Edge computing service resource configuration method and device and electronic equipment

Abstract

The invention discloses an edge computing service resource configuration method and device and electronic equipment. The edge computing service resource configuration method comprises the following steps: constructing a user demand model according to a user service demand in a network environment; according to the user demand model, respectively determining a cloud node resource limiting condition, an edge node resource limiting condition, an overall resource limiting condition, a service delay limiting condition and an edge computing service cost model; establishing a configuration optimization model according to the limiting conditions and the edge computing service cost model; and solving the configuration optimization model and carrying out resource configuration according to a solvingresult. The edge computing service resource configuration device comprises a user demand module, a constraint condition module, a service cost module and a configuration optimization module. The electronic equipment comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor implements the edge computing service resourceconfiguration method when executing the program.

Description

technical field [0001] The present invention relates to the field of network communication services, in particular to an edge computing service resource configuration method, device and electronic equipment. Background technique [0002] With the widespread application of cloud computing, the problem of poor immediate response to transmit large amounts of data to cloud service centers has gradually emerged. In the service mode of the traditional cloud computing system, due to the limited network bandwidth, it takes a certain amount of time to transmit massive data, and it also takes a certain amount of time for the cloud service center to process the data, which will increase the request response time and cause poor user experience. . Edge computing, as a new computing model that pushes cloud services to the edge of the network, can make good use of the powerful computing capabilities of cloud service centers while freeing services from network congestion and long delays. ...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing edge computing model, the edge infrastructure provider (EIP) is more inclined to establish a series of private edge computing environments to meet the specific needs of specific users from the perspective of their respective services. Each edge infrastructure provides The provider (EIP) only manages and uses the storage and computing resources deployed by itself, and the independent edge computing environment is usually resource-constrained

On the one hand, when the edge infrastructure provider (EIP) wants to provide services for more users, it is necessary to build and maintain more edge nodes to cover more users, which greatly increases the service cost; on the other hand, Different edge infrastructure providers (EIP) often establish edge nodes in the same node area, and there is no cooperation between these edge nodes, which leads to a serious waste of resources for edge computing services; at the same time, a single edge infrastructure provider (EIP) has limited information about the entire edge computing environment, which makes it difficult to effectively optimize globally when providing various services to different users

The problems of high cost, low resource utilization, and difficult global optimization of Edge Infrastructure Provider (EIP) lead to low Quality of Service (QoS) for Edge Service Provider (ESP) and low Quality of Experience (QoE) for end users

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