Scopus Publications
- Survey on AI technologies aiding multicast and broadcast services in 5G and 6G
Marcell Szabó, László Toka
Telecommunication Systems, 2026
Despite standardization since 3GPP Release 9, multicast and broadcast services (MBS) remain largely undeployed in commercial networks. Artificial intelligence may catalyze adoption by addressing the optimization complexity hindering practical deployment, particularly as 6G targets demanding applications requiring efficient group-oriented transmission. Following PRISMA guidelines, this survey reviews the 5G MBS architecture and analyzes 23 studies applying AI to multicast and broadcast optimization. Surveyed works demonstrate computational complexity reductions from $$O(N^3)$$ O ( N 3 ) to $$O(N^2)$$ O ( N 2 ) , throughput gains of 18–50%, and resource savings up to 33%. Deep reinforcement learning variants dominate resource allocation and scheduling, while unsupervised clustering methods address multicast group formation and federated learning enables privacy-preserving optimization across distributed deployments. We organize findings across six areas: physical layer intelligence, RAN slicing and scheduling, multicast group formation and routing, RIS-assisted transmission, D2D-assisted multicast, and end-to-end optimization. We identify underexplored areas, non-terrestrial networks, ISAC integration, graph neural networks, and foundation models, and provide a research roadmap addressing standardization gaps and deployment barriers. - Temporal Graph Network Framework for Quantifying Pass Reception Probabilities Against Defensive Structures
Pegah Rahimian, Jesse Davis, Laszlo Toka
Machine Learning, 2026
Passing decisions in soccer are heavily influenced by the opposing team’s defensive organization. Existing approaches often decompose the problem into pass selection and success probabilities, sometimes incorporating pressure-related features to account for defensive constraints. In this study, we propose a framework for evaluating passing decisions against defensive structures using temporal graph networks (TGNs). Rather than separately modeling selection and success, we estimate the probability of a pass being received by each teammate or intercepted by an opponent, leveraging temporal, spatial, and relational data to capture dynamic interactions. We focus on forward passes originating in the middle third of the pitch, where teams frequently encounter structured defensive shapes. Specifically, we analyze passes that (1) bypass defensive lines, (2) reach teammates inside defensive structure, or (3) penetrate, exit, and reach teammates outside defensive structure. Our evaluation compares pass reception prediction accuracy against baselines, examines receiver availability against defensive structure, and assesses the situational value of passing options. The results suggest that TGNs improve pass probability estimates while offering practical insights for decision-making against organized defenses. - Routing LEO satellite traffic in adverse weather
Laszlo Toka, Zoltan Illes, Endre Angelus Papp, Laszlo Hevizi, Istvan Godor
Computer Networks, 2025
This research investigates the planning and optimization of sixth-generation (6G) non-terrestrial networks (NTNs) by leveraging Free-Space Optical (FSO) communication to enhance speed, coverage, and resilience in global communication. Building on the theoretical foundation of NTN technologies, this study develops a dynamic simulation model to represent interactions among satellites, ground stations, and environmental variables. Our model allows detailed analysis of weather-induced disruptions, revealing that conditions such as rain and fog can significantly impact radio and FSO-based communication by reducing network speed and reliability. Simulation results show that integrating FSO links alongside traditional microwave connections enhances network adaptability, reducing latency and hop counts, particularly in high-traffic scenarios. In stress tests simulating ground station outages, the network demonstrated resilience by dynamically rerouting traffic over inter-orbit inter-satellite links, maintaining continuity even under significant regional disruptions. These findings underscore the importance of hybrid connectivity models and adaptive routing strategies in 6G NTN planning, providing critical insights for designing robust, high-performance networks capable of meeting future connectivity demands. - All about momentum: Investigating high-pressure situations in the NBA through scoring probability
Balázs Mihályi, Gergely Biczók, László Toka
International Journal of Sports Science and Coaching, 2025
One of the defining characteristics of real basketball stars, and even great role players, is how well they perform under immense mental pressure. This paper presents a method to identify high-pressure situations during a basketball game through shooting success. Our analysis incorporates a novel feature set that emphasizes both player- and team-level momentum, including scoring streaks. Additionally, we redefine player roles using a clustering-based approach with deep learning techniques, allowing for a more nuanced evaluation of performance under pressure. Using six seasons of NBA data, we find that shotmaking is mainly impacted by the so-called momentum , i.e., when a team outscores their opponent significantly over a short period of time. - Performance analysis in SailGP: A machine learning approach
Benedek Zentai, László Toka
International Journal of Sports Science and Coaching, 2025
