GRU-based digital twin framework for data allocation and storage in IoT-enabled smart home networks

Abstract

In recent years, the Internet of Things (IoT) devices utilization with Information Communication Technology (ICT) has grown exponentially in various Smart City applications, including Smart Homes, Smart Enterprises, and others. The fusion of IoT, ICT, and Smart Home delivers interactive solutions to reduce costs and resource consumption, enhance performance, and engage people's needs more virtually and proactively. A smart home has numerous advantages with the integration of emerging advanced technologies. Big data, centralization, data and resource allocation, security, and privacy issues persist as challenges in IoT-enabled Smart Home Networks. To address these challenges, in this paper, we propose a GRU-based Digital Twin Framework for Data Allocation in IoT-enabled Smart Home Networks. Data and resource allocation of smart home applications are completed at the virtual twin layer using Gated Recurrent Unit (GRU)-based Digital Twin Networks. Low-priority data is stored and processed at the Macro-based Stations (MBSs), and high-priority data is transferred to the upper (Security) layer for authentication and validation. Blockchain-based distributed networks are utilized for Smart Home Data authentication at the security layer with a Proof of Authentication (PoAh) Consensus Algorithm; Data is stored at the cloud layer after validation. The validation results of the proposed framework demonstrate superior performance as the quantitative analysis with accuracy 0.9412, Root Mean Square Error (RMSE) 0.0588 for IoT-enable Smart Home compared to existing works as LSTM-based Digital Twin network and provide a secure environment in IoT-enabled Smart Home.