A comprehensive survey on machine learning for networking: evolution, applications and research opportunities

R Boutaba, MA Salahuddin, N Limam, S Ayoubi… - Journal of Internet …, 2018 - Springer
Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

Survey on machine learning for intelligent end-to-end communication toward 6G: From network access, routing to traffic control and streaming adaption

F Tang, B Mao, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The end-to-end quality of service (QoS) and quality of experience (QoE) guarantee is quite
important for network optimization. The current 5G and conceived 6G network in the future …

A survey on bitrate adaptation schemes for streaming media over HTTP

A Bentaleb, B Taani, AC Begen… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
In this survey, we present state-of-the-art bitrate adaptation algorithms for HTTP adaptive
streaming (HAS). As a key distinction from other streaming approaches, the bitrate …

A survey on quality of experience of HTTP adaptive streaming

M Seufert, S Egger, M Slanina, T Zinner… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
Changing network conditions pose severe problems to video streaming in the Internet. HTTP
adaptive streaming (HAS) is a technology employed by numerous video services that …

Efficient device scheduling with multi-job federated learning

C Zhou, J Liu, J Jia, J Zhou, Y Zhou, H Dai… - Proceedings of the AAAI …, 2022 - ojs.aaai.org
Recent years have witnessed a large amount of decentralized data in multiple (edge)
devices of end-users, while the aggregation of the decentralized data remains difficult for …

QoE-driven rate adaptation heuristic for fair adaptive video streaming

S Petrangeli, J Famaey, M Claeys, S Latré… - ACM Transactions on …, 2015 - dl.acm.org
HTTP Adaptive Streaming (HAS) is quickly becoming the de facto standard for video
streaming services. In HAS, each video is temporally segmented and stored in different …

Multi-job intelligent scheduling with cross-device federated learning

J Liu, J Jia, B Ma, C Zhou, J Zhou… - … on Parallel and …, 2022 - ieeexplore.ieee.org
Recent years have witnessed a large amount of decentralized data in various (edge)
devices of end-users, while the decentralized data aggregation remains complicated for …

A review of predictive quality of experience management in video streaming services

MT Vega, C Perra, F De Turck… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Satisfying the requirements of devices and users of online video streaming services is a
challenging task. It requires not only managing the network quality of service but also to …

Seamless multimedia delivery within a heterogeneous wireless networks environment: Are we there yet?

R Trestian, IS Comsa, MF Tuysuz - … Communications Surveys & …, 2018 - ieeexplore.ieee.org
The increasing popularity of live video streaming from mobile devices, such as Facebook
Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the …

Survey on fair reinforcement learning: Theory and practice

P Gajane, A Saxena, M Tavakol, G Fletcher… - arXiv preprint arXiv …, 2022 - arxiv.org
Fairness-aware learning aims at satisfying various fairness constraints in addition to the
usual performance criteria via data-driven machine learning techniques. Most of the …