The significance of data analysis in high-performance sports has largely increased in recent years, offering opportunities for further exploration using machine learning techniques. SailGP is a relatively new sailing event driven by a passion for speed and innovation. The racing series brings excitement and thrill to the world of sailing that has been relatively unexplored. As a pioneer work in the academic community, our work showcases the power of data-driven approaches in enhancing performance and decision-making at high-performance sailing events. We explore data mining techniques on datasets collected at high-performance sailing events in Bermuda in 2021 and Italy in 2023. By analysing race data, the study aims to gain insights into the relationship between variables such as wind speed, wind direction, foil usage, and daggerboard adjustments, and their impact on boat speed. For a comprehensive understanding, we used three distinct methodologies. Various prediction models, including Gradient Boosting, Random Forest, and a stacked model, were employed and evaluated using performance metrics like R² score and mean squared error. The results demonstrate the models’ ability to accurately predict boat speed. Anomaly detection techniques examined boat stability, adding a new chapter to the research. Additionally, we introduced a reinforcement learning approach to identify optimal settings for speed enhancement, representing another new dimension of the study. These findings refine race strategies, optimise sail and rudder settings, and improve performance in SailGP races. Future plans include collaborating with SailGP to work with larger datasets and integrate models into live racing scenarios. - Dimensioning space-air-ground integrated networks for in-flight 6G slice orchestration
László Toka, Endre Angelus Papp, Tibor Cinkler, István Gódor, László Hévizi
Vehicular Communications, 2025
In this study, we present an in-depth analysis of communication services for commercial airline passengers, focusing on the challenges posed by increasing internet traffic demand. We explore the integration of satellite, airborne, and terrestrial networks, emphasizing the roles of Low Earth Orbit (LEO) satellites, High-Altitude Platform Station (HAPS), and Terrestrial Aviation Network (TAN)-based services. Our contribution includes a theoretical model for optimizing resource allocation and capacity planning in non-terrestrial wireless networks, using a bipartite graph approach and linear programming techniques. The model shows adaptability and efficiency, providing key insights through numerical analysis. Leveraging a detailed air traffic dataset, a machine learning-based aggregation method, and real-world network parameters, our research addresses current challenges, such as scalable network capacity dimensioning in high-density airspaces and meeting the demand for quality of service by robust resource provisioning, and advances the design of communication networks for Space–Air–Ground Integrated Network (SAGIN). Numerical results from European airspace suggest that complementing TAN and LEO satellite networks with HAPS-based services will be essential as airline passengers adopt ground-level internet usage patterns. - Collaborative HD Map Creation: A Stackelberg Evolutionary Game Approach
Marcell Szabó, László Toka
IEEE Vehicular Technology Conference, 2025
High-definition (HD) maps are becoming essential for Advanced Driver Assistance Systems and Fully Self-Driving technology. Given the vast scale and dynamic nature of road networks, crowdsensing appears to be the only viable solution for maintaining these maps. However, sustaining user contributions requires effective incentive mechanisms. In this work, we analyze such a system using game theory, nonlinear programming, and deep learning. Specifically, we employ a Stackelberg evolutionary game framework and optimize incentive strategies using a Deep Deterministic Policy Gradient method enhanced with Evolutionary Algorithms. Our recent theoretical results highlight the necessity of incentives to ensure sustained participation, while also revealing challenges in rural areas due to participation fluctuations, which may impact long-term data reliability. - Analyzing Energy Consumption of Loihi 2 Neuromorphic Chip in a Self-driving Use-case
Ádám Nagy, Róbert Szabó, László Toka
2025 10th International Conference on Smart and Sustainable Technologies Splitech 2025, 2025
A modern network often studied today, which comes closer to copying and imitating the dynamics and characteristics of a realistic brain, is the Spiking Neural Network (SNN). This network operates on completely new principles and requires specific hardware for efficient operation. In order to achieve these requirements, Intel researchers developed the Loihi 2 neuromorphic chip. In our research, we got to work with a Loihi 2 hardware system developed by Intel Labs. We explored the main differences in performance and accuracy compared to traditional GPUs. Using the hardware and provided framework, we carried out a comparison of applications implemented on both GPU and Loihi 2 hardware. The primary focus of the comparison was energy consumption and speed. The study involves benchmarking a vehicular steering prediction model implemented on both platforms, utilizing an SNN architecture optimized for neuromorphic computing. At the end of the study we conclude results of the implemented SNN on both hardware and show that Loihi 2 does not fall short of GPU regarding accuracy as it reaches a 0.89 R-squared score compared to the 0.94 R-squared score of the GPU, while only using 3 to 3.5 Watts on average in contrast to GPUs over 50 Watts power consumption on average. - Minimizing Energy Consumption of Satellite Edge Computing-Capable LEO Satellites
Amad Alnahdi, Abdulhalim Fayad, László Toka, Tibor Cinkler
IEEE Access, 2025
Low Earth Orbit (LEO) satellite constellations have gained considerable attention from both academia and industry due to their potential to provide reliable global coverage. However, the continuous movement of satellites causes periodic transitions between the sunlit and shadowed regions of orbit, leading to fluctuations in available energy. Satellites on the sunlit side can harvest solar energy to recharge their batteries, while those in the shadowprimarily rely on stored battery power. This paper presents a joint task and energy allocation framework that optimizes satellite energy consumption by considering three key factors: onboard processing of small tasks, relaying tasks to sunlit satellites for processing, and offloading larger tasks to ground stations when available. An Integer Linear Programming (ILP) approach is employed to determine the optimal energy distribution across these tasks, while a computationally efficient greedy algorithm is introduced as an alternative. Additionally, Dynamic Voltage and Frequency Scaling (DVFS) is incorporated to optimize the energy consumption during task processing by adjusting the processing frequency according to the available energy. The results indicate that ILP achieves optimal energy efficiency, while the greedy approach provides a near-optimal solution with only a 4.4% deviation. - 6G for Connected Sky: Holistic Adaptive Combined Airspace and Non Terrestrial Network Architecture
