in term of this parameter. This introduces parameterized-style analysis to online algorithms. The idea is that rather than normalizing the performance of an online algorithm by an (optimal) offline algorithm, we explicitly express the behavior of the algorithm in terms of two more natural parameters: the size of the cache and Denning’s working set measure. This technique creates a performance hierarchy of paging algorithms which better reflects their intuitive relative strengths. Also it reflects the intuition that a larger cache leads to a better performance. We obtain similar separation for list update algorithms. Lastly, we show that, surprisingly, certain randomized algorithms which are superior to MTF in the classical model are not so in the parameterized case, which matches experimental results.