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Guiltiness: A practical approach for quantifying virtual network functions performance.

, , , , , , , и . Comput. Networks, (2019)

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José Ricardo Pino Rivera

Humberto Jorge José

Nadine José Gonzalez

José Baena

José Teixeira

 

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Guiltiness: A practical approach for quantifying virtual network functions performance., , , , , , , и . Comput. Networks, (2019)Predicting Elephant Flows in Internet Exchange Point Programmable Networks., , , и . AINA, том 926 из Advances in Intelligent Systems and Computing, стр. 485-497. Springer, (2019)Refining Network Intents for Self-Driving Networks., , , и . SelfDN@SIGCOMM, стр. 15-21. ACM, (2018)Examining the Centralization of Email Industry: A Landscape Analysis for IPv4 and IPv6., , , и . ISCC, стр. 360-366. IEEE, (2023)Refining Network Intents for Self-Driving Networks., , , и . CoRR, (2020)AMNESiA: Affinity measurement platform for NFV-enabled networks., , , , , и . IM, стр. 899-900. IEEE, (2017)IDEAFIX: Identifying Elephant Flows in P4-Based IXP Networks., , , и . GLOBECOM, стр. 1-6. IEEE, (2018)Sample Selection Search to Predict Elephant Flows in IXP Programmable Networks., , , , и . AINA, том 1151 из Advances in Intelligent Systems and Computing, стр. 357-368. Springer, (2020)Affinity measurement for NFV-enabled networks: A criteria-based approach., , , , , и . IM, стр. 125-133. IEEE, (2017)Artificial neural network model to predict affinity for virtual network functions., , , , , и . NOMS, стр. 1-9. IEEE, (2018)