Shuai Zhang, Mustafa Ozger, Siva S. S. G. Seeram, Istvan Godor, Luca Feltrin, Anders Nordlow, Joerg Pfeifle, Laszlo Toka, Gergely Biczok, Dominic A. Schupke, Cicek Cavdar
IEEE Wireless Communications, 2025
The evolution toward 6G networks introduces unprecedented challenges and opportunities, particularly in the realm of serving both aerial and ground users seamlessly. In this article, we propose a holistic adaptive combined airspace and non-terrestrial network (NTN) architecture designed to address the unique requirements of the 6G era. Three principle features - joint sensing, communication, and computation (JSCC) in three dimensions (3D), cloud-native and artificial intelligence (AI) native, and the flexibility of radio access network (RAN) and core functions of the proposed architecture - are presented. Next, two application scenarios are analyzed: one catering to aerial users and the other supporting ground users, each, in particular, supporting communication links. Finally, we look into the network management and control aspects of the proposed architecture and discuss challenges and future research directions. - In-game soccer outcome prediction with offline reinforcement learning
Pegah Rahimian, Balazs Mark Mihalyi, Laszlo Toka
Machine Learning, 2024 - A data-driven approach to assist offensive and defensive players in optimal decision making
Pegah Rahimian, Laszlo Toka
International Journal of Sports Science and Coaching, 2024 - Towards maximizing expected possession outcome in soccer
Pegah Rahimian, Jan Van Haaren, Laszlo Toka
International Journal of Sports Science and Coaching, 2024 - A career handbook for professional soccer players
Balázs Ács, Roland Kovács, László Toka
International Journal of Sports Science and Coaching, 2024 - A Survey on Integrating Edge Computing With AI and Blockchain in Maritime Domain, Aerial Systems, IoT, and Industry 4.0
Amad Alanhdi, László Toka
IEEE Access, 2024 - Optimizing the Edge Computing System of a LEO Satellite Constellation
Amad Alnahdi, László Toka
Proceedings of the 15th International Conference on Network of the Future Nof 2024, 2024 - Boat Speed Prediction in SailGP
Benedek Zentai, László Toka
Communications in Computer and Information Science, 2024 - Momentum Matters: Investigating High-Pressure Situations in the NBA Through Scoring Probability
Balazs Mihalyi, Gergely Biczók, Laszlo Toka
Communications in Computer and Information Science, 2024 - Pass Receiver and Outcome Prediction in Soccer Using Temporal Graph Networks
Pegah Rahimian, Hyunsung Kim, Marc Schmid, Laszlo Toka
Communications in Computer and Information Science, 2024 - Integrating the Skies for 6G: Techno-Economic Considerations of LEO, HAPS, and UAV Technologies
Laszlo Toka, Mark Konrad, Adrian Pekar, Gergely Biczók
IEEE Communications Magazine, 2024 - Minimizing Resource Allocation for Cloud-Native Microservices
Roland Erdei, Laszlo Toka
Journal of Network and Systems Management, 2023 - Real-Time FaaS: Towards a Latency Bounded Serverless Cloud
Márk Szalay, Péter Mátray, László Toka
IEEE Transactions on Cloud Computing, 2023 - Let’s Penetrate the Defense: A Machine Learning Model for Prediction and Valuation of Penetrative Passes
Pegah Rahimian, Dayana Grayce da Silva Guerra Gomes, Fanni Berkovics, Laszlo Toka
Communications in Computer and Information Science, 2023 - A Comprehensive Performance Analysis of Stream Processing with Kafka in Cloud Native Deployments for IoT Use-cases
István Pelle, Bence Szőke, Abdulhalim Fayad, Tibor Cinkler, László Toka
Proceedings of IEEE IFIP Network Operations and Management Symposium 2023 NOMS 2023, 2023 - Federated learning for vehicular coordination use cases
László Toka, Márk Konrád, István Pelle, Balázs Sonkoly, Marcell Szabó, Bhavishya Sharma, Shashwat Kumar, Madhuri Annavazzala, Sree Teja Deekshitula, A Antony Franklin
Proceedings of IEEE IFIP Network Operations and Management Symposium 2023 NOMS 2023, 2023 - 5G on the Roads: Latency-Optimized Federated Analytics in the Vehicular Edge
László Toka, Márk Konrad, István Pelle, Balázs Sonkoly, Marcell Szabó, Bhavishya Sharma, Shashwat Kumar, Madhuri Annavazzala, Sree Teja Deekshitula, A. Antony Franklin
IEEE Access, 2023 - 5G on the roads: optimizing the latency of federated analysis in vehicular edge networks
László Toka, Márk Konrád, István Pelle, Balázs Sonkoly, Marcell Szabó, Bhavishya Sharma, Shashwat Kumar, Madhuri Annavazzala, Sree Teja Deekshitula, A Antony Franklin
Proceedings of IEEE IFIP Network Operations and Management Symposium 2023 NOMS 2023, 2023 - 6G for Connected Sky: A Vision for Integrating Terrestrial and Non-Terrestrial Networks
Mustafa Ozger, Istvan Godor, Anders Nordlow, Thomas Heyn, Sreekrishna Pandi, Ian Peterson, Alberto Viseras, Jaroslav Holis, Christian Raffelsberger, Andreas Kercek, Bengt Mölleryd, Laszlo Toka, Gergely Biczok, Robby de Candido, Felix Laimer, Udo Tarmann, Dominic Schupke, Cicek Cavdar
2023 Joint European Conference on Networks and Communications and 6g Summit Eucnc 6g Summit 2023, 2023 - Optical tracking in team sports A survey on player and ball tracking methods in soccer and other team sports
Pegah Rahimian, Laszlo Toka
Journal of Quantitative Analysis in Sports, 2022 - Optimizing and dimensioning a data intensive cloud application for soccer player tracking
Gergely Dobreff, Marton Molnar, Laszlo Toka
International Journal of Computer Science in Sport, 2022 - Cost and Latency Optimized Edge Computing Platform
István Pelle, Márk Szalay, János Czentye, Balázs Sonkoly, László Toka
Electronics Switzerland, 2022 - The Shape of Your Cloud: How to Design and Run Polylithic Cloud Applications
Laszlo Toka
IEEE Access, 2022 - Inferring the Strategy of Offensive and Defensive Play in Soccer with Inverse Reinforcement Learning
Pegah Rahimian, Laszlo Toka
Communications in Computer and Information Science, 2022 - Predicting Player Transfers in the Small World of Football
Roland Kovacs, Laszlo Toka
Communications in Computer and Information Science, 2022 - A Career in Football: What is Behind an Outstanding Market Value?
