RIoT Digital Twin: Modeling, Deployment, and Optimization of Reconfigurable IoT System with Optical-Radio Wireless Integration

Abstract

This paper proposes an optimized Reconfigurable Internet of Things (RIoT) framework that integrates optical and radio wireless technologies with a focus on energy efficiency, scalability, and adaptability. To address the inherent complexity of hybrid optical-radio environments, a high-fidelity Digital Twin (DT) is developed within the Network Simulator 3 (NS-3) platform. The DT models deploy subsystems of the RIoT architecture, including radio frequency (RF) communication, optical wireless communication (OWC), and energy harvesting and consumption mechanisms that enable autonomous operation. Real-time energy and power measurements from target hardware platforms are also incorporated to ensure accurate representation of physical behavior and enable runtime analysis and optimization. Building on this foundation, a proactive cross-layer optimization strategy is devised to balance energy efficiency and quality of service (QoS). The strategy dynamically reconfigures RIoT nodes by adapting transmission rates, wake/sleep scheduling, and access technology selection. Results demonstrate that the proposed framework, combining digital twin technology, hybrid optical-radio integration, and data-driven energy modeling, substantially enhances the performance, resilience, and sustainability of 6G IoT networks.