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001-es BibID:BIBFORM094402
035-os BibID:(cikkazonosító)103010
Első szerző:Gál Zoltán (informatikus)
Cím:Performance evaluation of massively parallel and high speed connectionless vs. connection oriented communication sessions / Gál Zoltán, Kocsis Gergely, Tajti Tibor, Tornai Robert
Dátum:2021
ISSN:0965-9978
Megjegyzések:In this paper we focus on the fast communication issues of the Big Data processing tasks shared between High Performance Computing systems. In our performance evaluation framework we designed and developed two traffic measurement tools in order to answer some theoretical questions related to congestion control in practice. The first one is based on iperf and tcpdump softwares to capture data flows of TCP and UDP sessions. Classification aspects of the measurement cases were: homogeneity of the traffics, number of parallel communication sessions, and implementation types of the TCP congestion control algorithm. Dozens of parallel traffic scenarios were executed in a dumbbell topology to evaluate effects of the massively parallel communication sessions in wireline local and metropolitan area networks. Since we found that connection oriented data transfer sessions have limited performance features during communication, we implemented a second communication tool named Fast Manager of File Transfer (FMFT). This application with transfer rate monitoring and regulation capability is based on parallel connectionless data transfer sessions supervised by a common connection oriented control session and provides better transfer rate than the classical file transfer mechanisms using TCP services. Methodology of the statistical analysis and highlights of this heterogeneous parallel communication mechanism are explained, too.
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
High speed networking
High performance computing
Parallel communication
Internet
Congestion control
Traffic engineering
Statistical analysis
Scale independence
Megjelenés:Advances In Engineering Software. - 157-158 (2021), p. 1-20. -
További szerzők:Kocsis Gergely (1983-) (programtervező matematikus) Tajti Tibor Gábor (1970-) (informatikus) Tornai Róbert (1976-) (informatikus, matematikus)
Pályázati támogatás:EFOP-3.6.3-VEKOP-16-2017-00002
EFOP
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2.

001-es BibID:BIBFORM079185
035-os BibID:(cikkazonosító)34
Első szerző:Gál Zoltán (informatikus)
Cím:Performance evaluation of massively parallel communication sessions / Z. Gál, I. Varga, T. Tajti, G. Kocsis, Z. Langmajer, M. Kosa, J. Panovics
Dátum:2019
Megjegyzések:Main issues of the Big Data processing imply high speed transmission between different nodes of the infocommunication system. Best effort based datagram delivery of the protocol data units requires bandwidth in the scale of n*10 Mb/s for time critical services. Although IntServ and DiffServ QoS mechanisms make possible for time critical data flows to be forwarded in reasonable conditions, high speed transmission of the big data in LAN/WAN environments remains hot topic. Different implementations of the TCP congestion control mechanism were developed in the last decades. The QoS strategies applied in LAN environment are weakly usable in wide area data networks producing low usage efficiency of the communication path traversing different ISPs. In our performance evaluation framework we developed an own measurement tool based on iperf and tcpdump software to capture data flows of TCP and UDP sessions. Classification aspects of the measurement cases were: homogeneity of the traffics, number of parallel communication sessions and implementation types of the TCP congestion control algorithm. High number of traffic scenarios were executed in a dump-bell topology. Statistical analysis methods were used to evaluate effects of the aspects mentioned above in the wireline local and metropolitan area networks.
ISBN:978-1-905088-67-6
Tárgyszavak:Természettudományok Matematika- és számítástudományok előadáskivonat
high speed networking
parallel communication
congestion control
traffic engineering
statistical analysis
scale independence
Megjelenés:Proceedings of the Sixth International Conference on Parallel, Distributed, GPU and Cloud Computing for Engineering / ed. P. Iványi, B. H. V. Topping. - p. 1-19. -
További szerzők:Varga Imre (1979-) (fizikus, informatikus) Tajti Tibor Gábor (1970-) (informatikus) Kocsis Gergely (1983-) (programtervező matematikus) Langmajer Z. Kósa Márk (1975-) (programtervező matematikus) Pánovics János (1975-) (programtervező matematikus)
Pályázati támogatás:FIKP-20428-3/2018/FEKUTSTRAT
FIKP
EFOP-3.6.3-VEKOP-16-2017-00002
EFOP
Internet cím:Intézményi repozitóriumban (DEA) tárolt változat
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3.