Balazs Acs, Laszlo Toka
Communications in Computer and Information Science, 2022 - Optimal Resource Provisioning for Data-intensive Microservices
Roland Mark Erdei, Laszlo Toka
Proceedings of the IEEE IFIP Network Operations and Management Symposium 2022 Network and Service Management in the Era of Cloudification Softwarization and Artificial Intelligence NOMS 2022, 2022 - Optimizing Performance and Resource Consumption of Cloud-Native Logging Application Stacks
Gergo Csati, Istvan Pelle, Laszlo Toka
Proceedings of the IEEE IFIP Network Operations and Management Symposium 2022 Network and Service Management in the Era of Cloudification Softwarization and Artificial Intelligence NOMS 2022, 2022 - LSSO: Long Short-Term Scaling Optimizer
Balazs Fodor, Laszlo Toka, Balazs Sonkoly
2022 IEEE Conference on Network Function Virtualization and Software Defined Networks Nfv Sdn 2022 Proceedings, 2022 - AnnaBellaDB: A key value store for stateless network functions
Márk Szalay, Péter Mátray, László Toka
Proceedings of the SIGCOMM 2020 Poster and Demo Sessions SIGCOMM 2020, 2021 - AR over NDN: Augmented reality applications and the rise of information centric networking
János Dóka, Bálint György Nagy, Muhammad Atif Ur Rehman, Dong-Hak Kim, Byung-Seo Kim, László Toka, Balázs Sonkoly
Proceedings of the SIGCOMM 2020 Poster and Demo Sessions SIGCOMM 2020, 2021 - Ultra-Reliable and Low-Latency Computing in the Edge with Kubernetes
László Toka
Journal of Grid Computing, 2021 - Real-Time task scheduling in a FaaS cloud
Mark Szalay, Peter Matray, Laszlo Toka
IEEE International Conference on Cloud Computing Cloud, 2021 - Factors Influencing Creatine Kinase Response in Youth National Team Soccer Players
Gabor Schuth, Gyorgy Szigeti, Gergely Dobreff, Peter Revisnyei, Alija Pasic, Laszlo Toka, Tim Gabbett, Gabor Pavlik
Sports Health, 2021 - Predicting cloud-native application failures based on monitoring data of cloud infrastructure
Proceedings of the IM 2021 2021 IFIP IEEE International Symposium on Integrated Network Management, 2021 - Machine Learning-Based Scaling Management for Kubernetes Edge Clusters
Laszlo Toka, Gergely Dobreff, Balazs Fodor, Balazs Sonkoly
IEEE Transactions on Network and Service Management, 2021 - State management for cloud-native applications
Márk Szalay, Péter Mátray, László Toka
Electronics Switzerland, 2021 - Pricing games of NFV infrastructure providers
Laszlo Toka, Marton Zubor, Attila Korosi, George Darzanos, Ori Rottenstreich, Balazs Sonkoly
Telecommunication Systems, 2021 - Towards optimized actions in critical situations of soccer games with deep reinforcement learning
Pegah Rahimian, Afshin Oroojlooy, Laszlo Toka
2021 IEEE 8th International Conference on Data Science and Advanced Analytics Dsaa 2021, 2021 - Survey on Placement Methods in the Edge and beyond
Balazs Sonkoly, Janos Czentye, Mark Szalay, Balazs Nemeth, Laszlo Toka
IEEE Communications Surveys and Tutorials, 2021 - Location, proximity, affinity - The key factors in faas
David Haja, Zoltan Richard Turanyi, Laszlo Toka
Infocommunications Journal, 2020 - Scalable edge cloud platforms for IoT services
Balázs Sonkoly, Dávid Haja, Balázs Németh, Márk Szalay, János Czentye, Róbert Szabó, Rehmat Ullah, Byung-Seo Kim, László Toka
Journal of Network and Computer Applications, 2020 - AnnaBellaDB: Key-value store made cloud native
Mark Szalay, Peter Matray, Laszlo Toka
16th International Conference on Network and Service Management Cnsm 2020 2nd International Workshop on Analytics for Service and Application Management Anservapp 2020 and 1st International Workshop on the Future Evolution of Internet Protocols Ipfuture 2020, 2020 - On the mediation price war of 5G providers
Laszlo Toka, Akos Recse, Mate Cserep, Robert Szabo
Electronics Switzerland, 2020 - 5G Applications from Vision to Reality: Multi-Operator Orchestration
Balazs Sonkoly, Robert Szabo, Balazs Nemeth, Janos Czentye, David Haja, Mark Szalay, Janos Doka, Balazs P. Gero, David Jocha, Laszlo Toka
IEEE Journal on Selected Areas in Communications, 2020 - To boost or not to boost: A stochastic game in wireless access networks
Laszlo Toka, Mark Szalay, David Haja, Geza Szabo, Sandor Racz, Miklos Telek
IEEE International Conference on Communications, 2020 - Adaptive AI-based auto-scaling for Kubernetes
Laszlo Toka, Gergely Dobreff, Balazs Fodor, Balazs Sonkoly
Proceedings 20th IEEE ACM International Symposium on Cluster Cloud and Internet Computing Ccgrid 2020, 2020 - Transition to sdn is harmless: Hybrid architecture for migrating legacy ethernet switches to sdn
Levente Csikor, Mark Szalay, Gabor Retvari, Gergely Pongracz, Dimitrios P. Pezaros, Laszlo Toka
IEEE ACM Transactions on Networking, 2020 - 5g support for industrial iot applications – challenges, solutions, and research gaps
Pal Varga, Jozsef Peto, Attila Franko, David Balla, David Haja, Ferenc Janky, Gabor Soos, Daniel Ficzere, Markosz Maliosz, Laszlo Toka
Sensors Switzerland, 2020 - Low-cost optical tracking of soccer players
Gabor Csanalosi, Gergely Dobreff, Alija Pasic, Marton Molnar, László Toka
Communications in Computer and Information Science, 2020 - Physical performance optimization in football
Gergely Dobreff, Péter Revisnyei, Gábor Schuth, György Szigeti, László Toka, Alija Pašić
Communications in Computer and Information Science, 2020 - Minimizing state access delay for cloud-native network functions
Mark Szalay, Peter Matray, Laszlo Toka
Proceeding of the 2019 IEEE 8th International Conference on Cloud Networking Cloudnet 2019, 2019 - Towards making big data applications network-aware in edge-cloud systems
David Haja, Balazs Vass, Laszlo Toka
Proceeding of the 2019 IEEE 8th International Conference on Cloud Networking Cloudnet 2019, 2019 - A stable matching method for cloud scheduling
Laszlo Toka, Barnabas Gema, Balazs Sonkoly
Proceeding of the 2019 IEEE 8th International Conference on Cloud Networking Cloudnet 2019, 2019 - Resource provisioning for highly reliable and ultra-responsive edge applications
Laszlo Toka, David Haja, Attila Korosi, Balazs Sonkoly
Proceeding of the 2019 IEEE 8th International Conference on Cloud Networking Cloudnet 2019, 2019 - Cloud-Powered Digital Twins: Is It Reality?
