Multimedia Communication

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A Webbing Journey @ Level Up 2023

Sebastian Uitz and Hannes Dermutz had an amazing time showcasing their highly anticipated game, A Webbing Journey, at the Level Up event at Messe Salzburg on July 1 and 2, 2023. The event was a vibrant gathering of game developers and enthusiasts, providing the perfect platform to connect with fellow game devs and experience many fantastic games.

At our booth, attendees had the opportunity to immerse themselves in the enchanting world of “A Webbing Journey” on the PC, Steam Deck, and Nintendo Switch. Players of all ages were captivated by the game’s endearing storyline and unique gameplay mechanics, embarking on a spider’s extraordinary adventure. The valuable feedback from the event-goers will be crucial in further refining and enhancing the game for its upcoming release.

In addition to the exhilarating gameplay experience, we had the privilege of sitting down for an insightful interview with the FM4 radio channel. It was an incredible opportunity to discuss the inspiration behind “A Webbing Journey” and delve into the game’s captivating features. We’re grateful for the chance to share our journey with a broader audience and promote the excitement surrounding our game.

IEEE Network Special Issue on Advancements in Network-Assisted Video Streaming: Optimization and Performance Analysis

Call for Papers

Network-assisted video streaming has become a substantial part of modern multimedia applications, enabling users to access high-quality video content over different networks, including the Internet and wireless networks. Efficiently delivering video content over networks poses numerous challenges, such as limited bandwidth, varying network conditions, heterogeneous end devices, and diverse user preferences. Network-assisted video streaming approaches leverage modern networking technologies, such as Software-Defined Networking (SDN), Network Function Virtualization (NFV), and edge computing, to not only improve the users’ Quality of Experience (QoE) but also enhance network utilization. Read more

The paper has been accepted for presentation in the Poster and Demo session and the workshop proceedings of Euro-Par 2023.

Title: Designing A Sustainable Serverless Graph Processing Tool on the Computing Continuum

Authors: Reza Farahani, Sashko Ristov, and Radu Prodan

29th International European Conference on Parallel and Distributed Computing, , LIMASSOL, CYPRUS, 28 August–1 September 2023

Abstract: Graph processing has become increasingly popular and essential for solving complex problems in various domains, like social networks. However, processing graphs at a massive scale poses critical challenges, such as inefficient resource and energy utilization. To bridge such challenges, the Graph-Massivizer project, funded by the Horizon Europe research and innovation program, conducts research and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph (MG) representation of extreme data. This paper presents an initial architectural design for the Choreographer, one of the five Graph-Massivizer tools. We explain Choreographer’s components and their collaboration with other Graph-Massivizer tools. We demonstrate how Choreographer can adopt the emerging serverless computing paradigm to process Basic Graph Operations (BGOs) as serverless functions across the computing continuum efficiently. Moreover, we present an early vision of our federated Function-as-a-Service (FaaS) testbed, which will be used to conduct experiments and assess Choreographer performance.

Josef Hammer presented at CCGRID + ICFEC 2023

Josef Hammer presented the poster “Unique Prefix vs. Unique Mask for Minimizing SDN Flows with Transparent Edge Access” at the 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023) and the paper “Scalable Transparent Access to 5G Edge Services” at the 7th IEEE International Conference on Fog and Edge Computing (ICFEC 2023), both in Bangalore, India.
Authors: Josef Hammer and Hermann Hellwagner – Alpen-Adria-Universität Klagenfurt
Abstract: The challenging demands for the next generation of the Internet of Things have led to a massive increase in edge computing and network virtualization technologies. One significant technology is Multi-access Edge Computing (MEC), a central piece of 5G telecommunication systems. MEC provides a cloud computing platform at the edge of the radio access network and is particularly essential to satisfy the challenging low-latency demands of future applications. Our previous publications argue that edge computing should be transparent to clients. We introduced an efficient solution to implement such a transparent approach, leveraging Software-Defined Networking (SDN) and virtual IP+port addresses for registered edge services. Building on our already efficient approach, in this work, we propose significant improvements to scale our transparent solution to large-scale real-world access networks. First, by improving the modularity of our SDN controller design, we enable various options to distribute both the SDN controller’s load and the switches’ flows. Second, we introduce the Unique Mask, a solution superior to the Unique Prefix presented in our previous work that considerably reduces the number of required flows in the switches. Our evaluations show that both algorithms perform very well, with the Unique Mask capable of reducing the number of flows by up to 98 %.
 
For more information about the research, visit the website: https://edge.itec.aau.at/.
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These three short papers presented at MHV´23 are published at ACM Digital Library

  • CP-Steering: CDN- and Protocol-Aware Content Steering Solution for HTTP Adaptive Video Streaming
    Reza Farahani (University of Klagenfurt, Austria), Abdelhak Bentaleb (Concordia University, Canada), Mohammad Shojafar (University of Surrey, UK), Hermann Hellwagner (University of Klagenfurt, Austria)
    https://dl.acm.org/doi/10.1145/3588444.3591044
  • Context-Aware HTTP Adaptive Video Streaming Utilizing QUIC’s Stream Priority
    Sindhu Chellappa (University of New Hampshire), Reza Farahani (University of Klagenfurt, Austria), Radim Bartos (University of New Hampshire, USA), Hermann Hellwagner (University of Klagenfurt, Austria)
    https://dl.acm.org/doi/10.1145/3588444.3591038
  • Which CDN to Download From? A Client and Server Strategies
    Abdelhak Bentaleb (Concordia University, Canada), Reza Farahani (University of Klagenfurt, Austria), Farzad Tashtarian (University of Klagenfurt, Austria), Hermann Hellwagner (University of Klagenfurt, Austria), Roger Zimmermann (National University of Singapore, Singapore)
    https://dl.acm.org/doi/10.1145/3588444.3591030

Reza Farahani gave talks on at Austrian Computer Sience Day (ACSD 2023)

Titles: Modern Network-Assisted Delivery of Adaptive Video Streaming Services and Towards Sustainable Servessless Processing of Massive Graphs on Computing Continuum

Link: https://springschool.iaik.tugraz.at/

Josef Hammer presented our work at NOMS 2023

Josef Hammer presented the paper “C3-Edge – An Automated Mininet-Compatible SDN Testbed On Raspberry Pis and Nvidia Jetsons” at the 36th IEEE/IFIP Network Operations and Management Symposium (NOMS 2023) in Miami, Florida, USA.

