Task Scheduling Algorithm Based on Time and Cost in Smart Grid Cloud Computing

With the rapid development of power informatization, more and more power applications and tasks are deployed in the cloud. In view of the huge amount of users and data in the cloud computing environment of smart grid, how to design an efficient task scheduling algorithm is a key issue in this field. This paper proposes a task scheduling algorithm based on time and cost. The algorithm realizes the reasonable assignment of tasks through dynamic evaluation of virtual machine nodes. The evaluation factors include execution time, transmission delay and system cost. The first two factors are estimated by performing standard tasks, and the system cost is measured by transmission cost, request processing cost and virtual machine maintenance cost. When the evaluation factors are weighted, the subjective weight and the objective weight are combined to obtain the comprehensive weight, and the users in the power grid are classified at the same time. Users with high ranks give priority to processing efficiency and load balance, while users with low ranks give priority to system cost, thereby providing differentiated services to power users. The results show that, compared with traditional scheduling algorithms such as round robin, the proposed algorithm can effectively improve the load balance and reduce the system cost.