Balazs Sonkoly, Balint Gyorgy Nagy, Janos Doka, Istvan Pelle, Geza Szabo, Sandor Racz, Janos Czentye, Laszlo Toka
Proceeding of the 2019 IEEE 8th International Conference on Cloud Networking Cloudnet 2019, 2019 - Towards human-robot collaboration: An industry 4.0 VR platform with clouds under the hood
Balint Gyorgy Nagy, Janos Doka, Saandor Racz, Geza Szabo, Istvan Pelle, Janos Czentye, Laszlo Toka, Balazs Sonkoly
Proceedings International Conference on Network Protocols Icnp, 2019 - Sharpening Kubernetes for the Edge
David Haja, Mark Szalay, Balazs Sonkoly, Gergely Pongracz, Laszlo Toka
SIGCOMM 2019 Proceedings of the 2019 ACM SIGCOMM Conference Posters and Demos Part of SIGCOMM 2019, 2019 - Improving big data application performance in edge-cloud systems
David Haja, Balazs Vass, Laszlo Toka
IEEE International Conference on Cloud Computing Cloud, 2019 - Industrial-scale stateless network functions
Mark Szalay, Mate Nagy, Daniel Gehberger, Zoltan Kiss, Peter Matray, Felician Nemeth, Gergely Pongracz, Gabor Retvari, Laszlo Toka
IEEE International Conference on Cloud Computing Cloud, 2019 - Demo Abstract: Turning OpenStack into a Fog Orchestrator
Mark Szalay, David Haja, Janos Doka, Balazs Sonkoly, Laszlo Toka
INFOCOM 2019 IEEE Conference on Computer Communications Workshops INFOCOM Wkshps 2019, 2019 - Optimizing latency sensitive applications for amazon's public cloud platform
Janos Czentye, Istvan Pelle, Andras Kern, Balazs Peter Gero, Laszlo Toka, Balazs Sonkoly
Proceedings IEEE Global Communications Conference Globecom, 2019 - Network Management and Orchestration
Luis M. Contreras, Víctor López, Ricard Vilalta, Ramon Casellas, Raúl Muñoz, Wei Jiang, Hans Schotten, Jose Alcaraz‐Calero, Qi Wang, Balázs Sonkoly, László Toka
Wiley 5g Ref the Essential 5g Reference Online, 2019 - FERO: Fast and Efficient Resource Orchestrator for a Data Plane Built on Docker and DPDK
Balazs Sonkoly, Marton Szabo, Balazs Nemeth, Andras Majdan, Gergely Pongracz, Laszlo Toka
Proceedings IEEE INFOCOM, 2018 - Controlling drones from 5G networks
János Czentye, János Dóka, Árpád Nagy, László Toka, Balázs Sonkoly, Róbert Szabó
SIGCOMM 2018 Proceedings of the 2018 Posters and Demos Part of SIGCOMM 2018, 2018 - Policy injection: A cloud dataplane DoS attack
Levente Csikor, Christian Rothenberg, Dimitrios P. Pezaros, Stefan Schmid, László Toka, Gábor Rétvári
SIGCOMM 2018 Proceedings of the 2018 Posters and Demos Part of SIGCOMM 2018, 2018 - Business network formation among 5G providers
Mate Cserep, Akos Recse, Robert Szabo, Laszlo Toka
INFOCOM 2018 IEEE Conference on Computer Communications Workshops, 2018 - Fast and efficient network service embedding method with adaptive offloading to the edge
Balazs Nemeth, Mark Szalay, Janos Doka, Matthias Rost, Stefan Schmid, Laszlo Toka, Balazs Sonkoly
INFOCOM 2018 IEEE Conference on Computer Communications Workshops, 2018 - How to orchestrate a distributed OpenStack
David Haja, Marton Szabo, Mark Szalay, Adam Nagy, Andras Kern, Laszlo Toka, Balazs Sonkoly
INFOCOM 2018 IEEE Conference on Computer Communications Workshops, 2018 - Realizing services and slices across multiple operator domains
I. Vaishnavi, J. Czentye, M. Gharbaoui, G. Giuliani, D. Haja, J. Harmatos, D. Jocha, J. Kim, B. Martini, J. MeMn, P. Monti, B. Nemeth, Wint Yi Poe, A. Ramos, A. Sgambelluria, B. Sonkoly, L. Toka, F. Tusa, C. J. Bernardos, R. Szabo
IEEE IFIP Network Operations and Management Symposium Cognitive Management in A Cyber World NOMS 2018, 2018 - HARMLESS: Cost-Effective Transitioning to SDN for Small Enterprises
Levente Csikor, Laszlo Toka, Mark Szalay, Gergely Pongracz, Dimitrios P. Pezaros, Gabor Retvari
2018 IFIP Networking Conference IFIP Networking and Workshops IFIP Networking 2018 Proceedings, 2018 - HARMLESS: Cost-Effective Transitioning to SDN for Small Enterprises
17th International IFIP Tc6 Networking Conference Networking 2018, 2018 - Network Management and Orchestration
Luis M. Contreras, Víctor López, Ricard Vilalta, Ramon Casellas, Raúl Muñoz, Wei Jiang, Hans Schotten, Jose Alcaraz‐Calero, Qi Wang, Balázs Sonkoly, László Toka
5g System Design Architectural and Functional Considerations and Long Term Research, 2018 - The orchestration in 5G exchange - A multi-provider NFV framework for 5G services
Balazs Gero, Carlos Jesus Bernardos Cano, Luis Miguel Contreras Murillo, David Jocha, Robert Szabo, Janos Czentye, David Haja, Balazs Nemeth, Balazs Sonkoly, Mark Szalay, Laszlo Toka
2017 IEEE Conference on Network Function Virtualization and Software Defined Networks Nfv Sdn 2017, 2017 - A resource-aware and time-critical IoT framework
Laszlio Toka, Balazs Lajtha, Eva Hosszu, Bence Formanek, Daniel Gehberger, Janos Tapolcai
