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A distributed Front-end Edge node assessment model by using Fuzzy and a learning-to-rank method-machine learning.

, and . (January 2019)

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When machine learning meets Network Management and Orchestration in Edge-based networking paradigms., , and . J. Netw. Comput. Appl., (March 2023)From statistical- to machine learning-based network traffic prediction., , , and . Trans. Emerg. Telecommun. Technol., (2022)QARIMA: A new approach to prediction in queue theory., , , and . Appl. Math. Comput., (2014)Internet Traffic Classification Using an Ensemble of Deep Convolutional Neural Networks., , , and . FlexNets@SIGCOMM, page 38-43. ACM, (2021)Last significant trend change detection method for offline poisson distribution datasets., , and . ISNCC, page 1-7. IEEE, (2017)AMbit: An Efficient Pruning Technique in Federated Learning for Edge Computing Systems., , , , and . ICFEC, page 1-10. IEEE, (2024)FLITC: A Novel Federated Learning-Based Method for IoT Traffic Classification., , and . SMARTCOMP, page 206-212. IEEE, (2022)A Review on the effects of IoT and Smart Cities Technologies on Urbanism., , and . SEEDA-CECNSM, page 1-8. IEEE, (2018)A distributed Front-end Edge node assessment model by using Fuzzy and a learning-to-rank method-machine learning., and . (January 2019)Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A Survey., , and . Comput. Commun., (2021)