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The Application of Restricted Counter Schemes to Three Models of Linear Search

Published online by Cambridge University Press:  27 July 2009

Micha Hofri  and
Hadas Shachnai
Micha Hofri
Affiliation:
Department of Computer ScienceUniversity of Houston Houston, Texas 77204-3475
Hadas Shachnai
Affiliation:
Department of Computer ScienceTechnion-Israel Institute of Technology, Haifa 32000, Israel
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Abstract

The mechanism of the Counter Scheme (CS) has been shown to be an effective statistical approach for the reorganization of linear lists, where the records in the list are referenced independently with a time homogeneous multinomial distribution. In this paper we show that derivative schemes can be used effectively in other contexts as well. Specifically, we consider (a) linear lists that are doubly linked, so that they may be accessed at both ends, (b) multilists, which result from dissecting a linear list into several pieces that are accessed independently and reside in WORM (write-once-read-many) store, and (c) reorganizing a disk, by copying its contents to another disk, so as to minimize the expected seek time required to access a record.

Type
Articles
Information
Probability in the Engineering and Informational Sciences , Volume 6 , Issue 3 , July 1992 , pp. 371 - 389
Copyright
Copyright © Cambridge University Press 1992

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References

Bellow, M.E. (1987). An investigation of self-organizing heuristics for doubly linked lists. Allerton 25th Conference, pp. 64–65.Google Scholar
Carson, S.D. & Vongsathorn, P. (1989). Error bounds on disk arrangement using frequency information. Information Processing Letters 31: 209–213.CrossRefGoogle Scholar
Chung, F.R.K., Hajela, D.J., & Seymour, P.D. (1988). Self-organizing sequential search and Hilbert's inequalities. Journal of Computer and System Sciences 36:148–157.CrossRefGoogle Scholar
Courcoubetis, C. & Weber, R.R. (1990). The Move-To-Front rule for multiple lists. Probability in the Engineering and Informational Sciences 4: 19–27.CrossRefGoogle Scholar
Flajolet, P., Gardy, D., & Thimonier, L. (1988). Probabilistic Languages and Random Allocations. Proceedings of ICALP '88, Tempere, July 1988, published by Springer-Verlag as Lecture Notes in Computer Science 317: 239–253.Google Scholar
Hester, J.H. & Hirschberg, D.S. (1985). Self-organizing linear search. ACM Computing Surveys 17(3): 295–312.CrossRefGoogle Scholar
Hofri, M. & Shachnai, H. (1991). On the optimality of the counter scheme for dynamic linear lists. Information Processing Letters 37: 175–179.CrossRefGoogle Scholar
Hofri, M. & Shachnai, H. (1991). Self-organizing lists and independent references-A statistical synergy. Journal of Algorithms 12: 533–555.CrossRefGoogle Scholar
Hofri, M. & Shachnai, H. (05 1991). Partial information and its limited utility–The case of the reorganizing lists. Technical Report UH-CS-9 1–11, The Department of Computer Science, The University of Houston. (To appear in Stochastic Models.)Google Scholar
Makinen, E. (1988). On linear search heuristics. Information Processing Letters 29: 35–36.CrossRefGoogle Scholar
Matthews, D., Rothem, D., & Bretholz, E. (1980). Self-organizing doubly linked lists. International Journal of Computer Mathematics 8: 99–106.CrossRefGoogle Scholar
Oommen, B.J. & Hansen, E.R. (1987). List organizing strategies using stochastic move-to-front and stochastic move-to-rear operations. SIAM Journal of Computing 16(4): 705–716.CrossRefGoogle Scholar
Rivest, R. (1976). On self-organizing sequential search heuristics. Communications of the ACM 19(2): 63–67.CrossRefGoogle Scholar