Proceedings IEEE INFOCOM, 2017 - Making the data plane ready for NFV: An effective way of handling resources
Marton Szabo, Andras Majdan, Gergely Pongracz, Laszlo Toka, Balazs Sonkoly
SIGCOMM Posters and Demos 2017 Proceedings of the 2017 SIGCOMM Posters and Demos Part of SIGCOMM 2017, 2017 - HARMLESS: Cost-effective transitioning to SDN
Márk Szalay, László Toka, Gábor Rétvári, Gergely Pongrácz, Levente Csikor, Dimitrios P. Pezaros
SIGCOMM Posters and Demos 2017 Proceedings of the 2017 SIGCOMM Posters and Demos Part of SIGCOMM 2017, 2017 - Orchestration of Network Services across multiple operators: The 5G Exchange prototype
A. Sgambelluri, F. Tusa, M. Gharbaoui, E. Maini, L. Toka, J. M. Perez, F. Paolucci, B. Martini, W. Y. Poe, J. Melian Hernandes, A. Muhammed, A. Ramos, O. G. de Dios, B. Sonkoly, P. Monti, I. Vaishnavi, C. J. Bernardos, R. Szabo
Eucnc 2017 European Conference on Networks and Communications, 2017 - On Measuring the Geographic Diversity of Internet Routes
Attila Csoma, Andras Gulyas, Laszlo Toka
IEEE Communications Magazine, 2017 - Analysis of end-to-end multi-domain management and orchestration frameworks for software defined infrastructures: An architectural survey
Riccardo Guerzoni, Ishan Vaishnavi, David Perez Caparros, Alex Galis, Francesco Tusa, Paolo Monti, Andrea Sganbelluri, Gergely Biczók, Balasz Sonkoly, Laszlo Toka, Aurora Ramos, Javier Melián, Olivier Dugeon, Filippo Cugini, Barbara Martini, Paola Iovanna, Giovanni Giuliani, Ricardo Figueiredo, Luis Miguel Contreras‐Murillo, Carlos J. Bernardos, Cristina Santana, Robert Szabo
Transactions on Emerging Telecommunications Technologies, 2017 - On Pricing of 5G Services
Laszlo Toka, Janos Tapolcai, George Darzanos, Balazs Sonkoly
Proceedings IEEE Global Communications Conference Globecom, 2017 - Manufactured by software: SDN-enabled multi-operator composite services with the 5G exchange
Gergely Biczok, Manos Dramitinos, Laszlo Toka, Poul E. Heegaard, Hakon Lonsethagen
IEEE Communications Magazine, 2017 - NFPA: Network function performance analyzer
Levente Csikor, Mark Szalay, Balazs Sonkoly, Laszlo Toka
2015 IEEE Conference on Network Function Virtualization and Software Defined Network Nfv Sdn 2015, 2016 - Sharing is power: Incentives for information exchange in multi-operator service delivery
Poul E. Heegaard, Gergely Biczok, Laszlo Toka
Proceedings IEEE Global Communications Conference Globecom, 2016 - On measuring the geographic diversity of internet routes
Infocommunications Journal, 2015 - On lower estimating internet queuing delay
Attila Csoma, Laszlo Toka, Andras Gulyas
2015 38th International Conference on Telecommunications and Signal Processing Tsp 2015, 2015 - On pricing online data backup
Laszlo Toka, Gergely Biczók
Proceedings IEEE INFOCOM, 2015 - Adaptive redundancy management for durable P2P backup
Matteo Dell’Amico, Pietro Michiardi, Laszlo Toka, Pasquale Cataldi
Computer Networks, 2015 - Redundancy management for P2P backup
Laszlo Toka, Pasquale Cataldi, Matteo Dell'Amico, Pietro Michiardi
Proceedings IEEE INFOCOM, 2012 - Analysis of user-driven peer selection in peer-to-peer backup and storage systems
Laszlo Toka, Pietro Michiardi
Telecommunication Systems, 2011 - Incentivizing the global wireless village
Gergely Biczók, László Toka, András Gulyás, Tuan A. Trinh, Attila Vidács
Computer Networks, 2011 - Data transfer scheduling for P2P storage
Laszlo Toka, Matteo Dell'Amico, Pietro Michiardi
2011 IEEE International Conference on Peer to Peer Computing P2p 2011 Proceedings, 2011 - Automatic protocol signature generation framework for deep packet inspection
Géza Szabó, Zoltán Turányi, László Toka, Sándor Molnár, Alysson Santos
Valuetools 2011 5th International Icst Conference on Performance Evaluation Methodologies and Tools, 2011 - On distributed dynamic spectrum allocation for sequential arrivals
Laszlo Toka, Attila Korosi, Attila Vidacs
2010 IEEE Symposium on New Frontiers in Dynamic Spectrum Dyspan 2010, 2010 - Online data backup: A peer-assisted approach
L. Toka, M. Dell'Amico, P. Michiardi
2010 IEEE 10th International Conference on Peer to Peer Computing P2p 2010 Proceedings, 2010 - General distributed economic framework for dynamic spectrum allocation
László Toka, Attila Vidács
Computer Communications, 2009 - On incentives in global wireless communities
Gergely Biczók, László Toka, Attila Vidacs, Tuan A. Trinh
Proceedings of the 2009 ACM Conference on Emerging Networking Experiments and Technologies Conext 09 Co Located 1st ACM Workshop on User Provided Networking Challenges and Opportunities U Net 09, 2009 - Selfish neighbor selection in peer-to-peer backup and storage applications
Pietro Michiardi, Laszlo Toka
