SenseQ: Context-Aware Video Quality Adaptation for Optimal Mobile Video Streaming in Dynamic Environments
The growth of the mobile device and video streaming market has led to a significant increase in mobile video streaming as a primary mode of media consumption over the Internet. Mobile video streaming systems operate in dynamic environments and contexts that can change over time, posing challenges fo...
Main Authors: | Duin Baek, Youngchan Lim, Jihoon Ryoo |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10401160/ |
Similar Items
-
Integrating Visual and Network Data with Deep Learning for Streaming Video Quality Assessment
by: George Margetis, et al.
Published: (2023-04-01) -
Deep Reinforcement Learning-Based Approach for Video Streaming: Dynamic Adaptive Video Streaming over HTTP
by: Naima Souane, et al.
Published: (2023-10-01) -
On the Identification and Prediction of Stalling Events to Improve QoE in Video Streaming
by: J.-M. Martinez-Caro, et al.
Published: (2021-03-01) -
QoE-Driven Resource Allocation for Live Video Streaming Over D2D-Underlaid 5G Cellular Networks
by: Jihyeok Yun, et al.
Published: (2018-01-01) -
Data analysis on video streaming QoE over mobile networks
by: Qingyong Wang, et al.
Published: (2018-07-01)