International Conference on Visual Communications and Image Processing (IEEE VCIP’23)

http://www.vcip2023.org/

Authors: Vignesh V Menon, Reza Farahani, Prajit T Rajendran, Samira Afzal, Klaus Schoeffmann, Christian Timmerer

Abstract: With the emergence of multiple modern video codecs, streaming service providers are forced to encode, store, and transmit bitrate ladders of multiple codecs separately, consequently suffering from additional energy costs for encoding, storage, and transmission. To tackle this issue, we introduce an online energy-efficient Multi-Codec Bitrate ladder Estimation scheme (MCBE) for adaptive video streaming applications. In MCBE, quality representations within the bitrate ladder of new-generation codecs (e.g., HEVC, AV1) that lie below the predicted rate-distortion curve of the AVC codec are removed. Moreover, perceptual redundancy between representations of the bitrate ladders of the considered codecs is also minimized based on a Just Noticeable Difference (JND) threshold. Therefore, random forest-based models predict the VMAF of bitrate ladder representations of each codec. In a live streaming session where all clients support the decoding of AVC, HEVC, and AV1, MCBE achieves impressive results, reducing cumulative encoding energy by 56.45%, storage energy usage by 94.99%, and transmission energy usage by 77.61% (considering a JND of six VMAF points). These energy reductions are in comparison to a baseline bitrate ladder encoding based on current industry practice.

The Interactive Video Retrieval for Beginners (IVR4B) special session and competition took place on September 21, 2023, at the International Conference on Multimedia Indexing (CBMI2023) in Orleans, France. https://cbmi2023.org/

We are happy to announce that Klaus Schoeffmann could save the BEST KIS-VISUAL award for this competition, with his interactive video search system diveXplore.

 

 

 

 

 

 

From September 19-21, professors and students from the University of Klagenfurt met with FH Villach, FH St. Pölten, and HTL Villach students for the Future of Education Hackathon. During this event, they were split into three groups to work on concepts and solutions in AI, digital platform ecosystems, and gamification to solve various problems and improve the future of education. The gamification group consisted of Samuele and Elias from the master’s program Game Studies and Engineering and Noah and David from the HTL Villach for Informatics. Their supervisors during this event were Mathias Lux, Sebastian Uitz, and Wolfgang Hoi, with expert support from Fabian Schober on the event’s second day.

Throughout the 3 day event, they worked on a solution to utilize gamification to foster the development of skills, knowledge, and competencies and generate a motivating, clear, and exciting journey. Their solution consisted of a gamified study tracker, which tracks the student’s progress, recommends additional courses, and keeps the student motivated via quests and competition. This tracker is combined with the Study Buddy, an AI chatbot to interact with the student more naturally and ask them about their study, presents quests, and helps if the motivation drops. The final step of their solution was the “Job Tinder” which can be used to look for possible jobs in a fun way and which will recommend jobs based on the information gathered via the student tracker.

On the event’s last day, all solutions were pitched to a Jury, and after a lengthy discussion, the gamification team was elected as the winning team.

A video summary of this event is available via the following link. German only.

HACKATHON | The Future Of Education

 

The GraphMassivizer plenary meeting is underway in #Walldorf, hosted by our valued partner metaphacts GmbH

We’re thrilled to gather for three days of collaboration, sharing project results, and planning upcoming activities.

Radu Prodan, Laurentiu Vasiliu, Irina Schmidt, Roberta Turra, Peter Haase, Richard Lloyd Stevens, Alexandru Iosup, Ana-Lucia Varbanescu, Nuria De Lama, Reza Farahani.

From September 7-9, nearly 40 participants joined us at AAU Klagenfurt to discuss and theorise about the theme of “Video Game Cultures: Exploring New Horizons.” VGC is a recurring conference reinstated after the lockdowns, coordinated between universities and scholars from the US, UK, Czech Republic, Austria, and Germany. This year’s conference was an organisational collaboration between ITEC and the Department of English at AAU; Felix Schniz and René Schallegger were the local organising chairs. We had the pleasure to not only listen to a wonderful variety of perspectives and approaches from our participants in and around the field of Game Studies but also to cultivate a kind and constructive atmosphere. Many thanks to everyone who helped set up this year’s VGC, especially our sponsors!

