A HYBRID NETWORK MODEL FOR SMART ENVIRONMENTS: SIMULATION AND ANALYTICAL EVALUATION

Abstract

Smart Environments (SE) require efficient and scalable network architectures to handle the increasing number of interconnected devices. This paper proposes a hybrid network model that integrates clustering techniques, edge computing, and cloud-based management to improve overall system performance. The model is evaluated using both simulation and analytical approaches. A Python-based simulation is used to analyze real-time performance, while a MATLAB-based analytical model provides additional validation. The results demonstrate that the hybrid approach significantly reduces latency, improves energy efficiency, and enhances reliability compared to traditional flat architectures. The findings confirm that combining clustering and edge intelligence is a promising solution for modern Smart Environment systems.