Resource scheduling system and method based on edge computing in heterogeneous environment

Abstract

The embodiment of the invention discloses a resource scheduling system and method based on edge computing in a heterogeneous environment in the technical field of edge computing. The resource scheduling system based on edge computing in a heterogeneous environment includes an EdgeCloud is used for task analysis, scheduling, resource management and arrangement, an EdgeAgent which is used for creating and destroying resources required by calculation according to an instruction of the EdgeCloud and monitoring a resource load of the EdgeAgent, and a TaskWorker which is used for executing a calculation task allocated by the EdgeCloud. According to the method, the scattered resources in each region are grouped and further added into the resource pool, and the situation of how to dynamically calculate the score of the equipment is designed to determine the scheduling priority of the equipment; through the stored namespace, the method and system can be applied to the data sharing problem during large-scale calculation, and then the data can be shared with the equipment resource group.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of edge computing, and in particular to a resource scheduling system and method based on edge computing in a heterogeneous environment. Background technique [0002] In the existing distributed computing, a centralized cloud computing solution is usually used. Typical resource orchestration includes virtual machine orchestration based on openstack (or similar cloudstack\vmware, etc.), or container orchestration based on kubernetes. Common solutions in the industry are mainly the above-mentioned resource orchestration solutions based on the above, or variant solutions, which are not much different in essence. [0003] For end users, they must hope that the computing power resources they use are as cheap as possible. However, the hardware architectures used by existing manufacturers are not fundamentally different, and the functions provided are gradually converging. When a user uses a ...

AI Technical Summary

Problems solved by technology

When a user uses a certain vendor's computing resources, it is cheap at a certain time, but as time goes by, it is often not the cheapest resource, but when switching to other provider's resources at this time, there are often Migration Difficulties, and Difficulty Negotiating Prices

[0004]At this stage, no matter whether it is kubernetes-based container orchestration or openstack-based virtual machine orchestration, cross-regional orchestration cannot be performed. When used in batches, there will be resource limitations

In actual use, if you encounter factors such as fiber cuts, power outages, or core switch failures, it often means that the resources in the cloud computing area cannot be used.

[0005] In addition, at the current stage, the resource utilization rate of some small and medium-sized idcs is not high, limited by commercial influence, they cannot provide good external services

At the same time, although some small and medium-sized IDCs have cost advantages, they often have limited equipment scale and relatively poor stability, which will limit their large-scale application

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