Empirical Characterization of Wireless Connectivity Performance for Cognitive Edge IoT Nodes
Warnakulasuriya, Diluna Adeesha; Mikhaylov, Konstantin (2023-12-05)
IEEE
05.12.2023
D. A. Warnakulasuriya and K. Mikhaylov, "Empirical Characterization of Wireless Connectivity Performance for Cognitive Edge IoT Nodes," 2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Ghent, Belgium, 2023, pp. 73-80, doi: 10.1109/ICUMT61075.2023.10333267
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© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202312083599
https://urn.fi/URN:NBN:fi:oulu-202312083599
Tiivistelmä
Abstract
Cognitive edge nodes are becoming increasingly important for various Internet of Things (IoT) applications, requiring reliable, efficient and ubiquitous communication. This paper evaluates the performance of direct cellular (5G) and IEEE 802.11-based Wireless Local Area Network (WLAN) technology for cognitive edge nodes based on FRACTAL platform. The FRACTAL edge platform is designed to be flexible, scalable and support different wireless technologies. The study assesses the network performance in terms of throughput, latency, and power consumption for three different network architectures. The findings reveal that IEEE 802.11 technology is more energy-efficient and favourable for latency for peer-to-peer communication scenarios, while 5G technology demonstrates high throughput for communication between a test node and an upper-tier edge node. This research sheds light on the feasibility and performance of these technologies for implementing cognitive edge nodes in various applications and respective interplays, providing valuable insights for researchers and practitioners in the field of wireless communication and edge computing.
Cognitive edge nodes are becoming increasingly important for various Internet of Things (IoT) applications, requiring reliable, efficient and ubiquitous communication. This paper evaluates the performance of direct cellular (5G) and IEEE 802.11-based Wireless Local Area Network (WLAN) technology for cognitive edge nodes based on FRACTAL platform. The FRACTAL edge platform is designed to be flexible, scalable and support different wireless technologies. The study assesses the network performance in terms of throughput, latency, and power consumption for three different network architectures. The findings reveal that IEEE 802.11 technology is more energy-efficient and favourable for latency for peer-to-peer communication scenarios, while 5G technology demonstrates high throughput for communication between a test node and an upper-tier edge node. This research sheds light on the feasibility and performance of these technologies for implementing cognitive edge nodes in various applications and respective interplays, providing valuable insights for researchers and practitioners in the field of wireless communication and edge computing.
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