GMSys 2023: First International ACM Green Multimedia Systems Workshop

7 – 10 June 2023, Vancouver, Canada

Call For Submissions

The threat of climate change requires a drastic reduction of global greenhouse gas (GHG) emissions in several societal spheres. Thus, this also applies to reducing and rethinking energy consumption of digital technologies. Video streaming technology is responsible for more than half of digital technology’s global impact [ref]. There is rapid growth, also now with digital and remote work has become more mainstream, in the amount of video data volume, processing of video content, and streaming which affects the rise of energy consumption and its associated GHG emissions.

The processes from video encoding, transmission, decoding, and displaying on the end user’s screen require a non-negligible amount of electricity – it starts with computational resources for video frame processing (encoding, compression), transmission, and decoding (decompression, error correction, and compensation, etc.) and consumption (video effects, etc.). There is also significant growth in video resolutions and hence higher bitrates, and the fact that this content is ubiquitously accessible anytime and everywhere with mobile devices and through high internet speed (e.g., 5G). These factors altogether inevitably cause a higher consumption of computation, distribution, and transmission resources. Therefore, there is a need to explore methods to make video encoding, transmission, and decoding greener without compromising quality. Tackling the challenge of reducing resource consumption end-to-end also brings direct opportunities to reduce the overall energy consumption in the whole video processing chain. Such challenges are: Developing video compression methods to minimize the decoding energy on user devices, designing energy management strategies to improve energy performance on cloud servers, developing algorithms helping to improve video encoding and decoding energy efficiency optimizing their usage of the underlying platform, e.g., CPUs, select the most energy-efficient network channel for video streaming, approaches to lower data volumes produced by video content, Artificial Intelligence (AI) techniques leveraging to calculate expected encoding energy consumption.

The International Workshop on Green Multimedia Systems 2023 aims to bring together experts and researchers to present and discuss recent developments and challenges for energy reduction in multimedia systems. This workshop focuses on innovations, concepts, and energy-efficient solutions from video generation to processing, delivery, and further usage. Please see the Call for Paper.

Content Generation, Processing & Provisioning
- Creation and production tool designs that promote and enable energy efficiency
- Energy usage analysis for video encoding in the cloud
- Tradeoffs between QoE-optimized video encoding and energy consumption
- Energy-efficient management of cloud computing systems
- Resource and energy-efficient job scheduling in cloud computing
- Optimized energy models and resource provisioning for video encoding
- Energy-efficient video encoding across the edge-cloud continuum
- AI-based resource allocation for climate-friendly video encoding
- Leveraging new cloud platform features (hardware) to improve video encoding energy efficiency
- Energy efficiency gains in dedicated hardware units (e.g., CPU, GPU) for video encoding
Video Delivery
- Energy usage analysis for video streaming, routers, switches, and network channels
- Design, analysis, and evaluation of adaptive bitrate (ABR) algorithms for Green video streaming
- Green video streaming over 5G and 6G networks
- Low-latency, quality, and energy-aware video streaming
- AI and machine learning approaches for energy efficiency in video communication networks
- Energy efficient approaches for video caching distribution at multiple locations, e.g., CDNs
- Green and QoE-driven network management & monitoring, including application layer QoS
Video Consumption & QoE
- Energy usage analysis for decoding and displaying video on user devices
- High perceived video quality at low energy consumption
- Energy-efficient video decoding techniques
- AI approaches for analyzing and influencing user behavior to optimize energy consumption
- User engagement, QoE, and its relation to energy consumption
- Understanding user behavior and habits, e.g., “willingness-to-greener-consumption”
- Empowering users to utilize green multimedia services

Submission Guideline

- Full/research papers: up to 6 pages, including references
- Short/industry position paper: 1-2 page(s) (+1 for references, if any)
- Papers must include author names and affiliations for single-blind peer reviewing by the program committee, using ACM style format

Important Dates

Paper Submission: March 10, 2023 (submit your paper here)
Notification: March 31, 2023
Camera ready deadline: April 17, 2023

Organizing Committee

Co-Chairs

Samira Afzal, Post-Doctoral researcher, Alpen-Adria-Universität Klagenfurt, Austria
Simone Ferlin-Reiter, Senior performance engineer, Red Hat AB and Karlstad University, Sweden
Tobias Hoßfeld, Full Professor, Chair of Communication Networks, University of Würzburg, Germany
Christian Timmerer, Full Professor, Director Christian Doppler Lab ATHENA, Alpen-Adria-Universität Klagenfurt, Austria

Innovative Event Programming Chair

Raimund Schatz, Austrian Institute of Technology, Austria

Technical Program Committee

Ali C. Begen, Ozyegin University, Turkey
Abdelhak Bentaleb, Concordia University
Alexander Raake, Technische Universität Ilmenau, Germany
Christian Timmerer, Alpen-Adria-Universität Klagenfurt, Austria
Christian Herglotz, Friedrich-Alexander-Universität, Germany
Cormac Sreenan, University College Cork, Ireland
Franco Davoli, University of Genoa, Italy
Farzad Tashtarian, Alpen-Adria-Universität Klagenfurt, Austria
Hadi Amirpour, Alpen-Adria-Universität Klagenfurt, Austria
Hatem Abou-Zeid, University of Calgary, Canada
Hamed Zolghadri Jahromi, Netverge, Canada
Jiyan Wu, OmniVision Technologies Inc, Singapore
Katrien de Moor, Norwegian University of Science and Technology, Norway
Mickaël Raulet, ATEME, France
Ozgu Alay, University of Oslo, Norway
Prashant Shenoy, University of Massachusetts, Amherst, USA
Radu Prodan, Alpen-Adria-Universität Klagenfurt, Austria
Raimund Schatz, Austrian Institute Of Technology, Austria
Simone Ferlin-Reiter, Red Hat AB and Karlstad University, Sweden
Tobias Hoßfeld, University of Würzburg, Germany
Thomas Zinner, Norwegian University of Science and Technology, Norway
Tian Guo, Worcester Polytechnic Institute, USA
Werner Robitza, AVEQ, Austria
Zhi Li, Netflix, United States