| Title | Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Grochol, D., Sekanina, L. |
| Conference Name | 2020 IEEE Congress on Evolutionary Computation (CEC) |
| Date Published | jul |
| Keywords | Cartesian genetic programming, compositionality, computer network, evolutionary computation, genetic algorithms, genetic programming, hash algorithms, Hash Function, high-quality network flow hashing, high-speed network systems, Internet protocol, IP networks, IPv6 flow hashing, IPv6 network flow hashing, linear genetic programming, Monitoring, multiobjective evolutionary design method, network flow, network monitoring probes, nondominated sorting genetic algorithm II, pubcrawl, Resiliency, Sorting, Task Analysis, Throughput, transport protocols |
| Abstract | Fast and high-quality network flow hashing is an essential operation in many high-speed network systems such as network monitoring probes. We propose a multi-objective evolutionary design method capable of evolving hash functions for IPv4 and IPv6 flow hashing. Our approach combines Cartesian genetic programming (CGP) with Non-dominated sorting genetic algorithm II (NSGA-II) and aims to optimize not only the quality of hashing, but also the execution time of the hash function. The evolved hash functions are evaluated on real data sets collected in computer network and compared against other evolved and conventionally created hash functions. |
| DOI | 10.1109/CEC48606.2020.9185723 |
| Citation Key | grochol_evolutionary_2020 |
Evolutionary Design of Hash Functions for IPv6 Network Flow Hashing