Abstract
Polynomial hash functions are well studied and widely used in various applications. They have gained popularity because of certain performances they exhibit. It has been shown that even linear hash functions are expected to have such performances. However, quite often we would like the hash functions to be reliable, meaning that they perform well with high probability; for some certain important properties even higher degree polynomials were not known to be reliable. We show that for certain important properties linear hash functions are not reliable. We give indication that quadratic hash functions might not be reliable. On the positive side, we prove that cubic hash functions are reliable. In a more general setting, we show that higher degree of the polynomial hash functions translates into higher reliability. We also introduce a new class of hash functions, which enables to reduce the universe size in an efficient and simple manner. The reliability results and the new class of hash functions are used for some fundamental applications: improved and simplified reliable algorithms for perfect hash functions and real-time dictionaries, which use significantly less random bits, and tighter upper bound for the program size of perfect hash functions.
Partially supported by DFG Grain Me 872/1-4.
Partially supported by NSF grants CCR-9111348 and CCR 8906949.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
N. Alon, L. Babai, and A. Itai. A fast and simple randomized parallel algorithm for the maximal independent set problem. J. of Alg., 7:567–583, 1986.
L. J. Carter and M. N. Wegman. Universal classes of hash functions. JCSS, 18:143–154, 1979.
B. Chor and O. Goldreich. On the power of two-point based sampling. J. Complexity, 5:96–106, 1989.
M. Dietzfelbinger, A. R. Karlin, K. Mehlhorn, F. Meyer auf der Heide, H. Rohnert, and R. E. Tarian. Dynamic perfect hashing: Upper and lower bounds. Technical Report 70, Universität Paderborn, Gesamthochschule, Jan. 1991. Revised Version of the paper of the same title that appeared in FOCS '88, pp. 524–531.
M. Dietzfelbinger and F. Meyer auf der Heide. A new universal class of hash functions and dynamic hashing in real time. In ICALP '90 (LNCS 443), pp. 6–19, July 1990.
M. L. Fredman, J. Komlós, and E. Szemerédi. Storing a sparse table with O(1) worst case access time. J. ACM, 31(3):538–544, July 1984.
J. Gil and Y. Matias. Fast hashing on a PRAM-designing by expectation. In SODA '91, pp. 271–280, Jan. 1991.
J. Gil, Y. Matias, and U. Vishkin. Towards a theory of nearly constant time parallel algorithms. In FOCS '91, pp. 698–710.
C. T. M. Jacobs and P. van Emde Boas. Two results on tables. IPL, 22(1):43–48, 1986.
A. Joffe. On a set of almost deterministic k-independent random variables. The Annals of Prob., 2:161–162, 1974.
A. R. Karlin and E. Upfal. Parallel hashing-an efficient implementation of shared memory. In STOC '86, pp. 160–168.
D. E. Knuth. Sorting and Searching, volume 3 of The Art of Computer Programming.
C. P. Kruskal. L. Rudolph, and M. Snir. A complexity theory of efficient parallel algorithms. TCS, 71:95–132, 1990.
M. Luby. A simple parallel algorithm for the maximal independent set problem. SIAM J. Comput., 15(4):1036–1053, 1986.
H. G. Mairson. The program complexity of searching a table. In FOCS '83, pp. 40–75.
G. Markowsky, L. J. Carter, and M. N. Wegman. Analysis of a universal class of hash functions. In MFCS '78, pp. 345–354, 1978.
K. Mehlhorn. On the program size of perfect and universal hash functions. In FOCS '82, pp. 170–175.
K. Mehlhorn. Data Structures and Algorithms. Springer-Verlag, Berlin Heidelberg, 1984.
K. Mehlhorn and U. Vishkin. Randomized and deterministic simulations of PRAMs by parallel machines with restricted granularity of parallel memories. Acta Inf., 21:339–374, 1984.
N. Nisan. Pseudorandom generators for space-bounded computations. In STOC '90, pp. 204–212.
M. V. Ramakrishna and P.-A. Larson. File organization using composite perfect hashing. ACM Trans. Database Syst., 14(9);231–263. 1989.
A. G. Ranade. How to emulate shared memory. In FOCS '87, pp. 185–194.
A. G. Ranade, S. N. Bhatt, and S. L. Johnsson. The fluent abstract machine. In Proc. of the 5th MIT Conference on Advanced Research in VLSI, pp. 71–93, 1988.
J. P. Schmidt and A. Siegel. The spatial complexity of oblivious k-probe hash functions. SIAM J. Comput., 19(5):775–786, 1990.
A. Siegel. On universal classes of fast high performance hash functions, their time-space tradeoff, and their applications. In FOCS '89, pp. 20–25.
C. Slot and P. van Emde Boas. On tape versus core; an application of space efficient hash functions to the invariance of space. In STOC '84, pp. 391–400.
M. N. Wegman and L. J. Carter. New classes and applications of hash functions. In FOCS '79, pp. 175–182.
M. N. Wegman and L. J. Carter. New hash functions and their use in authentication and set equality. JCSS, 22:265–279, 1981.
A. C. Yao. Should tables be sorted? J. ACM, 28(3);615–628, July 1981.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1992 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dietzfelbinger, M., Gil, J., Matias, Y., Pippenger, N. (1992). Polynomial hash functions are reliable. In: Kuich, W. (eds) Automata, Languages and Programming. ICALP 1992. Lecture Notes in Computer Science, vol 623. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55719-9_77
Download citation
DOI: https://doi.org/10.1007/3-540-55719-9_77
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-55719-7
Online ISBN: 978-3-540-47278-0
eBook Packages: Springer Book Archive