A comprehensive survey on machine learning for networking: evolution, applications and research opportunities
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 …
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
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 …
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
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 …
streaming (HAS). As a key distinction from other streaming approaches, the bitrate …
A survey on quality of experience of HTTP adaptive streaming
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 …
adaptive streaming (HAS) is a technology employed by numerous video services that …
Efficient device scheduling with multi-job federated learning
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 …
devices of end-users, while the aggregation of the decentralized data remains difficult for …
QoE-driven rate adaptation heuristic for fair adaptive video streaming
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 …
streaming services. In HAS, each video is temporally segmented and stored in different …
Multi-job intelligent scheduling with cross-device federated learning
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 …
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 …
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?
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 …
Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the …
Survey on fair reinforcement learning: Theory and practice
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 …
usual performance criteria via data-driven machine learning techniques. Most of the …