IEEE Communications Magazine, vol.61, no.3, pp.36-42, 2023 (SCI-Expanded)
An efficient serving of predictive management and what-if-analysis of smart cities is the only way to achieve a net-zero waste target. With the aid of the enhanced learning capabilities of digital twin, net-zero aims of smart cities can be obtained with highly accurate results in the prediction of waste-to-energy and candidate truck paths. However, there is no unified communication model yet for a digital twin to maintain complete data and control flow in a fully synchronized way. Without having a clear communication model for the digital twin, the interaction between the physical and digital replica cannot be sustained. To handle this, we propose a digital twin networking framework called T6CONF, based on an IPv6 infrastructure, to solve the end-to-end two-way communication and synchronization problem of the resource-constrained Internet of Things networks. Besides, T6CONF serves two specific net-zero waste services, waste-to-energy and planned-truck-routing prediction services, for the net-zero goal. We evaluate the proposed digital twin communication model with changing fidelity levels over the twinning rate and round-trip time. Additionally, we prove that the proposed T6CONF model increases the accuracy of service layer operations.