Self-adjusting binary search trees
Journal of the ACM (JACM)
A locally adaptive data compression scheme
Communications of the ACM
Operating systems: design and implementation
Operating systems: design and implementation
Skip lists: a probabilistic alternative to balanced trees
Communications of the ACM
An approximate analysis of the LRU and FIFO buffer replacement schemes
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Handbook of theoretical computer science (vol. A)
The LRU-K page replacement algorithm for database disk buffering
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A simulation study of IP switching
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
Algorithm Design and Software Libraries: Recent Developments in the LEDA Project
Proceedings of the IFIP 12th World Computer Congress on Algorithms, Software, Architecture - Information Processing '92, Volume 1 - Volume I
Opportunistic data structures with applications
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
A parameterizable methodology for Internet traffic flow profiling
IEEE Journal on Selected Areas in Communications
ISAAC '02 Proceedings of the 13th International Symposium on Algorithms and Computation
A data structure for a sequence of string accesses in external memory
ACM Transactions on Algorithms (TALG)
Dynamic optimality for skip lists and B-trees
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
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A dictionary data structure supports efficient search, insert, and delete operations on n keys from a totally ordered universe. Red-black trees, 2-3 trees, AVL trees, skip lists and other classic data structures facilitate O(logn) time search, insert and deletes, matching the information theoretic lower bound when access probabilities are uniform i.i.d. If access probabilities are non-uniform but still i.i.d., there are other weighted data structures such as D-trees, biased search trees, splay trees and treaps which can achieve optimality.In many applications, however, the source of nonuniformity in access probabilities is locality of reference: examples include memory, cache, disk and buffer management and emerging applications in internetwork traffic management. In such applications, the access probability of any given key is not i.i.d., but decreases with idle time since the last access to the key.It is possible to adjust the weighted dictionaries to achieve optimal search time even under time dependent distributions; however insert/delete times will be suboptimal at O(logn). In this paper, we present a lazy updating scheme which can be applied to weighted dictionaries to improve their amortized insert/delete performance when access probabilities decrease with time; optimality of search time is preserved. More speci%cally, let r(k) be the number of distinct keys accessed since the last access to key k- that is r(k) is the move-to-front rank of k. Let rmax(k) be the maximum rank of k during its lifetime. Then our lazy update scheme enables the abovementioned data structures to perform search in O(log r(k)) time and insert/delete in O(log rmax(k)) time. We illustrate our lazy update scheme in the context of a new Biased Skip List data structure and show that our bounds are optimal.