[icnrg] [CFP] IEEE International Workshop on Data-Driven Rate Control for Media Streaming (DDRC)

[Chih-Fan Hsu <[e-mail]>]

CALL FOR PAPERS

The 1st IEEE International Workshop on Data-Driven Rate Control for Media
Streaming (DDRC'21)

Co-located with the IEEE International Conference on Multimedia Big Data
(BigMM'21)

Workshop URL: https://sites.google.com/view/bigmm2021-ddrc

Workshop Co-Charis:

- Prof. Chung-Ying Huang, National Yang Ming Chiao Tung University, Taiwan
- Dr. Chih-Fan Hsu, Inventec Corporation, Taiwan
- Prof. Xin Liu, University of California, Davis, United States

While the usage of streaming services has skyrocketed due to the Covid-19
pandemics, sustaining good user experience is still challenging because of
the dynamics of network conditions, especially for extremely low-latency
applications. The first Data-Driven Rate Control for Media Streaming (DDRC)
workshop aims to present and discuss recent advances in data-driven rate
control technologies, including but not limited to low-latency scenarios
and real-time communication. It also advocates to explore and understand
the research challenges in new approaches for controlling the rate
according to user experience. Specifically, the workshop intends to address
the following objectives:

- Research challenges in developing new rate-control techniques for media
streaming services;
- New visions and concepts that will drive the evolution of rate control
mechanisms to avoid video/audio impairment caused by dynamic network
conditions; and
- Deployment challenges that arise when applying new rate control
mechanisms to mobile and desktop platforms.

With the workshop, we hope to foster interaction among researchers and
exchange new ideas by bringing together content, systems, and networking
communities with a specific focus on media streaming. The goal is to gather
active researchers and practitioners in this important field to gain
insight from their experiences and to inspire new approaches. Our ambition
in this incarnation is to bring together a wider group of researchers
involved in addressing data-driven rate control from different perspectives
including data collection, mechanism designs, and technology deployment. We
believe that a forum that allows experts in these communities to interact
with each other will support a more holistic approach to future research in
streaming. In addition, the workshop provides an exciting venue to discuss
existing challenges, best practices, and new ideas among the academic and
industrial communities in terms of introducing the data-driven rate control
model to support streaming.

Topics: The workshop will solicit original and unpublished research
achievements in various aspects, including, but not limited to, the
following topics

- Data-driven adaptive rate media solutions
- Cross-layer architectures and technologies for rate control
- Congestion control for media streaming
- Quality of experience for media streaming
- Performance study on streaming
- QoE and QoS estimation and measurement
- Design for subjective quality assessments
- Media streaming systems over heterogeneous networks and devices
- Realistic simulator based on real-world data

Submission of Manuscript: Papers should be formatted in IEEE-style format
and not longer than eight pages of text using 10 point size font on letter
paper. The page limit includes tables, figures, and references. Papers will
be peer-reviewed and selected based on their originality, technical merit,
and topical relevance. Authors should submit a PDF file at the submission
site: https://optimus.cs.nthu.edu.tw/bigmm_streaming/, following the
submission instructions on the workshop website.

Important Dates:

- Submission Deadline: September 22, 2021 PDT
- Acceptance Notification Date: October 20, 2021 PDT
- Camera Ready Deadline: October 27, 2021 PDT


Best,
DDRC Co-chair
Chih-Fan Hsu, Ph.D.