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Workshop paper accepted: One Spell Fits All: A Generative AI Game as a Tool for Research in AI Creativity and Sustainable Design

Authors: Tom Tucek, Kseniia Harshina, Georgia Samaritaki (University of Amsterdam), and Dipika Rajesh (University of California, Santa Cruz)

Abstract:
This paper presents “One Spell Fits All”, an AI-native game prototype where the player, playing as a witch, solves villagers’ problems using magical conjurations. We show how, beyond being a standalone game, “One Spell Fits All” could serve as a research platform to explore several key areas in AI-driven and AI-native game design. These areas include AI creativity, user experience in predominantly AI-generated content, and the energy efficiency of locally running versus cloud-based AI models. By leveraging smaller, locally running generative AI models, including LLMs and diffusion models for image generation, the game dynamically generates and evaluates content without the need for external APIs or internet access, offering a sustainable and responsive gameplay experience. This paper explores the application of LLMs in narrative video games, outlines a game prototype’s design and mechanics, and proposes future research opportunities that can be explored using the game as a platform.

EXAG ’24: Experimental AI in Games Workshop at the AIIDE Conference, November 18, 2024, Lexington, USA

 

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Short paper accepted: Experiencing Forced Migration: A Participatory Approach to Developing a Serious Video Game

Authors: Kseniia Harshina, Imke Alenka Harbig, Mathias Lux, and Tom Tucek

Abstract: Forced migration affects millions worldwide due to conflict, disasters, and persecution. This paper presents a participatory approach to serious game development, engaging individuals with lived migration experiences to create authentic and impactful narratives. Based on qualitative research, we propose a game design methodology to enhance empathy and raise awareness of forced migration. Our study demonstrates the potential of participatory games to bridge the gap between forced migrants and the broader public, fostering empathy, social change, and empowerment for marginalized communities.

GALA Conference 2024 Proceedings will be published on Springer Lecture Notes in Computer Science. Kseniia and Imke Harbig from the psychology department will present their research at the GALA conference in Berlin from November 20 to 22.

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Paper accepted: PagerBombs and Intelligent Vehicles: Stop Weaponing Supply Chains with Blockchain Intelligence

Authors: Jing Yang, Qinghua Ni, Song Zhang, Nan Zheng, Juanjuan Li, Lili Fan, Lili Fan, Radu Prodan, Levente Kovacs, Fei-Yue Wang

IEEE Transactions on Intelligent Vehicles: https://ieeexplore.ieee.org/document/10734076/

Abstract: The Lebanese wireless device explosion incident has drawn widespread attention, involving devices such as pagers, walkie-talkies, and other common devices. This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment, signaling the onset of a new wave of “supply chain warfare”. Even worse, with the rapid proliferation of Internet of Things (IoT) devices and smart hardware, the fragility of global supply chains would become increasingly fatal and significant, since almost all devices of daily usage could be maliciously programmed and triggered as weapons of massive destruction. Given this, we need new thinking and new approaches to improve supply chain security [3]. With its decentralized, tamper-proof, and highly traceable characteristics, blockchain technology is considered an effective solution to address these security threats [4], [5]. How to secure the entire lifecycle of smart devices, from production and transportation to usage, through blockchain-enabled safety management and protection, has become a pressing issue that requires immediate attention.

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Paper accepted: In-Band Quality Notification from Users to ISPs

Authors: Leonardo Peroni (UC3M, Spain); Sergey Gorinsky (IMDEA Networks Institute, Spain); Farzad Tashtarian (Alpen-Adria Universität Klagenfurt, Austria)

Conference: IEEE 13th International Conference on Cloud Networking (CloudNet)

