Principles of database buffer management
ACM Transactions on Database Systems (TODS)
Amortized efficiency of list update and paging rules
Communications of the ACM
Journal of Algorithms
Trans-dichotomous algorithms for minimum spanning trees and shortest paths
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
Competitive paging with locality of reference
Selected papers of the 23rd annual ACM symposium on Theory of computing
Memory versus randomization in on-line algorithms
IBM Journal of Research and Development
STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
Strongly Competitive Algorithms for Paging with Locality of Reference
SIAM Journal on Computing
Competitive analysis of randomized paging algorithms
Theoretical Computer Science
Succinct Dynamic Data Structures
WADS '01 Proceedings of the 7th International Workshop on Algorithms and Data Structures
Truly online paging with locality of reference
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Faster deterministic sorting and searching in linear space
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
IP over connection-oriented networks and distributional paging
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
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The paging problem is that of deciding which pages to keep in a cache of k pages to minimize the number of page faults for a two-level memory system. We consider efficient paging algorithms that require limited space and time on a unitcost RAM with word size w. We present an implementation of the randomized marking algorithm of Fiat et al. that uses only k + o(k) bits of space while supporting page requests in O(1) worst-case time. In addition, we present a novel k-competitive deterministic algorithm called Surely Not Recently Used (SNRU) that approximates the Least Recently Used (LRU) algorithm. For any constant 1/k 驴 驴 k驴 most recently requested pages are in the cache, while using only O(1/驴) worst-case time per request and 2k + o(k) bits of space.