Authors: Josef Hammer, Dragi Kimovski, Narges Mehran, Radu Prodan, and Hermann Hellwagner – Alpen-Adria-Universität Klagenfurt

Abstract: The challenging demands for the next generation of the Internet of Things have led to a massive increase in edge computing and network virtualization technologies. While there is vast potential for research in these areas, managing complex adaptive infrastructure is difficult, and experiments with real hardware are tedious to set up. Furthermore, proposed solutions often require expensive hardware or labor-intensive procedures to replicate and build on these ideas. With our C3-Edge testbed, we address these challenges and propose a novel approach for automated edge testbed setup with a low-cost software-defined network and adaptive infrastructure configuration. We validated the efficiency of our approach on a real-world computing continuum infrastructure. The evaluation results confirm that our flexible approach is suitable for all but the most bandwidth-intensive applications.

Josef Hammer presented our work at NOMS 2023

For more information about the research, visit the website: https://edge.itec.aau.at/.

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Outstanding Poster Award (2nd Place) for Josef Hammer at the IPDPS PhD Forum 2023

Josef Hammer received the 2nd Place Outstanding Poster Award at the IPDPS PhD Forum 2023 for his poster titled “Distributed On-Demand Deployment for Transparent Access to 5G Edge Computing Services.” The event took place in St. Petersburg, Florida, USA, and was attended by Josef Hammer and Radu Prodan.

The recognition was part of the 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2023). For more information about the research and its contributors, visit the website: https://edge.itec.aau.at/.

 

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Josef Hammer presented his work at PAISE 2023

Josef Hammer presented the paper “Distributed On-Demand Deployment for Transparent Access to 5G Edge Computing Services” at the 5th Workshop on Parallel AI and Systems for the Edge (PAISE 2023). The workshop was held in conjunction with the 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2023) in St. Petersburg, Florida, USA.

Authors: Josef Hammer and Hermann Hellwagner, Alpen-Adria-Universität Klagenfurt

Abstract: Multi-access Edge Computing (MEC) is a central piece of 5G telecommunication systems and is essential to satisfy the challenging low-latency demands of future applications. MEC provides a cloud computing platform at the edge of the radio access network. Our previous publications argue that edge computing should be transparent to clients, leveraging Software-Defined Networking (SDN). While we introduced a solution to implement such a transparent approach, one question remained: How to handle user requests to a service that is not yet running in a nearby edge cluster? One advantage of the transparent edge is that one could process the initial request in the cloud. However, this paper argues that on-demand deployment might be fast enough for many services, even for the first request. We present an SDN controller that automatically deploys an application container in a nearby edge cluster if no instance is running yet. In the meantime, the user’s request is forwarded to another (nearby) edge cluster or kept waiting to be forwarded immediately to the newly instantiated instance. Our performance evaluations on a real edge/fog testbed show that the waiting time for the initial request – e.g., for an nginx-based service – can be as low as 0.5 seconds – satisfactory for many applications.

Josef Hammer presented his work at PAISE 2023

For more information about the research, visit the website: https://edge.itec.aau.at/.

Vignesh V Menon

Paper accepted: Transcoding Quality Prediction for Adaptive Video Streaming

2023 ACM Mile High Video (MHV) 

May 7-10, 2023 | Denver, US

Conference Website

Vignesh V Menon (Alpen-Adria-Universität Klagenfurt), Reza Farahani (Alpen-Adria-Universität Klagenfurt), Prajit T Rajendran (Universite Paris-Saclay), Mohammed Ghanbari (University of Essex), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt),  and Christian Timmerer (Alpen-Adria-Universität Klagenfurt).

Abstract:

In recent years, video streaming applications have proliferated the demand for Video Quality Assessment (VQA). Reduced reference video quality assessment (RR-VQA) is a category of VQA where certain features (e.g., texture, edges) of the original video are provided for quality assessment. It is a popular research area for various applications such as social media, online games, and video streaming. This paper introduces a reduced reference Transcoding Quality Prediction Model (TQPM) to determine the visual quality score of the video possibly transcoded in multiple stages. The quality is predicted using Discrete Cosine Transform (DCT)-energy-based features of the video (i.e., the video’s brightness, spatial texture information, and temporal activity) and the target bitrate representation of each transcoding stage. To do that, the problem is formulated, and a Long Short-Term Memory (LSTM)-based quality prediction model is presented. Experimental results illustrate that, on average, TQPM yields PSNR, SSIM, and VMAF predictions with an ?2 score of 0.83, 0.85, and 0.87, respectively, and Mean Absolute Error (MAE) of 1.31 dB, 1.19 dB, and 3.01, respectively, for single-stage transcoding.
Furthermore, an ?2 score of 0.84, 0.86, and 0.91, respectively, and MAE of 1.32 dB, 1.33 dB, and 3.25, respectively, are observed for a two-stage transcoding scenario. Moreover, the average processing time of TQPM for 4s segments is 0.328s, making it a practical VQA method in online streaming applications.