Digital Twin-enabled Opportunistic Routing with Redundant Path Injection

In future smart cities, intelligent city services based on detection, prediction, and automation via city-scale digital twins are expected to support the daily lives of citizens. However, high traffic burdens on mobile and fixed network infrastructures exist. This is because the digital twin requires collecting large amounts of local sensing data from local nodes such as sensors and personal devices. Wireless multi-hop networks can offload mobile traffic via wireless direct communications. However, fundamental issues in path construction and maintenance efficiency exist, owing to fast topological changes caused by node mobility and radio interference. Previous studies have comprehensively addressed such issues using initial path injection via digital twin, the characteristics of opportunistic routing based on the adaptive path selection, and convergence via continual packet transmissions. However, packet transmission failures occur when the injected initial and ideal forwarding paths differ because there is no redundancy in the initial forwarding path lacks redundancy. In this study, we propose a digital twin-enabled opportunistic routing that injects initial cost information into nodes along and around a path to provide path redundancy. Finally, we analyzed the impact of initial path injection by varying the redundancy level in the proposed method, compared to the non-redundant initial path used in the previous method.