Augmented Twin Empowered Intelligence for Lightweight Device in Internet of Things

Abstract

Lightweight devices are widely used in the Internet of Things (IoT), Due to the limited computation and communication resources, lightweight devices can only conduct simple actions and will thereby hinder the intelligent cooperation of the devices in IoT. Such situation will last long since currently it is hard to replace all lightweight devices with intelligent ones. To address this issue and improve the integrated intelligence of IoT, we propose an augmented digital twin empowered intelligence for lightweight devices in IoT. The augmented digital twin, or shorten as augmented twin (AT), is a virtual entity built for a given lightweight device, which can be constructed on some resource-rich devices such as a gateway or an edge server. Based on the resources in its carrier, AT can not only clone all functions of the lightweight device, but also extend some intelligent analysis and cooperation abilities for this device. We first propose the architecture of AT for lightweight device in IoT. Then, to achieve the most effective AT carrier selection of the lightweight device, we formulate an optimization problem and present a self-initialized genetic algorithm to solve this problem. Simulations are conducted to evaluate the cost in constructing the ATs of the lightweight devices, as well as the performance promotion when AT is used in an IoT network. Compared to the benchmark schemes, AT can decrease the scheduling latency and energy consumption by 60.38% and 32.16% respectively than normal digital twin with reasonable constructing cost.