Integration and characterisation of the performance of fifth-generation mobile technology (5g) connectivity over the University of Oulu 5g test network (5gtn) for cognitive edge node based on fractal edge platform

Abstract. In recent years, there has been a growing interest in cognitive edge nodes, which are intelligent devices that can collect and process data at the edge of the network. These nodes are becoming increasingly important for various applications such as smart cities, industrial automation, and healthcare. However, implementing cognitive edge nodes requires a reliable and efficient communication network. Therefore, this thesis assesses the performance of direct cellular (5G) and IEEE 802.11-based Wireless Local Area Network (WLAN) technology for three network architectures, which has the potential to offer low-latency, high-throughput and energy-efficient communication, for cognitive edge nodes. The study focused on evaluating the network performance metrics of throughput, latency, and power consumption for three different FRACTAL-based network architectures. These architectures include IEEE 802.11-based last mile, direct cellular (5G) backbone, and IEEE 802.11-based last mile over cellular (5G) backbone topologies. This research aims to provide insights into the performance of 5G technology for cognitive edge nodes. The findings suggest that the power consumption of IEEE 802.11-enabled nodes was only slightly higher than the reference case, indicating that it is more energy-efficient than 5G-enabled nodes. Additionally, in terms of latency, IEEE 802.11 technology may be more favourable. The throughput tests revealed that the cellular (5G) connection exhibited high throughput for communication between a test node and an upper-tier node situated either on the internet or at the network edge. In addition, it was found that the FRACTAL edge platform is flexible and scalable, and it supports different wireless technologies, making it a suitable platform for implementing cognitive edge nodes. Overall, this study provides insights into the potential of 5G technology and the FRACTAL edge platform for implementing cognitive edge nodes. The results of this research can be valuable for researchers and practitioners working in the field of wireless communication and edge computing, as it sheds light on the feasibility and performance of these technologies for implementing cognitive edge nodes in various applications

Wireless power transfer for bluetooth low energy based IoT device:an empirical study of energy performance

Abstract Radio Frequency (RF) Wireless Power Transfer (WPT) is a prospective technology promising to enable unintermittent and maintenance-free operation of IoT devices. In this paper, we shed some light on the energy performance of the state-of-the-art RF-WPT in Bluetooth Low Energy (BLE) and IoT hardware platforms, specifically the Powercast P21XXCSREVB and the Texas Instruments CC2652R1 multi-radio protocol system-on-chip. For this, we first study the energy consumption of the CC2652R1 communicating over BLE technology in advertising mode, and the effect of the different BLE configuration parameters, such as transmit power, the number of channels, advertising interval and size of advertising packet, have on the energy consumption. Next, we investigate how much energy can be harvested and stored in the P21XXCSR-EVB, when RF transmission is from a dedicated WPT equipment. Finally, we integrate both elements to instrument a WPT-powered IoT device communicating over BLE, and investigate its energy consumption. Our results show the feasibility of instrumenting a WPT-powered IoT device today, while revealing some challenges and limitations of this approach. We believe that our results can be a reference for new designs, further optimizations and analytic/simulation models for WPT-powered IoT