Software micro-service combination optimization method for edge cloud system

Abstract

The invention discloses a software micro-service combination optimization method for an edge cloud system. The method resets a step length factor and an attraction degree formula, gives full play to the detection capability of the step length factor at the early stage of an algorithm, and balances the local search and global search; micro-services are classified by utilizing the characteristics ofthe micro-services, and the services with the same input and output are classified into the same class, so that the number of combinations is reduced, and all combination schemes can be enumerated completely; in a combination algorithm, residual tangent initialization and residual tangent disturbance are adopted to replace random initialization and random disturbance, initialization and updatingof a micro-service combination scheme are improved, and the diversity of a final combination scheme is greatly improved; meanwhile, service attribute values stored in a service registration center arehashed and stored as a hash root through the concept of a hash tree, and therefore it is guaranteed that all the service quality attribute values stored in the service registration center are safe and reliable.

Description

technical field [0001] The invention relates to the technical fields of information integration and software engineering application, in particular to an optimization method for microservice combination oriented to an edge cloud system. Background technique [0002] Since the emergence of "microservice architecture", the design of software application systems has shifted towards the way of several sets of independently deployable services. Compared with the traditional monolithic development style, microservices focus more on developing an independent application system by developing a set of small services, each of which runs in its own process. These services are built around business functions and can be deployed independently through a fully automated deployment mechanism. [0003] A monolithic application is built as a single unit. As more and more application systems are deployed to the cloud, software changes are greatly restricted. Once a part of the application sy...

AI Technical Summary

Problems solved by technology

[0010] 1) As the number of microservices increases, the amount of calculation increases exponentially, so the efficiency of solving optimization problems is low;

[0011] 2) In the process of searching for the optimal solution, the random search strategy cannot guarantee the diversity of the final solution, and a new search strategy is needed;

[0014] 5) The data stored in the service registration center may be subject to malicious attacks at any time. The most important thing is to tamper with the service attribute values. It is also a very important issue to ensure that the service quality attribute values ​​stored in the service registration center are safe and reliable.

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