@article{MTMT:34559046,
	title = {Energy-Efficient Joint User and Power Allocation in 5G Millimeter Wave Networks: A Genetic Algorithm-based Approach},
	url = {https://m2.mtmt.hu/api/publication/34559046},
	author = {Fayad, Abdulhalim and Cinkler, Tibor},
	doi = {10.1109/ACCESS.2024.3361660},
	journal-iso = {IEEE ACCESS},
	journal = {IEEE ACCESS},
	volume = {12},
	unique-id = {34559046},
	year = {2024},
	eissn = {2169-3536},
	pages = {20019-20030}
}

@article{MTMT:34751443,
	title = {Boat Speed Prediction in SailGP},
	url = {https://m2.mtmt.hu/api/publication/34751443},
	author = {Zentai, B. and Toka, László},
	doi = {10.1007/978-3-031-53833-9_13},
	journal-iso = {COMMUN COMPUT INFORM SCI},
	journal = {COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE},
	volume = {2035},
	unique-id = {34751443},
	issn = {1865-0929},
	abstract = {The significance of data analysis in high-performance sports has largely increased in recent years offering opportunities for further exploration using machine learning techniques. 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. Specifically, we explore the application of data mining techniques on the dataset collected at a high-performance sailing event in Bermuda in 2021. By analyzing data from Race 4, the study aims to gain valuable insights into the relationship between variables such as wind speed, wind direction, foil usage, and daggerboard adjustments, and their impact on boat speed. 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. These findings can be utilized to refine race strategies, optimize sail and rudder settings, and improve overall performance in SailGP races. Future plans include collaboration with SailGP to work with larger datasets and integrate the models into live racing scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
	keywords = {PERFORMANCE; prediction; Learning systems; Forecasting; data mining; POWER; decision making; Forestry; Sports; Mean square error; Wind speed; Data-driven approach; Machine learning techniques; Boats; Academic community; data-mining techniques; Speed prediction; Decisions makings; boat speed; boat speed; Sailing analytics; Sailing analytic},
	year = {2024},
	eissn = {1865-0937},
	pages = {155-164},
	orcid-numbers = {Toka, László/0000-0003-1045-9205}
}

@article{MTMT:34751450,
	title = {Pass Receiver and Outcome Prediction in Soccer Using Temporal Graph Networks},
	url = {https://m2.mtmt.hu/api/publication/34751450},
	author = {Rahimian, Pegah and Kim, H. and Schmid, M. and Toka, László},
	doi = {10.1007/978-3-031-53833-9_5},
	journal-iso = {COMMUN COMPUT INFORM SCI},
	journal = {COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE},
	volume = {2035},
	unique-id = {34751450},
	issn = {1865-0929},
	abstract = {This paper explores the application of the Temporal Graph Network (TGN) model to predict the receiver and outcome of a pass in soccer. We construct two TGN models that estimate receiver selection probabilities (RSP) and receiver prediction probabilities (RPP) to predict the intended and actual receivers of a given pass attempt, respectively. Then, based on these RSP and RPP, we compute the success probability (CPSP) of each passing option that the pass is successfully sent to the intended receiver as well as the overall pass success probability (OPSP) of a given situation. The proposed framework provides deeper insights into the context around passes in soccer by quantifying the tendency of passers’ choice of passing options, difficulties of the options, and the overall difficulty of a given passing situation at once. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
	keywords = {Forecasting; Sports; Multi agent systems; outcome prediction; Network models; Temporal graphs; Multi agent; Graph neural networks; Graph Networks; Soccer analytics; Multi-Agent Analysis; Pass Receiver Prediction; Pass Receiver Prediction; Multi-agent analyse; Pass outcome prediction; Pass outcome prediction; Soccer analytic; Temporal graph network; Temporal graph network},
	year = {2024},
	eissn = {1865-0937},
	pages = {52-63},
	orcid-numbers = {Toka, László/0000-0003-1045-9205}
}

