AS-MPCA: An adaptive scheduling algorithm for industrial Internet of Things based on multi-population co-evolution

Abstract

The Industrial Internet of Things (IIoT) enables real-time data collection, analysis, and decision-making by tightly connecting physical devices, sensors, control systems, and information systems. Meanwhile, in the communication environment of industrial parks, a multi-dimensional heterogeneous information sensing network is constructed by sensor networks, shop floor Ethernet, field buses, etc. In this kind of network, multi-source heterogeneous data types are complex and diverse, the data scale is huge, and all kinds of data flows have different requirements for transmission volume and real-time performance. Especially in a communication environment with limited network resources, the transmission delay of real-time service data makes it difficult to meet the actual production requirements. These lead to problems such as low real-time and insufficient reliability of sensory data transmission. To address these problems, we propose an Adaptive Scheduling Algorithm for the Industrial Internet of Things Based on Multi-swarm Co-evolution(AS-MPCA). The algorithm combines a two-stage multiple swarm genetic algorithm with an adaptive routing mechanism. Firstly, the two-stage multiple swarm genetic algorithm expands the search space and enhances the diversity of the scheduling scheme through the combination of global search and multiple swarm strategies, which provides diversified path selection strategies for the adaptive routing mechanism. Then, the adaptive routing mechanism dynamically adjusts the optimal path according to the scheduling results of the above genetic algorithm. Simulation and experimental results demonstrate that the proposed method significantly enhances system schedulability. Compared with traditional algorithms, the proposed algorithm improves the task acceptance rate by an average of 10% across various conditions, effectively reduces the transmission delay of time-sensitive data, and ensures the quality of service for industrial IoT communication systems.