Minimizing Age-of-Information for Multisystem Energy IoT System with Multiple Subsystems

Age of Information (AoI), an important measure of information timeliness, plays a critical role in energy Internet of Things (IoT) systems. Maintaining a low AoI means that energy systems have access to up-to-date information to make more accurate and reliable decisions and ensure safe, efficient and reliable system operation.Focusing on a wireless networked energy IoT system with multiple subsystems, this paper analyzes the lower limit value of the average AoI of the system under unreliable wireless transmission, and verifies the accuracy of the theoretical analysis results through simulation experiments. Meanwhile, the experiments also reveal the effects of the number of channels, channel state (transmission success rate) and data sampling rate on the average AoI, which provides an important theoretical basis for optimizing the timeliness of energy IoT information.