Multi-Task Collaborative Scheduling System for Industrial Control Data Acquisition

Abstract

Network scanners, honeypots and network crawlers are developed to collect the data in Industrial Control System. However, each software or system lacks uniform management rules due to the different developers and development environments. It is urgent to develop a multi-task collaborative scheduling system for the data collection in Industrial Control System in order to make full use of existing hardware and software resources, save human resource costs, and improve the real-time and accuracy of data collection and fusion tasks. The paper proposes a heterogeneous inter-node communication architecture for industrial control data acquisition and researches the evaluation model of resource node and task. An urgent sorting scheduling algorithm and preemptive scheduling algorithm is proposed to solve the multidimensional scheduling requirements and real-time problems of industrial control data collection tasks.