Green Industrial Internet of Things Architecture: An Energy-Efficient Perspective

TLDR

The Internet of Things enables automatic collaboration between objects, but its expanding device count drives substantial energy consumption, prompting growing academic and industrial focus on energy efficiency. This study proposes an energy‑efficient Industrial IoT architecture comprising a sense‑entities domain, RESTful service‑hosted networks, a cloud server, and user applications, concentrating on the energy‑intensive sense‑entities domain. The architecture is organized into sense, gateway, and control layers, incorporating a sleep‑scheduling and wake‑up protocol that predicts sleep intervals and shifts device states to maximize resource use while minimizing energy use. Simulations show that the hierarchical framework balances traffic load, extends overall system lifetime, and yields significant improvements in resource utilization and energy consumption.

Abstract

The Internet of Things (IoT) can support collaboration and communication between objects automatically. However, with the increasing number of involved devices, IoT systems may consume substantial amounts of energy. Thus, the relevant energy efficiency issues have recently been attracting much attention from both academia and industry. In this article we adopt an energy-efficient architecture for Industrial IoT (IIoT), which consists of a sense entities domain, RESTful service hosted networks, a cloud server, and user applications. Under this architecture, we focus on the sense entities domain where huge amounts of energy are consumed by a tremendous number of nodes. The proposed framework includes three layers: the sense layer, the gateway layer, and the control layer. This hierarchical framework balances the traffic load and enables a longer lifetime of the whole system. Based on this deployment, a sleep scheduling and wake-up protocol is designed, supporting the prediction of sleep intervals. The shifts of states support the use of the entire system resources in an energy-efficient way. Simulation results demonstrate the significant advantages of our proposed architecture in resource utilization and energy consumption.