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)

Taichung, Taiwan, November 16, 2021

16:30 - 21:00 (GMT+8)

09:30 - 14:00 (GMT+1)

03:30 - 08:00 (GMT-5)

Conference Website: https://www.bigmm.org/ (November 15-17)

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The workshop will solicit original and unpublished research achievements in various aspects, including, but not limited to, the following topics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

Keynote Schedule

Session 1 (16:40 - 18:20, GMT+8) [Opening Slides]

Coffee Break (18:20 - 19:10, GMT+8)

Session 2 (19:10 - 21:10, GMT+8) [Closing Slides]

Workshop Co-Chairs

Chung-Ying Huang Ph.D., Professor, Department of Computer Science, National Yang Ming Chiao Tung University, Taiwan

Chih-Fan Hsu Ph.D., Senior Data Scientist, Inventec Corporation, Taiwan

Xin Liu Ph.D., Professor, Department of Computer Science, University of California, Davis, United States

Technical Program Committee

• Roger Zimmermann, Professor, Department of Computer Science, National University of Singapore, Singapore

• Hung-Hsuan Chen, Associate Professor, Department of Computer Science, National Central University, Taiwan

• Wei Tsang Ooi, Associate Professor, Department of Computer Science, National University of Singapore, Singapore

• Yong CUI, Associate Professor, Department of Computer Science and Technology, Tsinghua University, China

• Christian Timmerer, Associate Professor, Department of Information Technology, Alpen-Adria-Universität Klagenfurt, Austria

• Hwai-Jung Hsu, Assistant Professor, Department of Information Engineering and Computer Science, Feng Chia University, Taiwan

• Ming-Hung Wang, Assistant Professor, Department of Computer Science, National Chung Cheng University, Taiwan

• Fu-Yin Cherng, Assistant Professor, Department of Computer Science, National Chung Cheng University, Taiwan

• Jing-Kai Lou, Manager, KKStream Technologies Co., Ltd, Taiwan

• Chia-Ching Lin, Ph.D. Candidate, Department of Computer Science, National Taiwan University, Taiwan

Submission of Manuscript

Papers should be formatted in IEEE-style format (template) 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

• Extended Submission Deadline: October 6, 2021 PDT

• Acceptance Notification Date: October 20, 2021 PDT

• Camera Ready Deadline: October 27, 2021 PDT