A task container scheduling algorithm for spaceborne virtualization platform

Abstract

With the help of lightweight virtualization technology such as containers, the spaceborne virtualization platform encapsulates computing tasks into containers to form task containers, so as to achieve efficient utilization of resources. However, the platform's task container scheduling problem is a difficult problem that needs to be solved urgently. In this paper, we aim at this problem by establishing a multi-pass scheduling model for separable container tasks based on non-blocking communication mode. On the basis of this model, we propose a new scheduling algorithm, aiming at determining the optimal processor scheduling sequence and scheduling times. The algorithm combines the concept of divisible task container and multi-pass scheduling. By decomposing the task into executable subtasks, and performing task allocation and processor scheduling in multiple scheduling stages, it can optimize the scheduling order to improve the overall processing efficiency. This algorithm is an improved genetic algorithm that adds the optimization strategy of subpopulation isolation to the traditional genetic algorithm. Its core idea is to improve the performance and effect of the genetic algorithm by introducing the population division strategy into the algorithm process. We verify the effectiveness and convergence of the algorithm through experiments, and the experimental results show that the algorithm makes the task have less completion time.

Keywords

• spaceborne computing
• virtualization
• container
• separable task scheduling