Pseudorandom number generators (PRNGs) are an essential tool in many areas, including simulation studies of stochastic processes, modeling, randomized algorithms, and games. The performance of any PRNGs depends on the quality of the generated random sequences; they must be generated quickly and have good statistical properties. Several statistical test suites have been developed to evaluate a single stream of random numbers, such as TestU01, DIEHARD, the tests from the SPRNG package, and a set of tests designed to evaluate bit sequences developed at NIST. TestU01 provides batteries of test that are sets of the mentioned suites. The predefined batteries are SmallCrush (10 tests, 16 p-values) that runs quickly, Crush (96 tests, 187 p-values) and BigCrush (106 tests, 2254 p-values) batteries that take longer to run. Most pseudorandom generators use recursion to produce sequences of numbers that appear to be random. The linear congruential generator is one of the well-known pseudorandom generators, the next number in the random sequences is determined by the previous one. The recurrences start with a value called the seed. Each time a recurrence starts with the same seed the same sequence is produced. This thesis develops a new pseudorandom number generation scheme that produces random sequences with good statistical properties via scrambling linear congruential generators. The scrambling technique is based on a simplified version of Feistel network, which is a symmetric structure used in the construction of cryptographic block ciphers. The proposed research seeks to improve the quality of the linear congruential generators’ output streams and to break up the regularities existing in the generators. / A Dissertation submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2017. / May 4, 2017. / Feistel network, Linear congruential generators, Pseudorandom numbers / Includes bibliographical references. / Michael Mascagni, Professor Directing Dissertation; Dennis Duke, University Representative; Ashok Srinivasan, Committee Member; Robert van Engelen, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_552025 |
| Contributors | Aljahdali, Asia Othman (authoraut), Mascagni, Michael (professor directing dissertation), Duke, D. W. (Dennis W.) (university representative), Srinivasan, Ashok (Professor of Computer Science) (committee member), van Engelen, Robert (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Computer Science (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (167 pages), computer, application/pdf |
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