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001-es BibID:BIBFORM087589
035-os BibID:(Scopus)85090827056
Első szerző:Gál Zoltán (informatikus)
Cím:IEEE 802.11n/ac/ax Hot Zone Traffic Evaluation with Neural Compute Stick Based RNN Methods 114-127 / Gál Zoltán, Polgár Péter
Dátum:2020
ISSN:1613-0073
Megjegyzések:The longer than twenty-two-year success marching of the IEEE 802.11 communication technology continues in the next years with new standard editions having transfer rate in the multi Gbit/s range. Realistic evaluation of the WiFi controller supervised hot zone service level becomes more and more critical because of the very high number of frames transmitted per unit of time. Online evaluation of the content transmission efficiency on radio channel is affected by several conditions including environment reflection characteristics, multipath influences, movement behaviour of the users and time dependence of the mobile terminals population in the service area. Based on our anterior investigations we found that in special places of the coverage area with WiFi hot zone service high ratio of transmitted frames are temporarily control and management frames even in case of communications with low level of the radio signals. To scan and evaluate IEEE 802.11/n/ac/ax channel usage efficiency we developed a complex scanner and evaluator tool based on neural network stick hardware. The software prototype developed utilize Long-Short Term Memory and Gated Recurrent Unit functions to determine periodically the percent of data frames of the total transmitted radio frames. Constant number of frames and constant time intervals, respectively are applied as two basic approaches of our evaluation methods. Advantages, weaknesses and usability cases in practice of the proposed solutions will be given in the paper.
Tárgyszavak:Műszaki tudományok Informatikai tudományok előadáskivonat
könyvrészlet
Internet of Things (IoT)
Wireless Fidelity (WiFi) Hot Zone
Quality of Service (QoS)
Recurrent Neural Network (RNN)
Long-Short Term Memory (LSTM)
Gated Recurrent Unit (GRU)
Convolutional Network
routing
clustering
time series classification
Megjelenés:Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020) / ed. Gergely Kovásznai, István Fazekas, Tibor Tómács. - p. 114-127. -
További szerzők:Polgár Péter (1996-) (informatikus)
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001-es BibID:BIBFORM094453
035-os BibID:(WoS)000654007400011 (Scopu)85107458834
Első szerző:Korteby, Mohamed Amine (informatikus)
Cím:Multi dimensional analysis of sensor communication processes / Mohmamed Amine Korteby, Zoltán Gál, Péter Polgár
Dátum:2021
ISSN:1787-5021 1787-6117
Megjegyzések:The Internet of Things requires communication mechanism to be optimal not only from the data transfer but from the energy consumption point of view, too. One of the most analyzed types of the sensor network is Low Energy Adaptive Clustering Hierarchy (LEACH) system depending on the population density, algorithm of cluster head election, heterogeneity of the energy and physical position of the nodes, velocity of the sink node, data aggregation rate and size of the data frame. Complexity of the system has been analyzed based on status data series of 360 simulation cases. New family of wireless sensor network (WSN) system is proposed with name CB-LEACH, having better characteristics than the classical LEACH system. The service ability of sensor network and dependency properties was done with analytic technique based on Singular Value Decomposition (SVD). Using this method there were identified most important modes serving as basis to regenerate responses of the studied sensor systems. It was found that the number of significant modes is just six. The novelty of the paper is a proof of concept that SVD is a useful multidimensional tool which can be used for describing the behavior of the newly proposed CB-LEACH family of sensor network mechanisms.
Tárgyszavak:Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény hazai lapban
folyóiratcikk
Wireless sensor networks
Low Energy Adaptive Clustering Hierrarchy (LEACH)
switching
cluster
classification analysis
Megjelenés:Annales Mathematicae et Informaticae. - 53 (2021), p. 169-182. -
További szerzők:Gál Zoltán (1966-) (informatikus) Polgár Péter (1996-) (informatikus)
Pályázati támogatás:EFOP-3.6.3-VEKOP-16-2017-00002
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