Effective task scheduling for intelligent manufacturing with fog computing

Effective task scheduling is crucial for the real-time processing of manufacturing tasks, particularly in the context of intelligent manufacturing within a fog computing environment. The paper introduces a novel task scheduling strategy known as the Level Mapping Task Scheduling (LMTS). This strategy is specifically designed to address the challenges posed by complex task requirements and the heterogeneity of fog nodes. The LMTS leverages a level mapping mechanism to ensure an optimal match between tasks and fog nodes, effectively reducing both the scope of task scheduling and the algorithm's complexity. This mechanism is pivotal in achieving a balance between task real-time performance and resource utilization efficiency. In the proposed strategy, virtualization technology is employed to manage the computing resources of the fog servers. This allows for a more flexible and efficient allocation of resources, which is essential for handling the diverse and dynamic nature of manufacturing tasks. Each mapping branch is encapsulated within a container, enabling the solution to be completed in an isolated and secure environment. The LMTS strategy significantly enhances the real-time performance of tasks by minimizing service delays, which is a critical factor in manufacturing processes. Moreover, it is evaluated and compared with the existing scheduling strategies through simulation experiment, the results show that the proposed strategy can reduce service delay of task.