Upcoming 5G technology and the demand for near real-time response services raise the need for optimizing current IoT solutions. The aim of this paper is to model and execute the performance analysis of network structures suitable for Edge Computing in IoT. The prior research into different topology and parameter sets have not provided sufficient clarity, on which parameters had a considerable impact on overall system performance; therefore, repetitive simulations were performed to express dispersion of alternating values, as well as determining its confidence intervals. The paper presents Edge Computing service simulation setup on known and newly derived network topologies with different complexity varying network bandwidth and network delay parameters. The experimental investigation has revealed that the IoT configuration network is more sensitive to network topology, while the Internet configuration is more sensitive to network parameters. The discussion on the results received debates possible causes of performance differences in network parameters and device configurations, the comparison to similar state-of-the-art research results has also been presented. Finally, conclusions with recommendations based on the results acquired have been provided.

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The article discusses vulnerability of wireless sensors networks to weather-based disruptions considering the opinions of different experts published in a range of scientific materials. The introduction provides a brief overview of wireless signals in real world conditions focusing on how weather affects signals (rain, fog and clouds, snow, hail, lightning, wind, bodies of water, trees and physical obstruction). Information about the effects of weather on wireless sensor networks using Free Space Optical / Radio Frequency (FSO/RF) communication is then provided. Finally, the impact of weather conditions on MANET routing protocols is considered theoretically, and experimental simulations are performed by comparing the sustainability of different protocols to different weather conditions. After analysis of experiment results, ideas on how to decrease vulnerability of wireless networks to weather-based disruptions are discussed.

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