Application of improved genetic algorithm in cloud-assisted teaching platform

Application of improved genetic algorithm in cloud-assisted teaching platform

Wang Xiaohui Li San Pu

With the rapid development of cloud computing technology, cloud computing aided teaching platform came into being, it has the significant advantages of networked teaching data resource storage and computing, thin client and so on, which determines the diversity and data density of the data and users of cloud-assisted teaching platform. The design of cloud-assisted teaching platform is focused on efficient resource management and scheduling. This paper designs the architecture of cloud computing assistant teaching platform, and improves the original adaptive genetic algorithm of cloud platform job scheduling, based on traditional genetic algorithm, integrates data fairness and local selection of genetic genes, and is more efficient in responding to users ' needs than traditional algorithms. The simulation results show that the improved algorithm is more fair, more efficient and more suitable for cloud computer environment.

Application of improved genetic algorithm in cloud-assisted teaching platform