Cloud-side cooperative task scheduling method for intelligent building

Abstract

The invention discloses a cloud-side cooperative task scheduling method for an intelligent building. The intelligent building cloud edge collaborative architecture comprises a cloud computing layer, an edge computing layer and an intelligent equipment layer. The defects of cloud computing and edge computing can be overcome, and the advantages of cloud computing and edge computing are fully combined. According to the scheduling method, the task manager is firstly used for collecting the size of task data generated by the intelligent equipment, the type of tasks and the calculation intensive degree, then all equipment resources and network information in the system are collected, then a system model and a task model are established, and existing technical problems are converted into mathematical optimization problems. And finally, according to the density degree of task calculation, after tasks are segmented, a task scheduler and a built-in optimization algorithm search for an optimal scheduling scheme, and then the task scheduling scheme is distributed. The set of operation mechanism can quickly respond to the request of the intelligent building, greatly reduces the task completion time, achieves the reasonable configuration of computing resources, and enables the privacy of a user not to be leaked easily.

Description

technical field [0001] The invention relates to the technical field of intelligent computing. In particular, a task scheduling method for intelligent building cloud computing and edge computing collaboration. Background technique [0002] Due to the rapid development of communication technology and Internet of Things technology, more and more smart devices are favored by people. With the development of edge computing and the improvement of the living standards of home users, smart buildings have gradually become an important application of edge computing. A large number of network devices deployed in buildings will lead to explosive growth of network data. Moving data processing from the cloud to the edge is becoming an important trend, which can effectively reduce system latency. Edge computing is closer to the source of objects or data, and can provide real-time, dynamic and intelligent service computing for home users, resulting in faster network service responses, so ...

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Problems solved by technology

[0003] Defects in existing cloud computing and edge computing: In computing platforms based on cloud services, although there is a large-scale parallel computing architecture and strong computing capabilities, there are still problems with high delay, low resource utilization, and high risk of privacy leakage. Disadvantages: Edge computing has a fast response speed, but weak computing power is its main shortcoming, and it takes a long time to process computing-intensive tasks

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