001-es BibID:BIBFORM062529
035-os BibID:Zbl.06476013
Első szerző:Gál Zoltán (informatikus)
Cím:Surprise event detection of the supercomputer execution queues / Zoltán Gál, Tibor Tajti, György Terdik
Dátum:2015
ISSN:1787-5021 1878-6117
Megjegyzések:Huge amount of data is generated by and collected from the IoT (Internet of Things) physical and virtual devices. These sets of data series reflect in complex form the state of a given system in multidimensional space. Healthiness evaluation of a given system implies state analysis with enhanced methods. Special events can appear during the execution of jobs in a supercomputer (HPC - High Performance Computer) system. Depending on the HPC architecture hundreds or thousands of computation nodes are working in parallel. The scheduler of the HPC front-end node manages different queues (parallel, serial, test, etc.) of the job execution. The multitude of data series captured periodically with several tens of thousands of samples creates a set of several dozen variables for each computation node. The healthiness of the whole HPC system is a temporal concept in the term of 2D or 4D multidimensional time-space domains. In this paper we propose a healthiness evaluation method for each execution queue of a two different HPC system with 20 TFLOP/s and 5 TFLOP/s computation capacities, respectively. Time independent community structure is determined and controlled based on multiple similarity measures and ANN (Artificial Neural Network) based SOM (Self-Organized Map) algorithm. For each cluster of variables is determined a representing variable, including time specific and global characteristics of the own cluster. The resulting set of representing variables contains less than ten dissimilar time series. Wavelet methods are used for extreme event detection in time of each representing variable. The surprise event detection in time of the HPC execution queues is based on the simultaneity of extreme event fingerprints.
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény hazai lapban
High Performance Computer
sensors/actuators
IoT
Complex Event Processing
Event Stream Processing
Artificial Neural Networks
SOM
FFT
STFT
Wavelets
Megjelenés:Annales Mathematicae et Informaticae. - 44 (2015), p. 87-97. -
További szerzők:Tajti Tibor Gábor (1970-) (informatikus) Terdik György (1949-) (matematikus, informatikus)
Pályázati támogatás:TÁMOP-4.2.2.C-11/1/KONV-2012-0010
TÁMOP
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4.

001-es BibID:BIBFORM048982
Első szerző:Gál Zoltán (informatikus)
Cím:Complex event processing in supercomputer environment : sensor and neural network based analysis / Gál Zoltán, Tajti Tibor
Dátum:2013
Megjegyzések:Large number of sensors are running in the highperformance computer (HPC, supercomputer) environment todetect the hardware and software resource utilization during the jobs execution. Different state variables of the HPC system are detected by physical sensors but virtual sensors are producing important event information, as well. By measuring sensor data of different processes huge amount of state information is collected from the supercomputer during the execution time. Each of the time series collected in this way have special meaning and characterize the utilization of a given HPC resource subset. Having dozens of time series collected in parallel for each of the 128 computation nodes, complex event processing (CSP) methods are needed to evaluate the jobs execution efficiency. This paper gives a complex overview of a resource utilization analysis of 18 TFLOPS capacity HPC system with 1.5 thousand CPU cores. Advanced method is presented based on neural networks for defining clusters of the strongly correlated variables with 55 thousand samples each. Selection procedure of the representingvariable needed for each cluster. Method based on statistical analysis is proposed to evaluate jobs execution efficiency by the HPC system.
ISBN:978-1-4799-1543-9 978-1-4799-1546-0
Tárgyszavak:Természettudományok Matematika- és számítástudományok előadáskivonat
könyvrészlet
Complex Event Processing
Event Stream Processing
High Performance Computing
neural network
Self- Organizing Map
Tárgyak Internete (IoT)
Megjelenés:4th IEEE International Conference on Cognitive Infocommunications CogInfoCom 2013 : Proceedings, December 2-5, 2013 Budapest, Hungary / ed. Péter Baranyi. - p. 435-440. -
További szerzők:Tajti Tibor Gábor (1970-) (informatikus)
Pályázati támogatás:TÁMOP-4.2.2.C-11/1/KONV-2012-0001
TÁMOP
Tárgyak Internete és az IPv4/IPv6 rendszerekkel való integrációja
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5.

001-es BibID:bibKLT00105070
Első szerző:Terdik György (matematikus, informatikus)
Cím:A Debreceni Universitas lokális hálózatainak adatvédelmi és biztonsági bővítése / Terdik György, Gál Zoltán, Tajti Tibor
Dátum:1995
ISBN:963-04-8492-7
Tárgyszavak:Műszaki tudományok Informatikai tudományok előadáskivonat
könyvrészlet
Megjelenés:Networkshop '95 : Országos konferencia : Gödöllő 1995. április 19-21. / szerk. Bajza János, Tóth Beatrix. - p. 124-130. -
További szerzők:Gál Zoltán (1966-) (informatikus) Tajti Tibor Gábor (1970-) (informatikus)
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