Abstract
The concept of extended cloud requires efficient network infrastructure to support ecosystems reaching form the edge to the cloud(s). Standard network load balancing delivers static solutions that are insufficient for the extended clouds, where network loads change often. To address this issue, a genetic algorithm based load optimizer is proposed and implemented. Next, its performance is experimentally evaluated and it is shown that it outperforms other existing solutions.
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Acknowledgements
Work of Marek Bolanowski and Andrzej Paszkiewicz is financed by the Minister of Education and Science of the Republic of Poland within the “Regional Initiative of Excellence” program for years 2019-2023. Project number 027/RID/2018/19, amount granted 11 999 900 PLN. Work of Maria Ganzha and Marcin Paprzycki was funded in part by the European Commission, under the Horizon Europe project ASSIST-IoT, grant number 957258.
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Bolanowski, M., Gerka, A., Paszkiewicz, A., Ganzha, M., Paprzycki, M. (2023). Application of Genetic Algorithm to Load Balancing in Networks with a Homogeneous Traffic Flow. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 14074. Springer, Cham. https://doi.org/10.1007/978-3-031-36021-3_32
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