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009 - Uncoordinated peer selection in P2P backup and storage applications
Laszlo Toka, Pietro Michiardi
Proceedings IEEE INFOCOM, 2009 - Distributed dynamic spectrum management
Tsp 2009 32nd International Conference on Telecommunications and Signal Processing, 2009 - Managing a peer-to-peer data storage system in a selfish society
Patrick Maille, Laszlo Toka
IEEE Journal on Selected Areas in Communications, 2008 - Brief announcement: A dynamic exchange game
Laszlo Toka, Pietro Michiardi
Proceedings of the Annual ACM Symposium on Principles of Distributed Computing, 2008 - Managing a peer-to-peer backup system: Does imposed fairness socially outperform a revenue-driven monopoly?
László Toka, Patrick Maillé
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
RECENT SCHOLAR PUBLICATIONS
- Survey on AI technologies aiding multicast and broadcast services in 5G and 6G
M Szabó, L Toka
Telecommunication Systems 89 (1), 27 , 2026
2026 - Temporal Graph Network Framework for Quantifying Pass Reception Probabilities Against Defensive Structures
P Rahimian, J Davis, L Toka
Machine Learning 115 (1), 6 , 2026
2026
Citations: 1 - Collaborative HD Map Creation: A Stackelberg Evolutionary Game Approach
M Szabó, L Toka
2025 IEEE 102nd Vehicular Technology Conference (VTC2025-Fall), 1-6 , 2025
2025 - Minimizing Energy Consumption of Satellite Edge Computing-Capable LEO Satellites
A Alnahdi, A Fayad, L Toka, T Cinkler
IEEE Access , 2025
2025
Citations: 1 - All about momentum: Investigating high-pressure situations in the NBA through scoring probability
B Mihályi, G Biczók, L Toka
International Journal of Sports Science & Coaching 20 (4), 1584-1597 , 2025
2025
Citations: 1 - Analyzing Energy Consumption of Loihi 2 Neuromorphic Chip in a Self-driving Use-case
Á Nagy, R Szabó, L Toka
2025 10th International Conference on Smart and Sustainable Technologies … , 2025
2025
Citations: 3 - 6G for connected sky: Holistic adaptive combined airspace and non terrestrial network architecture
S Zhang, M Ozger, SSSG Seeram, I Godor, L Feltrin, A Nordlow, J Pfeifle, ...
IEEE wireless communications , 2025
2025
Citations: 2 - Performance analysis in SailGP: A machine learning approach
B Zentai, L Toka
International Journal of Sports Science & Coaching 20 (3), 1207-1225 , 2025
2025
Citations: 1 - Dimensioning space-air-ground integrated networks for in-flight 6G slice orchestration
L Toka, EA Papp, T Cinkler, I Godor, L Hévizi
Vehicular Communications 51, 100866 , 2025
2025
Citations: 4 - Routing Leo Satellite Traffic in Adverse Weather
L Toka, Z Illes, A Papp, L Hevizi, I Godor
COMPUTER NETWORKS , 2025
2025
Citations: 1 - Anomaly-Aware Cloud Resource Management System Receiving External Information, and Including Short-and Long-Term Resource Planning
M Gutierrez, L Toka, B Fodor, B Sonkoly
US Patent App. 18/697,563 , 2024
2024 - Integrating the skies for 6G: Techno-economic considerations of LEO, HAPS, and UAV technologies
L Toka, M Konrad, A Pekar, G Biczók
IEEE Communications Magazine 62 (11), 44-51 , 2024
2024
Citations: 27 - Optimizing the edge computing system of a LEO satellite constellation
A Alnahdi, L Toka
2024 15th International Conference on Network of the Future (NoF), 124-132 , 2024
2024
Citations: 5 - A Survey on Integrating Edge Computing With AI and Blockchain in Maritime Domain, Aerial Systems, IoT, and Industry 4.0
A Alnahdi, L Toka
IEEE Access 12, 136907-136907 , 2024
2024
Citations: 54 - In-game soccer outcome prediction with offline reinforcement learning
P Rahimian, BM Mihalyi, L Toka
Machine Learning 113 (10), 7393-7419 , 2024
2024
Citations: 18 - A career handbook for professional soccer players
B Ács, R Kovács, L Toka
International Journal of Sports Science & Coaching 19 (1), 444-458 , 2024
2024
Citations: 3 - Towards maximizing expected possession outcome in soccer
P Rahimian, J Van Haaren, L Toka
International Journal of Sports Science & Coaching 19 (1), 230-244 , 2024
2024
Citations: 26 - A data-driven approach to assist offensive and defensive players in optimal decision making
P Rahimian, L Toka
International Journal of Sports Science & Coaching 19 (1), 245-256 , 2024
2024
Citations: 19 - Boat Speed Prediction in SailGP
B Zentai, L Toka
International Workshop on Machine Learning and Data Mining for Sports … , 2023
2023 - Momentum matters: investigating high-pressure situations in the NBA through scoring probability
B Mihalyi, G Biczók, L Toka
International Workshop on Machine Learning and Data Mining for Sports … , 2023
2023
MOST CITED SCHOLAR PUBLICATIONS
- 5G support for industrial IoT applications—challenges, solutions, and research gaps
P Varga, J Peto, A Franko, D Balla, D Haja, F Janky, G Soos, D Ficzere, ...
