期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2017
卷号：7
期号：1
页码：521-525
DOI：10.11591/ijece.v7i1.pp521-525
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Cyclic Redundancy Codes (CRCs) are important for maintaining integrity in data transmissions. CRC performance is mainly affected by the polynomial chosen. Recent increases in data throughput require a foray into determining optimal polynomials through software or hardware implementations. Most CRC implementations in use, offer less than optimal performance or are inferior to their newer published counterparts. Classical approaches to determining optimal polynomials involve brute force based searching a population set of all possible polynomials in that set. This paper evaluates performance of CRC-polynomials generated with Genetic Algorithms. It then compares the resultant polynomials, both with and without encryption headers against a benchmark polynomial.
其他摘要：Cyclic Redundancy Codes (CRCs) are important for maintaining integrity in data transmissions. CRC performance is mainly affected by the polynomial chosen. Recent increases in data throughput require a foray into determining optimal polynomials through software or hardware implementations. Most CRC implementations in use, offer less than optimal performance or are inferior to their newer published counterparts. Classical approaches to determining optimal polynomials involve brute force based searching a population set of all possible polynomials in that set. This paper evaluates performance of CRC-polynomials generated with Genetic Algorithms. It then compares the resultant polynomials, both with and without encryption headers against a benchmark polynomial.
关键词：cyclic redundancy codes; data authentication; data integrity ; genetic algorithms; optimization