@article{MTMT:34751452,
	title = {Momentum Matters: Investigating High-Pressure Situations in the NBA Through Scoring Probability},
	url = {https://m2.mtmt.hu/api/publication/34751452},
	author = {Mihályi, Balázs Márk and Biczók, Gergely and Toka, László},
	doi = {10.1007/978-3-031-53833-9_7},
	journal-iso = {COMMUN COMPUT INFORM SCI},
	journal = {COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE},
	volume = {2035},
	unique-id = {34751452},
	issn = {1865-0929},
	abstract = {One of the defining characteristics of real basketball stars, and even great role players, is how well they perform under immense mental pressure. In this paper, we present a method to identify high-pressure situations during a basketball game through shooting success. In order to calculate the amount of pressure a team is facing going into a game, we use a prediction model to determine the importance of the given game for that team to reach their end-of-season goal. The model relies on features referring to game context, recent form, and pre-season aspirations. We then investigate the impact of our pre-game pressure metric, along with other factors, on the shooting performance of NBA players on six seasons’ worth of data. We find that shotmaking in the NBA is mainly impacted by the so-called momentum, i.e., when a team outscores their opponent significantly over a short period of time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
	keywords = {PERFORMANCE; PERFORMANCE; high pressure; Basketball; Sports; scoring; scoring; MOMENTUM; MOMENTUM; Prediction modelling; Short periods; shooting performance; Basketball games; mental pressure; mental pressure; Pressure situation},
	year = {2024},
	eissn = {1865-0937},
	pages = {77-90},
	orcid-numbers = {Mihályi, Balázs Márk/0009-0007-5766-4018; Toka, László/0000-0003-1045-9205}
}

@article{MTMT:33638899,
	title = {Minimizing Resource Allocation for Cloud-Native Microservices},
	url = {https://m2.mtmt.hu/api/publication/33638899},
	author = {Erdei, Roland and Toka, László},
	doi = {10.1007/s10922-023-09726-3},
	journal-iso = {J NETW SYST MANAG},
	journal = {JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT},
	volume = {31},
	unique-id = {33638899},
	issn = {1064-7570},
	abstract = {With the continuous progress of cloud computing, many microservices and complex multi-component applications arise for which resource planning is a great challenge. For example, when it comes to data-intensive cloud-native applications, the tenant might be eager to provision cloud resources in an economical manner while ensuring that the application performance meets the requirements in terms of data throughput. However, due to the complexity of the interplay between the building blocks, adequately setting resource limits of the components separately for various data rates is nearly impossible. In this paper, we propose a comprehensive approach that consists of measuring the resource footprint and data throughput performance of such a microservices-based application, analyzing the measurement results by data mining techniques, and finally formulating an optimization problem that aims to minimize the allocated resources given the performance constraints. We illustrate the benefits of the proposed approach on Cortex, an extension to Prometheus for storing monitored metrics data. The data-intensive nature of this illustrative example stems from real-time monitoring of metrics exposed by a multitude of applications running in a data center and the continuous analysis performed on the collected data that can be fetched from Cortex. We present Cortex’s performance vs resource footprint trade-off, and then we build regression models to predict the microservices’ resource consumption and draw a mathematical programming formulation to optimize the most important configuration parameters. Our most important finding is the linear relationship between resource consumption and application performance, which allows for applying linear regression and linear programming models. After the optimization, we compare our results to Cortex’s recommendation, leading to a CPU reservation reduced by 50–80%.},
	year = {2023},
	eissn = {1573-7705},
	orcid-numbers = {Toka, László/0000-0003-1045-9205}
}

@inproceedings{MTMT:33667720,
	title = {Towards realistic simulation of MEC-based Collective Perception: an initial edge service design for the Artery/Simu5G framework},
	url = {https://m2.mtmt.hu/api/publication/33667720},
	author = {Kovács, Gergely Attila and Bokor, László},
	booktitle = {Proceedings of the 1st Workshop on Intelligent Infocommunication Networks, Systems and Services (WI2NS2)},
	doi = {10.3311/WINS2023-010},
	unique-id = {33667720},
	abstract = {Day 2 V2X applications are the next step in vehicular communications, as they aim to extend the scope of shared information. In addition to status data, traffic participants are also aware of each other's sensory capabilities and the data deriving from those sensors. Collective Perception (CP), one of the flagship Day 2 services, enables vehicles and infrastructural elements, like roadside units or smart intersection controllers, to provide information about detected objects, significantly increasing the level of cooperative awareness V2X can grant for the communicating entities. However, with the escalation in the amount of data to be sent over the vehicular or mobile networks and the need for more processing power to enable real-time safety applications based on CP, some form of infrastructural aid is needed. The traditional central cloud-based approach might fall short of meeting the latency requirements. To keep latency within an acceptable range and solve the computational tasks locally, leveraging the capabilities of 5G Multi-access Edge Computing (MEC) could be a potential solution, thus ensuring a minimum impact on the core network. The architectural design and the modular approach of service implementation in the MEC specification by ETSI enable quick service deployment. This paper focuses on advanced Collective Perception-based V2X applications and the potential positive impact on their performance when operating with the support of edge computing. We also present the description – including the design considerations – of an initial, Artery/Simu5G-based edge service model working as a network-side intelligence extending the functionality of applications hosted on the vehicles.},
	year = {2023},
	pages = {1-6},
	orcid-numbers = {Kovács, Gergely Attila/0009-0003-7952-3145}
}

