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Sizing Network Buffers: An HTTP Adaptive Streaming Perspective.

, , and . FiCloud Workshops, page 369-376. IEEE Computer Society, (2016)

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Enabling scalable emulation of differentiated services in mininet., , and . MMSys, page 240-245. ACM, (2022)MATURE: Multistage Throughput Prediction for Adaptive Video Streaming in Cellular Networks., , , and . NOSSDAV, page 15-21. ACM, (2024)goDASH - GO Accelerated HAS Framework for Rapid Prototyping., , and . QoMEX, page 1-4. IEEE, (2020)Quantifying the Impact of Base Station Metrics on LTE Resource Block Prediction Accuracy., , , , , and . INFOCOM Workshops, page 1-2. IEEE, (2023)Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks., , , , , , , and . SmartGridComm, page 284-289. IEEE, (2022)A Supervised Machine Learning Approach for DASH Video QoE Prediction in 5G Networks., , , , and . Q2SWinet, page 57-64. ACM, (2020)On Leveraging Machine and Deep Learning for Throughput Prediction in Cellular Networks: Design, Performance, and Challenges., , , , , , and . IEEE Commun. Mag., 58 (3): 11-17 (2020)Beyond throughput, the next generation: a 5G dataset with channel and context metrics., , , and . MMSys, page 303-308. ACM, (2020)SMASH: A Supervised Machine Learning Approach to Adaptive Video Streaming over HTTP., , , and . QoMEX, page 1-6. IEEE, (2020)Realistic video sequences for subjective QoE analysis., , , , and . MMSys, page 246-251. ACM, (2022)