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
A locally adaptive data compression scheme
Communications of the ACM
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STOC '85 Proceedings of the seventeenth annual ACM symposium on Theory of computing
Improved randomized on-line algorithms for the list update problem
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
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SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Average Case Analyses of List Update Algorithms, with Applications to Data Compression
ICALP '96 Proceedings of the 23rd International Colloquium on Automata, Languages and Programming
Self-Organizing Data Structures with Dependent Accesses
ICALP '96 Proceedings of the 23rd International Colloquium on Automata, Languages and Programming
An Application of Self-organizing Data Structures to Compression
SEA '09 Proceedings of the 8th International Symposium on Experimental Algorithms
Lists on lists: a framework for self-organizing lists in environments with locality of reference
WEA'06 Proceedings of the 5th international conference on Experimental Algorithms
Parameterized analysis of paging and list update algorithms
WAOA'09 Proceedings of the 7th international conference on Approximation and Online Algorithms
Paging and list update under bijective analysis
Journal of the ACM (JACM)
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We consider the online list accessing problem and present a new family of competitive-optimal deterministic list update algorithms which is the largest class of such algorithms known to-date. This family, called SORT-BY-RANK (SBR), is parametrized with a real 0 ≤ α ≤ 1, where SBR(0) is the MOVE-TO-FRONT algorithm and SBR(1) is equivalent to the TIMESTAMP algorithm. The behaviour of SBR(α) mediates between the eager strategy of MOVE-TO-FRONT and the more conservative behaviour of TIMESTAMP. We also present a family of algorithms SORT-BY-DELAY (SBD) which is parametrized by the positive integers, where SBD(1) is MOVE-TO-FRONT and SBD(2) is equivalent to TIMESTAMP. In general, SBD(k) is k- competitive for k ≥ 2. This is the first class of algorithms that is asymptotically optimal for independent, identically distributed requests while each algorithm is constant-competitive. Empirical studies with with both generated and real-world data are also included.