Deep neural network–based enhancement for image and video streaming systems: A survey and future directions

R Lee, SI Venieris, ND Lane - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual
apps spanning from on-demand movies and 360° videos to video-conferencing and live …

Loki: improving long tail performance of learning-based real-time video adaptation by fusing rule-based models

H Zhang, A Zhou, Y Hu, C Li, G Wang… - Proceedings of the 27th …, 2021 - dl.acm.org
Maximizing the quality of experience (QoE) for real-time video is a long-standing challenge.
Traditional video transport protocols, represented by a few deterministic rules, can hardly …

Learning tailored adaptive bitrate algorithms to heterogeneous network conditions: A domain-specific priors and meta-reinforcement learning approach

T Huang, C Zhou, RX Zhang, C Wu… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Internet adaptive video streaming is a typical form of video delivery that leverages adaptive
bitrate (ABR) algorithms to provide video services with high quality of experience (QoE) for …

Deep reinforcement learning with communication transformer for adaptive live streaming in wireless edge networks

S Wang, S Bi, YJA Zhang - IEEE Journal on Selected Areas in …, 2021 - ieeexplore.ieee.org
The emerging mobile edge computing (MEC) technology has been recently applied to
improve the Quality of Experience (QoE) of network services, such as live video streaming …

A workload-aware DVFS robust to concurrent tasks for mobile devices

C Lin, K Wang, Z Li, Y Pu - Proceedings of the 29th Annual International …, 2023 - dl.acm.org
Power governing is a critical component of modern mobile devices, reducing heat
generation and extending device battery life. A popular technology of power governing is …

{GRACE}:{Loss-Resilient}{Real-Time} video through neural codecs

Y Cheng, Z Zhang, H Li, A Arapin, Y Zhang… - … USENIX Symposium on …, 2024 - usenix.org
In real-time video communication, retransmitting lost packets over high-latency networks is
not viable due to strict latency requirements. To counter packet losses without …

HCFL: A high compression approach for communication-efficient federated learning in very large scale IoT networks

MD Nguyen, SM Lee, QV Pham… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-
Things (IoT) devices to learn a collaborative model without sending the raw data to …

BoB: Bandwidth prediction for real-time communications using heuristic and reinforcement learning

A Bentaleb, MN Akcay, M Lim… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Bandwidth prediction is critical in any Real-time Communication (RTC) service or
application. This component decides how much media data can be sent in real time …

Cloud-edge learning for adaptive video streaming in B5G internet-of-thing systems

H Zhan, L Fan, C Li, X Lei, F Li - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
The development of Internet of Things (IoT) networks causes an increasing demand for high-
quality video streaming, which results in the burden of traditional mobile cloud computing …

Artificial intelligence of things: A survey

SI Siam, H Ahn, L Liu, S Alam, H Shen, Z Cao… - ACM Transactions on …, 2025 - dl.acm.org
The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …