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Radu Prodan presented at IPDPS 2023

Radu Prodan presented the paper “Proactive SLA-aware Application Placement in the Computing Continuum” at the 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2023) <https://www.ipdps.org/> in St. Petersburg, Florida, USA.

Authors: Zahra Najafabadi Samani, Narges Mehran, Dragi Kimovski, and Radu Prodan, Alpen-Adria-Universität Klagenfurt

Abstract: The accelerating growth of modern distributed applications with low delivery deadlines leads to a paradigm shift towards the multi-tier computing continuum. However, the geographical dispersion, heterogeneity, and availability of the continuum resources may result in failures and quality of service degradation, significantly negating its advantages and lowering users’ satisfaction. We propose in this paper a proactive application placement PROS method relying on distributed coordination to prevent the quality of service violations through service-level agreements on the computing continuum. PROS employs a sigmoid function with adaptive weights for the different parameters to predict the service level agreement assurance of devices based on their past credentials and current capabilities. We evaluate PROS using two application workloads with different traffic stress levels up to 90 million services on a real testbed with 600 heterogeneous instances deployed over eight geographical locations. The results show that PROS increases the success rate by 7-33%, reduces the response time by 16-38%, and increases the deadline satisfaction rate by 19-42% compared to the two related work methods. A comprehensive simulation study with 1000 devices and a workload of up to 670 million services confirms the scalability of the results.

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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/.

Paper accepted: Serverless ECG Stream Processing in Federated Clouds with Lambda Architecture @ Computer Jounal, Special Issue on Computing in Telemedicine

Title: Serverless ECG Stream Processing in Federated Clouds with Lambda Architecture

Authors: Sashko Ristov, Marjan Gusev, Armin Hohenegger, Radu Prodan, Dimitar Mileski, Pano Gushev, Goran Temelkov

Computer Jounal, Special Issue on Computing in Telemedicine

Abstract: Although telemedicine has emerged as an everyday necessity for health monitoring, still current solutions are built for a small number of patients or use sensors that do not stream data with high velocity and volume. In this article, we explore a novel architecture for distributing  health monitoring computations over distributed cloud regions, both for constantly online patients and offline for several hours daily. We propose a conceptual architecture for a use-case example capable of processing thousands of simultaneous incoming streams with electrocardiogram signals. Current serverless cloud providers limit the concurrency within a single region, and we evaluate the performance of this solution across multiple cloud regions. The results indicate that our new solution can overcome the limitations of a single cloud for online and offline patients, thereby saving their lives in case of detected dangerous arrhythmia.

The Graph-Massivizer Approach Toward a European Sustainable Data Center Digital Twin

Authors: Martin Molan, Junaid Ahmed Khan, Andrea Bartolini, Roberta Turra, Giorgio Pedrazzi, Michael Cochez, Alexandru Iosup, Dumitru Roman, Jože Rožanec, Ana Lucia Vărbănescu, Radu Prodan

COMPSAC 2023: 1st IEEE International Workshop on Digital Twins for Metaverse

Abstract: Modeling and understanding an expensive next-generation data center operating at a sustainable exascale performance remains a challenge yet to solve. The paper presents the approach taken by the Graph-Massivizer project, funded by the European Union, towards a sustainable data center, targeting a massive graph representation and analysis of its digital twin. We introduce five interoperable open-source tools that support this undertaking, creating an automated, ustainable loop of graph creation, analytics, optimization, sustainable resource management, and operation, emphasizing state-of-the-art progress. We plan to employ the tools for designing a massive data center graph, representing a digital twin describing spatial, semantic, and temporal relationships between the monitoring metrics, hardware nodes, cooling equipment, and jobs. The project aims to strengthen Bologna Technopole as a leading European supercomputing and big data hub offering sustainable green computing for improved societally relevant science throughput.

Towards Graph-based Cloud Cost Modelling and Optimisation

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

COMPSAC 2023: 8th IEEE International Workshop on Distributed Big Data Management

Abstract: Cloud computing has become an increasingly popular choice for businesses and individuals due to its flexibility, scalability, and convenience; owever, the rising cost of cloud resources has become a significant concern for many. The pay-per-use model used in cloud computing means that costs can accumulate quickly, and the lack of visibility and control can result in unexpected expenses. The cost structure becomes even more complicated when dealing with hybrid or multi-cloud environments. For businesses, the cost of cloud computing can be a significant portion of their IT budget, and any savings can lead to better financial stability and competitiveness. In this respect, it is essential to manage cloud costs effectively. This requires a deep understanding of current resource utilization, forecasting future needs, and optimising resource utilization to control costs. To address this challenge, new tools and techniques are being developed to provide more visibility and control over cloud computing costs. In this respect, this paper explores a graph-based solution for modelling cost elements and cloud resources and potential ways to solve the resulting constraint problem of cost optimisation. We primarily consider utilization, cost, performance, and availability in this context. Such an approach will eventually help organizations 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.

Event on Concertation and Consultation on Computing Continuum: From Cloud to Edge to IoT

Dragi Kimovski  participated in the EU Concentration and Consultation event on the computing continuum, held in Brussels on May 10-11, 2023. During the event, he delivered a presentation on the groundbreaking DataCloud H2020 Project and actively engaged in open panels and poster sessions.

Paper accepted: A distributed geofence-based discovery scheme for the computing Continuum @ MESDD

Titel: A distributed geofence-based discovery scheme for the computing Continuum

Euro-Par 2023, https://2023.euro-par.org/

Authors: Kurt Horvath1, Dragi Kimovski1, Christoph Uran1,2, Helmut Wöllik2, and
Radu Prodan1

1 Institute of Information Technology, University Klagenfurt, Klagenfurt, Austria
name.surname@aau.at

2 Faculty of Engineering and IT, Carinthian University of Applied Science
Klagenfurt, Austria surname@fh-kaernten.at

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.

 

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Paper accepted: Action Recognition in Video Recordings from Gynecologic Laparoscopy

Title: Action Recognition in Video Recordings from Gynecologic Laparoscopy

Authors: Sahar Nasirihaghighi, Negin Ghamsarian, Daniela Stefanics, Klaus Schoeffmann and Heinrich Husslein

IEEE 36th International Symposium on Computer-Based Medical Systems 2023

Abstract: Action recognition is a prerequisite for many applications in laparoscopic video analysis including but not limited to surgical training, operation room planning, follow-up surgery preparation, post-operative surgical assessment, and surgical outcome estimation. However, automatic action recognition in laparoscopic surgeries involves numerous challenges such as (I) cross-action and intra-action duration variation, (II) relevant content distortion due to smoke, blood accumulation, fast camera motions, organ movements, object occlusion, and (III) surgical scene variations due to different illuminations and viewpoints. Besides, action annotations in laparoscopy surgeries are limited and expensive due to requiring expert knowledge. In this study, we design and evaluate a CNN-RNN architecture as well as a customized training-inference framework to deal with the mentioned challenges in laparoscopic surgery action recognition. Using stacked recurrent layers, our proposed network takes advantage of inter-frame dependencies to negate the negative effect of content distortion and variation in action recognition. Furthermore, our proposed frame sampling strategy effectively manages the duration variations in surgical actions to enable action recognition with high temporal resolution. Our extensive experiments confirm the superiority of our proposed method in action recognition compared to static CNNs.

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CodeAbility Austria – Digitally supported programming education at Austrian universities

Authors: Clemens SAUERWEIN1 (Innsbruck), Ruth BREU (Innsbruck), Stefan OPPL (Krems), Iris GROHER (Linz), Tobias ANTENSTEINER (Innsbruck), Stefan PODLIPNIG (Wien) & Radu PRODAN (Klagenfurt)

Abstact: High-quality programming education at universities is a significant challenge due to rapidly increasing student numbers, tight teaching budgets and a shortage of instructors. The “CodeAbility Austria” project aims to meet this challenge by establishing suitable programming learning platforms. In this paper, we introduce the project in more detail, present the results of our empirical research on the experiences and challenges of using programming learning platforms, and provide an outlook for future work.

Link: Zeitschrift für Hochschulentwicklung