Virtualization resource scheduling and optimization method based on swarm intelligent systems

Abstract

Efficient scheduling of virtualized resources can not only meet the service needs of users, but also achieve the optimal allocation of resources and the stable operation of the system. However, due to the dynamic and diversity of virtualized resources, the traditional scheduling methods have been difficult to meet the actual needs. Therefore, a virtual resource scheduling and optimization method based on Swarm Intelligence System (SIS) is proposed in this paper. The core idea of this method is to transform the Virtualized Resource Scheduling (VRS) problem into a multi-objective optimization problem, and use the particle swarm optimization algorithm of SIS to search for the optimal solution. By updating the speed and position of the particles, the scheduling scheme is optimized iteratively to maximize the utilization of resources and optimize the performance of the system. The experimental results show that the SIS-based virtual resource scheduling method can significantly improve the resource utilization and system performance while meeting the needs of users. Compared with other scheduling methods, this method has better adaptability and robustness, and provides a new solution for virtualization resource scheduling in cloud computing environment.