Official Launch of Fire Totem Games GmbH

We are thrilled to announce the official launch of Fire Totem Games GmbH, a dynamic and innovative game development company based in Austria. After years of dedicated work and passion, we are ready to set the gaming world ablaze with our creative endeavors.

The company founders are Sebastian Uitz, Michael Steinkellner, Manuel Santner, and Noel Treese. We are grateful for the fantastic support from University Klagenfurt, the Game Studies and Engineering master’s program, ITEC, build!, KWF, and EFRE for making this happen.

As Fire Totem Games GmbH, we aim to craft captivating and immersive gaming experiences that ignite players’ imaginations and leave a lasting impact. With a talented team of developers and a burning desire to push the boundaries of gaming, we are excited to embark on this journey and bring our unique vision to life.

ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming

21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 2024), APRIL 16–18, 2024, SANTA CLARA, CA, USA

Authors: Farzad Tashtarian (Alpen-Adria Universität Klagenfurt),  Abdelhak Bentaleb (Concordia University), Hadi Amirpour (Alpen-Adria Universität Klagenfurt) , Sergey Gorinsky (IMDEA Networks Institute),  Junchen Jiang (University of Chicago), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt) , Christian Timmerer (Alpen-Adria Universität Klagenfurt)

Live streaming of segmented videos over the Hypertext Transfer Protocol (HTTP) is increasingly popular and serves heterogeneous clients by offering each segment in multiple representations. A bitrate ladder expresses this choice as an ordered list of bitrate-resolution pairs. Whereas existing solutions for HTTP-based live streaming use a static bitrate ladder, the fixed ladders struggle to appropriately accommodate the dynamics in the video content and network-conditioned client capabilities. This paper proposes ARTEMIS as a practical scalable alternative that dynamically configures the bitrate ladder depending on the content complexity, network conditions, and clients’ statistics. ARTEMIS seamlessly integrates with the end-to-end streaming pipeline and operates transparently to video encoders and clients. We develop a cloud-based implementation of ARTEMIS and conduct extensive real-world and trace-driven experiments. The experimental comparison vs. existing prominent bitrate ladders demonstrates that live streaming with ARTEMIS outperforms all baselines, reduces encoding computation by 25%, end-to-end latency by 18%, and increases quality of experience (QoE) by 11%.

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Congrats to Dr. Zahra Najafabadi Samani on her doctoral defense

On 14.07.2023, Zahra Najafabadi Samani successfully defended her doctoral studies with the thesis on the title: “Resource-Aware Time-Critical Application Placement in the Computing Continuum” under the supervision of Prof. Radu Prodan and Assoc.-Prof. Dr. Klaus Schöffmann at ITEC. Her defense was chaired by Univ.-Prof. Dr. Christian Timmerer and examined by Univ.-Prof. Dr. Thomas Fahringer (Leopold Franzens-Universität Innsbruck, AT) and Assoc.-Prof. Dr. Attila Kertesz (University of Szeged, HU).
During her doctoral study, she contributed to ARTICONF and DataCloud EU H2020 projects.
Zahra will continue as a Postdoctoral researcher at the Leopold Franzens-Universität Innsbruck.

The abstract of her disseration is as follows:

The rapid expansion of time-critical applications with substantial demands on high bandwidth and ultra-low latency pose critical challenges for Cloud data centers. To address time-critical application demands, the computing continuum emerged as a new distributed platform that extends the Cloud toward nearby Edge and Fog resources, substantially decreasing communication latency and network traffic. However, the distributed and heterogeneous nature of the computing continuum with sporadic availability of devices may result in service failures and deadline violations, significantly negating its advantages for hosting time-critical applications and lowering users’ satisfaction. Additionally, the dense deployment and intense competition for limited nearby resources pose resource utilization challenges. To tackle these problems, this thesis investigates the problem of resource-aware time-critical application placement with constraint deadlines and various demands in the heterogeneous computing continuum with three main contributions:
 1. A multilayer resource partitioning model for placing time-critical applications to minimize resource wastage while maximizing deadline satisfaction;
 2. An adaptive placement for dynamic computing continuum with sporadic device availability to minimize resource wastage and maximize deadline satisfaction;
 3. A proactive service level agreement-aware placement method, leveraging distributed monitoring to enhance deadline satisfaction and service success.
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Logistics 5.0: From Intelligent Networks to Sustainable Ecosystems

Authors: Juanjuan Li, Rui Qin, Cristina Olaverri-Monreal, Radu Prodan, Fei-Yue Wang

Journal: IEEE Transactions on Intelligent Vehicles

Abstract: As part of TIV’s DHW on Vehicle 5.0, this letter introduces a novel concept, Logistics 5.0, to address high complexities in logistics CyberPhysical-Social Systems (CPSS). Building upon the theory of parallel intelligence and leveraging advanced technologies and methods such as blockchain, scenarios engineering, Decentralized Autonomous Organizations and Operations (DAOs), Logistics 5.0 promises to accelerate the paradigm shift towards intelligent and sustainable logistics. First, the parallel logistic framework is proposed, and the logistics ecosystem is discussed. Then, the human-oriented operating systems (HOOS) are suggested to providing intelligent Logistics 5.0 solutions. Logistics 5.0 serves as a critical catalyst in realizing the “6S” objectives, i.e. Safety, Security, Sustainability, Sensitivity, Service, and Smartness, within the logistics industry

 

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Paper accepted in the Springer Computing Journal.

Title: A distributed and energy-efficient KNN for EEG classification with dynamic money-saving policy in heterogeneous clusters

Authors: Juan José Escobar, Francisco Rodríguez, Beatriz Prieto, Dragi Kimovski, Andrés Ortiz, and Miguel Damas

Abstract: Due to energy consumption’s increasing importance in recent years, energy-time efficiency is a highly relevant objective to address in High-Performance Computing (HPC) systems, where cost significantly impacts the tasks executed. Among these tasks, classification problems are considered due to their great computational complexity, which is sometimes aggravated when processing high-dimensional datasets. In addition, implementing efficient applications for high-performance systems is not an easy task since hardware must be considered to maximize performance, especially on heterogeneous platforms with multi-core CPUs. Thus, this article proposes an efficient distributed K-Nearest Neighbors (KNN) for Electroencephalogram (EEG) classification that uses minimum Redundancy Maximum Relevance (mRMR) as a feature selection technique to reduce the dimensionality of the dataset. The approach implements an energy policy that can stop or resume the execution of the program based on the cost per Megawatt. Since the procedure is based on the master-worker scheme, the performance of three different workload distributions is also analyzed to identify which one is more suitable according to the experimental conditions. The proposed approach outperforms the classification results obtained by previous works that use the same dataset. It achieves a speedup of 74.53 when running on a multi-node heterogeneous cluster, consuming only 13.38% of the energy consumed by the sequential version. Moreover, the results show that financial costs can be reduced when energy policy is activated and the importance of developing efficient methods, proving that energy-aware computing is necessary for sustainable computing.

 

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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.

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A Webbing Journey @ A1 Austria eSports Festival 2023

Sebastian Uitz and Michael Steinkellner showcased their game, A Webbing Journey, at the A1 Austria eSports Festival in the Austria Center Vienna on May 27, 2023. The booth, featuring two PCs, a Steam Deck, and a Nintendo Switch, offered players of all ages a delightful experience. Valuable feedback was gathered, fueling the team’s determination to enhance the game for future events.

We are grateful for the positive response and eagerly await incorporating the feedback received. With its endearing storyline and unique gameplay mechanics, the game continues to build anticipation for its official release, offering an enchanting adventure filled with exploration and heartwarming quests.

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.