Using optimal Golomb rulers for minimizing collisions in closed hashing

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Abstract

We give conditions for hash table probing which minimize the expected number of collisions. A probing algorithm is determined by a sequence of numbers denoting jumps for an item during multiple collisions. In linear probing, this sequence consists of only ones - for each collision we jump to the next location. To minimize the collisions, it turns out that one should use the Golomb ruler conditions: consecutive partial sums of the jump sequence should be distinct. The commonly used quadratic probing scheme fulfils the Golomb condition for some cases. We define a new probing scheme - Golomb probing - that fulfills the Golomb conditions for a much larger set of cases. Simulations show that Golomb probing is always better than quadratic and linear and in some cases the collisions can be reduced with 25% compared to quadratic and with more than 50% compared to linear. © Springer-Verlag Berlin Heidelberg 2004.

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APA

Lundberg, L., Lennerstad, H., Klonowska, K., & Gustafsson, G. (2004). Using optimal Golomb rulers for minimizing collisions in closed hashing. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3321, 157–168. https://doi.org/10.1007/978-3-540-30502-6_11

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