Distributed and Parallel Systems

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Paper accepted: PreMatch: A Prediction-based Scheduler for Dataflow Asynchronous Processing on the Computing Continuum

Authors: Narges Mehran, Zahra Najafabadi Samani, Samira Afzal, Radu Prodan, Frank Pallas and Peter Dorfinger

Event: The 40th ACM/SIGAPP Symposium On Applied Computing https://www.sigapp.org/sac/sac2025/

Abstract:

The popularity of asynchronous data exchange patterns has recently increased, as evidenced by an Alibaba trace analysis showing that 23% of the communication between microservices uses this method. Such workloads necessitate exploring a method for reducing their dataflow processing and completion time. Moreover, there is a need to exploit a prediction method to forecast the future requirements of such microservices and (re-)schedule them. Therefore, we investigate the prediction-based scheduling of asynchronous dataflow processing applications by considering the stochastic changes due to dynamic user requirements.

Moreover, we present a microservice scaling and scheduling method named PreMatch combining a machine learning prediction strategy based on gradient boosting with ranking and game theory matching scheduling principles. Firstly, PreMatch predicts the number of microservice replicas, and then, the ranking method orders the microservice replica and devices based on microservice and transmission times. Thereafter, the PreMatch schedules microservice replicas requiring dataflow processing on computing devices. Experimental analysis of the PreMatch method shows lower completion times on average 13% compared to a related prediction-based scheduling method.

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Keynote talk @ 21st EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous 2024)

Radu Prodan is invited to give a keynote talk at the 21st EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous 2024), which will be held from November 12-14,2024, in Oslo, Norway.

Abstract:

The presentation starts by reviewing the convergence of two historically disconnected AI branches: symbolic AI of explicit deductive reasoning owning mathematical rigor and interpretability, and connectionist AI of implicit inductive reasoning lacking readability and explainability.
Afterward, it makes a case of neuro-symbolic data processing in knowledge graph representation approached by the Graph-Massivizer Horizon Europe project and applied for anomaly prediction in data centers using graph neural networks. Machine learning-driven graph sampling algorithms support its training and inference on resource-constrained Edge devices. The presentation concludes with an outlook into future projects targeting Edge large language models fine-tuned and contextualized using symbolic knowledge representation for regulatory AI compliance, job market, and medicine.

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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 – 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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Haleh @ First International Workshop on Scaling Knowledge Graphs for Industry” in Conference “Semantics 24: 20th International Conference on Semantic Systems”

Haleh gave a presentation at the first International Workshop on Scaling Knowledge Graphs for Industry (co-located with the 20th International Conference on Semantic Systems – SEMANTICS 2024)  – in Amsterdam, Sept. 17-19, 2024.

Title: “Modeling and Generating Extreme Volumes of Financial Synthetic Time-Series Data with Knowledge Graphs”

Authors: Laurentiu Vasiliu, S. Haleh S. Dizaji , Aaron Eberhart, Dumitru Roman and Radu Prodan

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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.

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Reza Farahani gave a tutorial at the 12th European Workshop on Visual Information Processing 2024 in Geneva, Switzerland

Dr. Reza Farahani (University of Klagenfurt, Austria) and Dr. Vignesh V Menon (Fraunhofer HHI, Germany) presented a joint tutorial titled ‘Latency- and Energy-Aware Video Coding and Delivery Streaming Systems’ at the 12th European Workshop on Visual Information Processing (EUVIP 2024) on September 8.

Abstract: This tutorial introduces modern performance and energy-aware video coding and content delivery solutions and tools, focusing on popular video streaming applications, i.e., VoD and live streaming. In this regard, after introducing fundamentals of modern video encoding and networking paradigms, we introduce modern solutions systems, using per-title encoding, per-scene encoding, virtualized and software networks, edge computing, overlay networks such as Content Delivery Networks (CDNs) and/or Peer-to-Peer (P2P) paradigms to provide latency and energy-efficient VoD and live HAS streaming. Furthermore, the tutorial also presents our tools, software, datasets, and testbeds to demonstrate our latest achievements and share practical insights for researchers, engineers, and students who want to improve conversational streaming or even test such techniques for immersive video sequences (e.g., tile-based 360-degree VR) with a focus on latency, economic cost, and energy.

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Paper accepted for 20th International Conference on Network and Service Management (CNSM 2024)

Title: High Complexity and Bad Quality? Efficiency Assessment for Video QoE Prediction Approaches

Authors: Frank Loh, Gülnaziye Bingöl, Reza Farahani, Andrea Pimpinella, Radu Prodan, Luigi Atzori, Tobias Hoßfeld

Venue: 20th International Conference on Network and Service Management (CNSM 2024)

Abstract:  In recent years, video streaming has dominated Internet data traffic, prompting network providers to ensure high-quality streaming experiences to prevent customer churn. However, due to the encryption of streaming traffic, extensive network monitoring by providers is required to predict the streaming quality and improve their services. Several such prediction approaches have been studied in recent years, with a primary focus on the ability to determine key video quality degradation factors, often without considering the required resources or
energy consumption. To address this gap, we consider existing methods to predict key Quality of Experience (QoE) degradation factors from the literature and quantify the data that have to be monitored and processed for video streaming applications. Based on this, we assess the efficiency of different QoE degradation factor prediction approaches and quantify the ratio between efficiency and the achieved prediction quality. In this context, we identify significant disparities in the efficiency, influenced by data requirements and the specific prediction approach, and finally by the resulting quality. Consequently, we provide insights for network providers to choose the most appropriate method tailored to their specific requirements.

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CERCIRAS Summer School @ AAU – 25.-30.08.2024

CERCIRAS (CA19135), short for Connecting Education and Research Communities for an Innovative Resource Aware Society is a 4-year long COST Action, started at the end of September 2020 and now nearing completion. One of the highlights of CERCIRAS has been its yearly Training School, a week-long residential school designed for current and future PhD students with research interests falling within the thematic scope of the Action and open to other profiles, including industry professionals. While perturbed by unfortunate overlap with the outbreak of the COVID pandemic, CERCIRAS managed to execute three consecutive Training Schools successfully: mid-September 2022 in Split (HR); early September 2023 in Riga (LV); and late August 2024 in Klagenfurt (AT). All editions of the CERCIRAS Training School follow a common structure: 4 selected lecture topics, which alternate frontal lessons and assisted hands-on works; 25 to 35 participants from as many participating countries as possible, with rich diversity for provenance, seniority level, and research focus; a rich portfolio of social activities.

The Training School places a considerable burden on the local hosts, which includes securing comfortable and affordable accommodation for a large troop, providing a modern and spacious lecture hall for all lectures and labs, with refreshments for the two daily breaks and nearby canteens for lunch, and arranging exciting options for a whole-afternoon diversion.

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6G Continuum Kick-Off Meeting and Research Collaboration

Dragi Kimovski recently visited Mother Theresa University in Skopje as part of the OeAD 6G Continuum project, which focuses on developing middleware for Artificial Intelligence over 6G networks. This visit is the next step in the collaboration between the involved institutions. During the stay, the kick-off meeting for the 6G Continuum project took place, bringing together researchers from both institutions to discuss the project’s goals and clarify the the research activities in terms of supporting AI traning and inference in the Edge over 6G networks. In addition to the research focus, this visit also helped to strengthen the ongoing partnership between the institutions. They explored new opportunities for collaboration in teaching and research, including student and faculty exchanges through Erasmus and CEEPUS programs.