27–29 November 2024 // Rio de Janeiro, Brazil

Abstract: While ISPs (Internet service providers) strive to improve QoE (quality of experience) for end users, end-to-end traffic encryption by OTT (over-the-top) providers undermines independent inference of QoE by an ISP. Due to the economic and technological complexity of the modern Internet, ISP-side QoE inference based on OTT assistance or out-of-band signaling sees low adoption. This paper presents IQN (in-band quality notification), a novel mechanism for signaling QoE impairments from an automated agent on the end-user device to the server-to-client ISP responsible for QoE-impairing congestion. Compatible with multi-ISP paths, asymmetric routing, and other Internet realities, IQN does not require OTT support and induces the OTT server to emit distinctive packet patterns that encode QoE information, enabling ISPs to infer QoE by monitoring these patterns in network traffic. We develop a prototype system, YouStall, which applies IQN signaling to ISP-side inference of YouTube stalls.
Cloud-based experiments with YouStall on YouTube Live streams validate IQN’s feasibility and effectiveness, demonstrating its potential for accurate user-assisted ISP-side QoE inference from encrypted traffic in real Internet environments.

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Paper accepted: Energy-Efficient Video Streaming: A Study on Bit Depth and Color Subsampling

Authors: Hadi Amirpour (AAU, Austria), Lingfeng Qu (Guangzhou University, China), Jong Hwan Ko (SKKU, South Korea), Cosmin Stejerean (Meta, USA), Christian Timmerer (AAU, Austria

Conference: IEEE Visual Communications and Image Processing (IEEE VCIP 2024)  – Tokyo, Japan, December 8-11, 2024

Abtract: As video dimensions — including resolution, frame rate, and bit depth — increase, a larger bitrate is required to maintain a higher Quality of Experience (QoE). While videos are often optimized for resolution and frame rate to improve compression and energy efficiency, the impact of color space is often overlooked. Larger color spaces are essential for avoiding color banding and delivering High Dynamic Range (HDR) content with richer, more accurate colors, although this comes at the cost of higher processing energy. This paper investigates the effects of bit depth and color subsampling on video compression efficiency and energy consumption. By analyzing different bit depths and subsampling schemes, we aim to determine optimized settings that balance compression efficiency with energy consumption, ultimately contributing to more sustainable and high-quality video delivery. We evaluate both encoding and decoding energy consumption and assess the quality of videos using various metrics including PSNR, VMAF, ColorVideoVDP, and CAMBI. Our findings offer valuable insights for video codec developers and content providers aiming to improve the performance and environmental footprint of their video streaming services.

Index Terms— Video encoding, video decoding, video quality, bit depth, color subsampling, energy.

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Paper accepted: Characterizing the Geometric Complexity of G-PCC Compressed Point Clouds

Authors: Annalisa Gallina (UNIPD, Italy), Hadi Amirpour (AAU, Austria), Sara Baldoni (UNIPD, Italy), Giuseppe Valenzise (UPSaclay, France), Federica Battisti (UNIPD, Italy).

Conference: IEEE Visual Communications and Image Processing (IEEE VCIP 2024) – Tokyo, Japan, December 8-11, 2024

Abstract: Measuring the complexity of visual content is crucial in various applications, such as selecting sources to test processing algorithms, designing subjective studies, and efficiently determining the appropriate encoding parameters and bandwidth allocation for streaming. While spatial and temporal complexity measures exist for 2D videos, a geometric complexity measure for 3D content is still lacking. In this paper, we present the first study to characterize the geometric complexity of 3D point clouds. Inspired by existing complexity measures, we propose several compression-based definitions of geometric complexity derived from the rate-distortion curves obtained by compressing a dataset of point clouds using G-PCC. Additionally, we introduce density-based and geometry-based descriptors to predict complexity. Our initial results show that even simple density measures can accurately predict the geometric complexity of point clouds.

Index Terms— Point cloud, complexity, compression, G-PCC.

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Paper accepted: Energy-Quality-aware Variable Framerate Pareto-Front for Adaptive Video Streaming

Authors: Prajit T Rajendran (Universite Paris-Saclay), Samira Afzal (Alpen-Adria-Universität Klagenfurt), Vignesh V Menon (Fraunhofer HHI), Christian Timmerer (Alpen-Adria-Universität Klagenfurt)

Conference: IEEE Visual Communications and Image Processing (IEEE VCIP 2024)

