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001-es BibID:BIBFORM068837
Első szerző:Gál Zoltán (informatikus)
Cím:Anaysis of controller based IEEE 802.11 system with similarity measure clustering : Evaluation of channel allocation efficiency by change detection / Zoltan Gal, Gyorgy Terdik
Dátum:2017
Megjegyzések:IEEE Catalog Number CFP17F05-USB
The efficiency of a WiFi system with dozens of base stations in relatively small physical area is determined by the optimal allocation of the radio channels to the mobile devices. Based on the increased penetration rate of the high traffic capable smartphones and accentuated usage of these devices in densely populated buildings intelligent hardware tools are needed to offer QoS level to the users. The Radio Resource Management (RRM) of IEEE 802.11 network is provided by a wireless LAN controller. This node maintains an allocated control connection to each of the base stations providing enhanced quality level of the WiFi hot zone services. Modern base stations have the capability to listen to the radio channels periodically to detect the received signal intensity. The controller samples periodically each of the radio channels without affecting the own radio frame processing and collects in this way radio resource usage. Based on specific criteria like the number of active nodes, traffic intensity, interference, noise intensity the periodically executed RRM management algorithm modifies the distribution of active channels on the supervised hot zone level. The radio signal intensity scanning task is considered to be performed by the base stations as a sampling process of individual sensors distributed in physical space. Eighteen WiFi access points with thirteen channel sensors in 2.4 GHz range and sixteen channel sensors in 5 GHz range were used to capture radio signal intensity in a densely populated building. Holding special criteria in the scanned signal intensity values is considered as a complex event. Clustering method based on similarity measure was used to analyse sensor grouping behavior of the wireless controller RRM algorithm. Our work is focused on the usability of different statistical metrics (i.e. Hurst, Davies-Bouldin, etc.) to characterize intrusion detection efficiency of the wireless LAN controller.
ISBN:978-1-5090-5834-1
Tárgyszavak:Műszaki tudományok Informatikai tudományok tanulmány, értekezés
Clustering
Complex Event Processing
Davies-Bouldin index
Hurst exponent
Internet of Things
Self-Similarity
Sensor Network
Special Event Detection
WiFi LAN
Megjelenés:2017 5th International Symposium on Digital Forensic and Security (ISDFS) Petru Maior University Tîrgu Mureș, Romania April 26-28, 2017 / eds. Genge Béla, Haller Piroska. - p. 1-6. -
További szerzők:Terdik György (1949-) (matematikus, informatikus)
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