Virtual service migration method and system based on incremental minimum cost and maximum flow

Abstract

The invention relates to the technical field of information, and discloses a virtual service migration method and system based on incremental minimum cost and maximum flow, and the method comprises the steps: constructing a network topological graph according to the geographic position and connection relation of an edge server; calculating the shortest path distance between each pair of edge servers, and generating a shortest path distance matrix; in combination with the access information of each service, establishing a minimum-cost maximum-flow model, wherein the model comprises a service node and an edge server node; solving the model to obtain the maximum flow with the minimum cost, and migrating and placing the service nodes; updating the access information of each service, and updating the position of the service node by adopting an incremental minimum cost maximum flow algorithm; and performing real-time monitoring and statistics, and when the change rate of the access information exceeds a set threshold, adjusting the corresponding service node and edge server node. According to the invention, the optimal service placement and migration scheme can be solved in a short time,and the method is simple, reliable and easy to implement.

Description

technical field [0001] The present invention relates to the field of information technology, and more specifically, to a virtual service migration method and system based on incremental minimum cost maximum flow. Background technique [0002] In recent years, Mobile Edge Computing (MEC) has become a trend. It is a cloud computing platform that deploys servers on nodes such as routers, gateways, and base stations closer to users, and uses cloud computing technology as the core. For some delay-sensitive applications, such as facial recognition, real-time games, live video and other online service applications, traditional cloud computing centers cannot well meet the delay requirements of these applications. But with MEC, the cloud center pushes some computing resources to the edge of the network, making some services closer to users. This can not only relieve the load pressure of the cloud computing center, but also reduce service delay and network traffic to a certain extent...

AI Technical Summary

Problems solved by technology

Some scholars have defined a cost model for the migration problem, and proposed a migration framework with perception capabilities, more flexibility, and strong adaptability, but it is aimed at a single service

[0004] Existing work has achieved good results in the migration strategy, but with the increasing demand of people, the network scale has also increased, and the access mode has become more complex. The previous strategy is difficult to implement in a large-scale network topology. make the best decision

At the same time, the previous methods are either for the migration of a single service, or lack of certain dynamics, or the solution time is too long

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