Abstract: Optimizing framerate for a given bitrate-spatial resolution pair in adaptive video streaming is essential to maintain perceptual quality while considering decoding complexity. Low framerates at low bitrates reduce compression artifacts and decrease decoding energy. We propose a novel method, Decoding-complexity aware Framerate Prediction (DECODRA), which employs a Variable Framerate Pareto-front approach to predict an optimized framerate that minimizes decoding energy under quality degradation constraints. DECODRA dynamically adjusts the framerate based on current bitrate and spatial resolution, balancing trade-offs between framerate, perceptual quality, and decoding complexity. Extensive experimentation with the Inter-4K dataset demonstrates DECODRA’s effectiveness, yielding an average PSNR and VMAF increase of 0.87 dB and 5.14 points, respectively, for the same bitrate compared to the default 60 fps encoding. Additionally, DECODRA achieves an average reduction in decoding energy consumption of 13.27 %, enhancing the viewing experience, extending mobile device battery life, and reducing the energy footprint of streaming services.

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Paper accepted – StoreLess: Serverless workflow scheduling with federated storage in sky computing

Authors: Sashko Ristov, Mika Hautz, Philipp Gritsch, Stefan Nastic, Radu Prodan, Michael Felderer

ICSOC 2024: 22nd International Conference on Service-Oriented Computing https://icsoc2024.redcad.tn/

Abstract:

We observe irregular data transfer performance across federated serverless infrastructures (sometimes faster across providers than colocated), making the entire workflow scheduling even more challenging in federated FaaS and sky computing. This paper introduces STORELESS – a novel workflow scheduler and heuristic algorithm for serverless storage attachments that dynamically selects, provisions, and configures suitable function deployments and storage backends from the federated serverless infrastructure. STORELESS improves workflow execution time by up to 30% by running cross-regional setup compared to the state-of-the-art.

 

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Journal article accepted: Cost modelling and Optimisation for Cloud: A Graph-based Approach

Authors: Akif Quddus Khan, Mihhail Matskin, Radu Prodan, Christoph Bussler, Dumitru Roman, Ahmet Soylu

Journal of Cloud Computing: https://journalofcloudcomputing.springeropen.com/

Abstract: Cloud computing has become popular among individuals and enterprises due to its convenience, scalability, and flexibility. However, a major concern for many cloud service users is the rising cost of cloud resources. Since cloud computing uses a pay-per-use model, costs can add up quickly, and unexpected expenses can arise from a lack of visibility and control. The cost structure gets even more complicated when working with multi-cloud or hybrid environments. Businesses may spend much of their IT budget on cloud computing, and any savings can improve their competitiveness and financial stability. Hence, an efficient cloud cost management is crucial. To overcome this difficulty, new approaches and tools are being developed to provide greater oversight and command over cloud computing expenses. In this respect, this article, presents a graph-based approach for modelling cost elements and cloud resources and a potential way to solve the resulting constraint problem of cost optimisation. In this context, we primarily consider utilisation, cost, performance, and availability. The proposed approach is evaluated on three different user scenarios, and results indicate that it could be effective in cost modelling, cost optimisation, and scalability. This approach will eventually help organisations make informed decisions about cloud resource placement and manage the costs of software applications and data workflows deployed in single, hybrid, or multi-cloud environments.

Paper accepted: SEAL-CC: Scalable Latency Evaluation Methodology for Internet-of-Things Services

Authors: Kurt Horvath, Dragi Kimovski, Radu Prodan, Bernd Spiess, Oliver Hohlfeld

Venue: 14th International Conference on Internet of Things (IoT 2024); Oulu, Finland, 19-22 November, https://iot-conference.org/iot2024

Abstract: Traditional network measurement campaigns suffer from the lack of control over network infrastructure and the inability to evaluate communication performance directly, especially for the placement of highly distributed Internet of Things (IoT) services. In response, we propose a novel Scalable Latency Evaluation Methodology for the Computing Continuum (SEAL-CC). SEAL-CC extends beyond short-term evaluations by capturing the long-term responsiveness of networks supporting IoT services on the computing continuum. It organizes and evaluates a network of nodes, offering insights for optimized IoT service placement in urban and international settings. Our contributions include a novel evaluation methodology tailored for IoT services over the computing continuum, a comprehensive framework for transparent network evaluation using distributed Internet measurement platforms, and a real-life case-study validation with recommendations for IoT service placement.