A computing task unloading method based on edge computing and cloud computing collaboration

Abstract

The invention provides a computing task unloading method based on edge computing and cloud computing collaboration. The computing task unloading method comprises the steps that variable parameters areset and initialized; Constructing respective time delay models and energy consumption models of the mobile terminal, the edge node and the remote cloud, obtaining a time delay expected value model and a total energy consumption model of the mobile terminal when the current task load is completely executed, and further obtaining a time delay expected value model and a total energy consumption model of all tasks in the total mobile terminal when the tasks are executed; Defining an optimal distribution problem and converting the optimal distribution problem into a convex optimization problem; And introducing a Lagrangian function to solve an optimal solution of task execution amounts of the terminal local machine, the edge node and the far-end cloud under the KKT constraint condition, so that each mobile terminal adjusts and executes according to the task execution amounts of the terminal local machine, the edge node and the far-end cloud, which are obtained by respectively and correspondingly solving the optimal solution. According to the implementation of the invention, the computing power and the power consumption limitation of the mobile terminal, the edge node and the remote cloud are comprehensively considered, and an optimal computing task unloading decision is realized.

Description

technical field [0001] The present invention relates to the technical field of cloud computing, in particular to a method for offloading computing tasks based on edge computing and cloud computing. Background technique [0002] Traditional cloud computing centers can provide powerful computing capabilities, such as big data analysis and processing, data storage, platform services, etc. However, due to geographical location and transmission links, cloud computing centers are often far away from the edge side where data is generated and collected. Data needs to be transmitted through the network to be processed, and then transmitted back to the terminal. The delay in the whole process is relatively long and cannot be achieved. Applied to real-time application scenarios. Edge computing "enhances" the computing power of end users through wireless access networks, enabling the execution of computing-intensive and delay-sensitive tasks such as video monitoring, voice recognition,...

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Problems solved by technology

For example, the patent publication number is CN108600299A, and the name is an invention patent of a distributed multi-user computing task offloading method and system, which can realize stable computing task offloading among multiple users, and each user supports computing offloading to a single or multiple computing nodes, and run in a distributed manner, but in the face of large computing needs, only the edge side server is difficult to meet the demand, and it is still necessary to cooperate with the cloud server to perform task offloading work, the designed system does not consider Performance bottlenecks of edge computing servers

For another example, the patent number is CN107122249A, and the name is an invention patent of a task offloading decision-making method based on the edge cloud pricing mechanism. The task offloading decision based on the edge cloud pricing mechanism maps local computing resources to virtual edge cloud resources. , and combined with the edge cloud price to comprehensively calculate the optimal task offloading ratio, so that the load of the system can be balanced. Although the computing resources of each part of the system are fully utilized and the resource utilizatio

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