Sridevi G M
@dsatm.com
Assistant Professor, Department of Information Science and Engineering
Dayananda Sagar Academy of Technology and Management
EDUCATION
Ph.D. in computer science and Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Information Systems, Computer Science, Computer Engineering, Software
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
G. M. Sridevi, Medahalli Ramakrishna, and DV Ashoka
Moldova State University
Most literature on hashing functions speaks in terms of hashing functions being either ‘good’ or ‘bad’. In this paper, we demonstrate how a hashing function that gives good results for one key set, performs badly for another. We also demonstrate that, for a single key set, we can find hashing functions that hash the keys with varying performances ranging from perfect to worst distributions. We present a study on the effect of changing the prime number ‘$p$’ on the performance of a hashing function from $H_1$ Class of Universal Hashing Functions. This paper then explores a way to characterize hashing functions by studying their performance over all subsets of a chosen Universe. We compare the performance of some popular hashing functions based on the average search performance and the number of perfect and worst-case distributions over different key sets chosen from a Universe. The experimental results show that the division-remainder method provides the best distribution for most key sets of the Universe when compared to other hashing functions including functions from $H_1$ Class of Universal Hashing Functions.
G M Sridevi, Ashoka D V, and B V Ajay Prakash
University of Kerbala - KIJOMS