 

Authors: Reza Saeedinia (University of Tehran), S. Omid Fatemi (University of Tehran),Daniele Lorenzi (Alpen-Adria Universität Klagenfurt), Farzad Tashtarian (Alpen-Adria Universität Klagenfurt),  Christian Timmerer (Alpen-Adria Universität Klagenfurt)

Abstract: Live user-generated content (UGC) has increased significantly in video streaming applications. Improving the quality of experience (QoE) for users is a crucial consideration in UGC live streaming, where a user can be both a subscriber and a streamer. Resource allocation is an NP-complete task in UGC live streaming due to many subscribers and streamers with varying requests, bandwidth limitations, and network constraints. In this paper, to decrease the execution time of the resource allocation algorithm, we first process streamers’ and subscribers’ requests and then aggregate them into a limited number of groups based on their preferences. Second, we
perform resource allocation for these groups that we call communities. We formulate the resource allocation problem for communities into an optimization problem. With an efficient aggregation of subscribers and streamers at the core of the proposed architecture, the computational complexity of the optimization problem is reduced, consequently improving QoE. This improvement occurs because of the prompt reaction to the bandwidth fluctuations and, subsequently, appropriate resource allocation by the proposed model. We conduct experiments in various scenarios. The results show an average of 41% improvement in execution time. To evaluate the impact of bandwidth fluctuations on the proposed algorithm, we employ two network traces: AmazonFCC and NYUBUS. The results show 4%, and 28% QoE improvement in a scenario with 5
streamers over the AmazonFCC and the NYUBUS network traces, respectively.

Link: 13th International Conference on Computer and Knowledge Engineering (ICCKE)

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

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.

 

Kurt Horvath presented the paper titled A distributed geofence-based discovery scheme for the computing Continuum at 29th International European Conference on Parallel and Distributed Computing (EURO-PAR 2023)

Authors: Kurt Horvath, Dragi Kimovski, Christoph Uran, Helmut Wöllik, and Radu Prodan

Abstract: Service discovery is a vital process that enables low latency provisioning of Internet of Things applications across the computing continuum. Unfortunately, it becomes increasingly difficult to identify a proper service within strict time constraints due to the high heterogeneity of the computing continuum. Moreover, the plethora of network technologies and protocols commonly used by the Internet of Things applications further hinders service discovery. To address these issues, we introduce a novel mobile edge service discovery algorithm named Mobile Edge Service Discovery using the DNS (MESDD), which utilizes intermediate code to identify a suitable service instance across the computing continuum based on the naming scheme used to identify the users’ location. MESDD utilizes geofences to aid this process, which enables fine-grained resource discovery. We deployed a real-life distributed computing continuum testbed and compared MESDD with three related methods. The evaluation results show that MESDD outperforms the other approaches by 60% after eight discovery iterations.

A DEEP DIVE INTO VIDEO STREAMING AND GRAPH PROCESSING USE CASES

More information

Prof. Hermann Hellwagner is a keynote speaker at IEEE MIPR, 30th August – 1st September 2023.

Title: Advances in Edge-Based and In-Network Media Processing for Adaptive Video Streaming

Talk Abstract: Media traffic (mainly, video) on the Internet is constantly growing; networked multimedia applications consume a predominant share of the available Internet bandwidth. A major technical breakthrough and enabler in multimedia systems research was the HTTP Adaptive Streaming (HAS) technique. While this technique is widely used and works well in industrial networked multimedia services today, challenges exist for future multimedia systems, dealing with the trade-offs between (i) the ever-increasing content complexity, (ii) various requirements with respect to time (most importantly, low latency), and (iii) quality of experience (QoE). This situation sets the stage for our research work in the ATHENA Christian Doppler (CD) Laboratory (Adaptive Streaming over HTTP and Emerging Networked Multimedia Services; https://athena.itec.aau.at/), jointly funded by public sources and industry.

In this talk, I’ll explore one facet of the ATHENA research, namely how and with which benefits edge-based and in-network media processing can cope with adverse network conditions and/or improve media quality/perception. Content Delivery Networks (CDNs) are the classical example of supporting content distribution on today’s Internet. In recent years, though, techniques like Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Function Virtualization (NFV), Peer Assistance (PA) for CDNs, and Machine Learning (ML) have emerged that can additionally be leveraged to support adaptive video streaming services. In the talk, I’ll present several approaches of edge-based and in-network media processing in support of adaptive streaming, in four groups:

  1. Edge Computing (EC) support, for instance transcoding, content prefetching, and adaptive bitrate algorithms at the edge.
  2. Virtualized Network Function (VNF) support for live video streaming.
  3. Hybrid P2P, Edge and CDN support including content caching, transcoding, and super-resolution at various layers of the system.
  4. Machine Learning (ML) techniques facilitating various (end-to-end) properties of an adaptive streaming system.