@article{MTMT:33780195,
	title = {Closed-loop Orchestration for Cloud-native Mobile IPv6},
	url = {https://m2.mtmt.hu/api/publication/33780195},
	author = {Leiter, Ákos and Lami, Edina and Hegyi, Attila and Varga, József and Bokor, László},
	doi = {10.36244/ICJ.2023.1.5},
	journal-iso = {INFOCOMMUNICATIONS J},
	journal = {INFOCOMMUNICATIONS JOURNAL},
	volume = {15},
	unique-id = {33780195},
	issn = {2061-2079},
	abstract = {With the advent of Network Function Virtualization (NFV) and Software-Defined Networking (SDN), every network service type faces significant challenges induced by novel requirements. Mobile IPv6, the well-known IETF standard for network-level mobility management, is not an exemption. Cloud-native Mobile IPv6 has acquired several new capabilities due to the technological advancements of NFV/SDN evolution. This paper presents how automatic failover and scaling can be envisioned in the context of cloud-native Mobile IPv6 with closed-loop orchestration on the top of the Open Network Automation Platform. Numerical results are also presented to indicate the usefulness of the new operational features (failover, scaling) driven by the cloud-native approach and highlight the advantages of network automation in virtualized and softwarized environments.},
	year = {2023},
	eissn = {2061-2125},
	pages = {44-54},
	orcid-numbers = {Leiter, Ákos/0000-0003-1323-6541; Bokor, László/0000-0003-1870-8544}
}

@article{MTMT:33781827,
	title = {P4-assisted seamless migration of serverless applications towards the edge continuum},
	url = {https://m2.mtmt.hu/api/publication/33781827},
	author = {Pelle, István and Paolucci, Francesco and Sonkoly, Balázs and Cugini, Filippo},
	doi = {10.1016/j.future.2023.04.010},
	journal-iso = {FUTUR GENER COMP SYST},
	journal = {FUTURE GENERATION COMPUTER SYSTEMS},
	volume = {146},
	unique-id = {33781827},
	issn = {0167-739X},
	year = {2023},
	eissn = {1872-7115},
	pages = {122-138},
	orcid-numbers = {Pelle, István/0000-0003-2514-3019; Paolucci, Francesco/0000-0003-4821-5193; Sonkoly, Balázs/0000-0002-4640-388X}
}

@inproceedings{MTMT:33792422,
	title = {Towards an Edge Cloud Based Coordination Platform for Multi-User AR Applications Built on Open-Source SLAMs},
	url = {https://m2.mtmt.hu/api/publication/33792422},
	author = {Sonkoly, Balázs and Nagy, Bálint György and Dóka, János and Kecskés-Solymosi, Zsófia and Czentye, János Emánuel and Formanek, Bence and Jocha, Dávid and Gerő, Balázs Péter},
	booktitle = {2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)},
	doi = {10.1109/VRW58643.2023.00304},
	unique-id = {33792422},
	abstract = {Multi-user and collaborative AR applications pose several challenges. The expected user experience requires accurate pose information for each device and precise synchronization of the respective coordinate systems in real-time. Unlike mobile phones or AR glasses running on battery with constrained resource capacity, cloud and edge platforms can provide the computing power for the core functions under the hood. In this paper, we propose a novel edge cloud based platform for multi-user AR applications realizing an essential coordination service among the users. The latency critical, computation intensive Simultaneous Localization And Mapping (SLAM) function is offloaded from the device to the edge cloud infrastructure.},
	year = {2023},
	pages = {923-924},
	orcid-numbers = {Sonkoly, Balázs/0000-0002-4640-388X; Czentye, János Emánuel/0000-0001-7075-309X}
}

@inproceedings{MTMT:33845812,
	title = {P4-based Hitless FaaS Load Balancer for Packet-Optical Network Edge Continuum},
	url = {https://m2.mtmt.hu/api/publication/33845812},
	author = {Pelle, István and Paolucci, Francesco and Sonkoly, Balázs and Cugini, Filippo},
	booktitle = {Optical Fiber Communication Conference (OFC) 2023},
	doi = {10.1364/OFC.2023.Th1D.5},
	unique-id = {33845812},
	abstract = {P4 and novel node telemetry are leveraged to provide load balancing of ultra-low latency serverless application to multiple edges. Handling the overload of one edge without observable change in application delay is demonstrated.},
	year = {2023},
	orcid-numbers = {Pelle, István/0000-0003-2514-3019; Sonkoly, Balázs/0000-0002-4640-388X}
}