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 Discovering Optimal Transmission Path Based on Genetic Algorithm for Time Sensitive Traffic in Software-Defined Networks 


Vol. 48,  No. 7, pp. 816-825, Jul.  2023
10.7840/kics.2023.48.7.816


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  Abstract

Time sensitive traffic refers to traffic that meets requirements such as low jitter, low packet loss rate, and low delay in transmission and reception. To meet these requirements, it is essential to find the optimal transmission path within the network. In this paper, we construct a network in the form of Software-Defined Network (SDN), and through it, we enable control with a global perspective on the network. Next, we propose an algorithm to explore the optimal path for time sensitive traffic transmission using genetic algorithms (GA). In addition, it was confirmed that this algorithm showed very high efficiency in terms of time while having the level of accuracy of the actual optimal path derived by searching through dynamic programming (DP). Finally, when the path found through this algorithm is applied to the SDN topology, it was confirmed that the jitter, packet loss rate, and delay are significantly lower than that of the transmission path provided by the controller.

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[IEEE Style]

S. Lee, H. Joo, H. Kim, "Discovering Optimal Transmission Path Based on Genetic Algorithm for Time Sensitive Traffic in Software-Defined Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 7, pp. 816-825, 2023. DOI: 10.7840/kics.2023.48.7.816.

[ACM Style]

Seunghwan Lee, Hyeontae Joo, and Hwangnam Kim. 2023. Discovering Optimal Transmission Path Based on Genetic Algorithm for Time Sensitive Traffic in Software-Defined Networks. The Journal of Korean Institute of Communications and Information Sciences, 48, 7, (2023), 816-825. DOI: 10.7840/kics.2023.48.7.816.

[KICS Style]

Seunghwan Lee, Hyeontae Joo, Hwangnam Kim, "Discovering Optimal Transmission Path Based on Genetic Algorithm for Time Sensitive Traffic in Software-Defined Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 7, pp. 816-825, 7. 2023. (https://doi.org/10.7840/kics.2023.48.7.816)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880