Design and evaluation of a Python-based network automation system for internet of things devices

Abstract

The increasing demand for the internet of things (IoT) and massive machine-type communications has significantly expanded network size and complexity. Recent research indicates that 95% of network tasks are monitored manually, leading to configuration complexity, human errors, faults, downtime risks, and time consumption. Network automation emerges as a practical solution by reducing administrative overhead and enabling reliable, scalable, and self-managing networks through scripting and standardized programming languages. This paper proposes a model for automated networks using Python-based methods, specifically Paramiko, Netmiko, and the network automation and programmability abstraction layer with multivendor support (NAPALM), to configure the enhanced interior gateway routing protocol (EIGRP) within the graphical network simulator-3(GNS3) environment. The performance of the automated network was evaluated using two scenarios: with threading and without threading. Key metrics included execution time, configuration accuracy, error rates, and resource utilization. Simulation results demonstrate that the automated approach significantly outperforms manual configuration. In addition, the automated model with threading outperformed the automated model without threading, achieving execution time reductions up to 67% and 100% configuration accuracy with zero errors. These findings underscore the effectiveness of the proposed system for automating complex network tasks in large-scale IoT deployments.