DeepComfort: Energy-efficient thermal comfort control in buildings via reinforcement learning
Heating, ventilation, and air conditioning (HVAC) are extremely energy consuming,
accounting for 40% of total building energy consumption. It is crucial to design some energy …
accounting for 40% of total building energy consumption. It is crucial to design some energy …
[HTML][HTML] Video transcoding for adaptive bitrate streaming over edge-cloud continuum
G Gao, Y Wen - Digital Communications and Networks, 2021 - Elsevier
Video transcoding is to create multiple representations of a video for content adaptation. It is
deemed as a core technique in Adaptive BitRate (ABR) streaming. How to manage video …
deemed as a core technique in Adaptive BitRate (ABR) streaming. How to manage video …
{SENSEI}: Aligning video streaming quality with dynamic user sensitivity
This paper aims to improve video streaming by leveraging a simple observation—users are
more sensitive to low qualityin certain parts of a video than in others. For instance, re …
more sensitive to low qualityin certain parts of a video than in others. For instance, re …
Intersecting realms: a cross-disciplinary examination of VR quality of experience research
The advent of virtual reality (VR) technology has necessitated a reevaluation of quality of
experience (QoE) models. While numerous recent efforts have been dedicated to creating …
experience (QoE) models. While numerous recent efforts have been dedicated to creating …
When wireless video streaming meets AI: A deep learning approach
Wireless multimedia big data contains valuable information on users' behavior, content
characteristics and network dynamics, which can drive system design and optimization. The …
characteristics and network dynamics, which can drive system design and optimization. The …
Towards data-efficient continuous learning for edge video analytics via smart caching
Continuous learning (CL) has recently been adopted into edge video analytics, gaining
huge success in maintaining high accuracy without constantly retraining DNN models by …
huge success in maintaining high accuracy without constantly retraining DNN models by …
Bandwidth-efficient edge video analytics via frame partitioning and quantization optimization
The surging penetration of video cameras drives the rapid growth of video frames processed
on the mobile edge. However, the scarce bandwidth and limited edge computing resources …
on the mobile edge. However, the scarce bandwidth and limited edge computing resources …
User-Centric Algorithms: Sculpting the Future of Adaptive Video Streaming
K Khan - … Transactions on Electrical Engineering and Computer …, 2023 - iteecs.com
This paper explores the transformative potential of user-centric algorithms in shaping the
future landscape of adaptive video streaming. Traditional streaming methods, though …
future landscape of adaptive video streaming. Traditional streaming methods, though …
Deep Reinforcement Learning‐Based Collaborative Video Caching and Transcoding in Clustered and Intelligent Edge B5G Networks
Z Wan, Y Li - Wireless Communications and Mobile Computing, 2020 - Wiley Online Library
In the next‐generation wireless communications system of Beyond 5G networks, video
streaming services have held a surprising proportion of the whole network traffic …
streaming services have held a surprising proportion of the whole network traffic …
Successor Feature-Based Transfer Reinforcement Learning for Video Rate Adaptation with Heterogeneous QoE Preferences
In adaptive video streaming, the design of an adaptive bitrate (ABR) strategy is critical for the
quality-of-experience (QoE) perceived by users. Though current learning-based ABR …
quality-of-experience (QoE) perceived by users. Though current learning-based ABR …