Sensors 20 (3), 828 , 2020
2020
Citations: 362 - Machine learning-based scaling management for kubernetes edge clusters
L Toka, G Dobreff, B Fodor, B Sonkoly
IEEE Transactions on Network and Service Management 18 (1), 958-972 , 2021
2021
Citations: 226 - Survey on placement methods in the edge and beyond
B Sonkoly, J Czentye, M Szalay, B Németh, L Toka
IEEE Communications Surveys & Tutorials 23 (4), 2590-2629 , 2021
2021
Citations: 114 - Traffic analysis for HTTP user agent based device category mapping
P Kersch, G Nemeth, L Toka
US Patent 9,755,919 , 2017
2017
Citations: 114 - Adaptive AI-based auto-scaling for Kubernetes
L Toka, G Dobreff, B Fodor, B Sonkoly
2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet … , 2020
2020
Citations: 91 - Analysis of end‐to‐end multi‐domain management and orchestration frameworks for software defined infrastructures: an architectural survey
R Guerzoni, I Vaishnavi, D Perez Caparros, A Galis, F Tusa, P Monti, ...
Transactions on Emerging Telecommunications Technologies 28 (4), e3103 , 2017
2017
Citations: 85 - Online data backup: A peer-assisted approach
L Toka, M Dell'Amico, P Michiardi
2010 IEEE Tenth International Conference on Peer-to-Peer Computing (P2P), 1-10 , 2010
2010
Citations: 65 - Real-time faas: Towards a latency bounded serverless cloud
M Szalay, P Matray, L Toka
IEEE Transactions on Cloud Computing 11 (2), 1636-1650 , 2022
2022
Citations: 59 - 6G for connected sky: A vision for integrating terrestrial and non-terrestrial networks
M Ozger, I Godor, A Nordlow, T Heyn, S Pandi, I Peterson, A Viseras, ...
2023 Joint European Conference on Networks and Communications & 6G Summit … , 2023
2023
Citations: 57 - Ultra-reliable and low-latency computing in the edge with kubernetes
L Toka
Journal of Grid Computing 19 (3), 31 , 2021
2021
Citations: 56 - A Survey on Integrating Edge Computing With AI and Blockchain in Maritime Domain, Aerial Systems, IoT, and Industry 4.0
A Alnahdi, L Toka
IEEE Access 12, 136907-136907 , 2024
2024
Citations: 54 - Transition to SDN is HARMLESS: Hybrid architecture for migrating legacy ethernet switches to SDN
L Csikor, M Szalay, G Rétvári, G Pongrácz, DP Pezaros, L Toka
IEEE/ACM Transactions On Networking 28 (1), 275-288 , 2020
2020
Citations: 54 - Sharpening kubernetes for the edge
D Haja, M Szalay, B Sonkoly, G Pongracz, L Toka
Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos, 136-137 , 2019
2019
Citations: 49 - Optical tracking in team sports: A survey on player and ball tracking methods in soccer and other team sports
P Rahimian, L Toka
Journal of Quantitative Analysis in Sports 18 (1), 35-57 , 2022
2022
Citations: 48 - Scalable edge cloud platforms for IoT services
B Sonkoly, D Haja, B Németh, M Szalay, J Czentye, R Szabó, R Ullah, ...
Journal of network and computer applications 170, 102785 , 2020
2020
Citations: 45 - Orchestration of network services across multiple operators: The 5G exchange prototype
A Sgambelluri, F Tusa, M Gharbaoui, E Maini, L Toka, JM Perez, ...
2017 European Conference on Networks and Communications (EuCNC), 1-5 , 2017
2017
Citations: 43 - Beyond action valuation: A deep reinforcement learning framework for optimizing player decisions in soccer
P Rahimian, J Van Haaren, T Abzhanova, L Toka
MIT Sloan Sports Analytics Conference , 2022
2022
Citations: 40 - Manufactured by software: SDN-enabled multi-operator composite services with the 5G exchange
G Biczok, M Dramitinos, L Toka, PE Heegaard, H Lonsethagen
IEEE Communications Magazine 55 (4), 80-86 , 2017
2017
Citations: 38 - Systems and Methods for Identifying Applications in Mobile Networks
P Hága, Z Kenesi, L Toka, A Veres
US Patent App. 14/268,529 , 2014
2014
Citations: 36 - NFPA: Network Function Performance Analyzer
L Csikor, M Szalay, B Sonkoly, L Toka
2015
Citations: 34
