Resource scheduling method and system in cloud computing system

Abstract

The invention discloses a resource scheduling method in a cloud computing system. According to the method, the position of an updating frog is computed by the aid of a leapfrog updating formula when each sub-population is locally searched, the fitness of the updating frog is computed to judge whether the fitness of the updating frog is superior to that of the worst frog or not, the position of the updating frog replaces that of the worst frog if the fitness of the updating frog is superior to that of the worst frog, the position of the optimal frog in the whole population replaces that of the worst frog if not, whether the fitness of the updated frog is superior to that of the worst frog or not is judged, the position of the updated frog replaces that of the worst frog if the fitness of the updated frog is superior to that of the worst frog, a new step length is generated by a double learning factor formula if not, the new step length is mutated according to mutation probability to obtain the position of the updated frog and replace the position of the worst frog, and the fitness of the updated frog is computed. The method can achieve good performances in optimal time span and load balance for task scheduling. The invention further discloses a resource scheduling system in the cloud computing system.

Description

technical field [0001] The invention relates to the technical field of cloud computing, in particular to a method and system for resource scheduling in a cloud computing system. Background technique [0002] With the rapid development of the information age, on the basis of the gradual development and maturity of distributed computing, parallel computing and network computing, cloud computing came into being. As an emerging business computing model, cloud computing has become a research hotspot in industry and academia. In a cloud computing system, services can be dynamically deployed, configured, reconfigured, and canceled on demand. However, due to the growing number of users and the heterogeneity and complexity of nodes in the cloud computing network, how to schedule tasks in a timely and efficient manner, use resources reasonably, and improve resource utilization and task execution efficiency has become a major issue in cloud computing research. one of the core issues....

AI Technical Summary

Problems solved by technology

Although existing algorithms can improve task scheduling efficiency from a certain angle, they also have limitations. For example, it is difficult for general task scheduling algorithms to perform well in both optimal time span and load balancing.

Images