A method for simulating a Web service in an evolutionary scenario

Abstract

The invention relates to a method for simulating a Web service in an evolutionary scenario, the method comprising the following steps: 1) adopting a lightweight load model to carry out system modelingon a web system and a load thereof; 2) obtaining the key attribute of the system model through the integrated automatic mine method in the user access log; 3) carrying out model verification on the model and predicting under the evolution scene. Compared with the prior art, the invention has the advantages of lightweight load model, shortening the simulation running time, being applicable to a plurality of evolution scenes and the like.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to a method for simulating Web services in an evolving scene. Background technique [0002] Existing web systems are becoming more complex and constantly evolving. In order to maintain the system and cope with the continuous evolution of the system, administrators usually need to face such problems: If the load increases or the system is updated, what impact will it have on system performance and user-perceived service response time? Before any changes, it is very important and necessary to perform what-if analysis on the system. Especially in the era of cloud computing, because cloud services can provide users with flexible resource supply and pricing, web systems are often hosted on the cloud. Cloud services bring many benefits to system maintenance and cost control. Often, the demand for cloud resources may change as application load fluctuates, so anticipating c...

AI Technical Summary

Problems solved by technology

These further add to the complexity of load modeling, so a simpler and scalable approach is required for real-life applications

[0004] There is another problem in the existing what-if analysis methods: most studies focus on one or two main computing resources (such as CPU, memory, disk read and write), and do not involve bandwidth resources

Currently, the biggest challenges in predicting bandwidth consumption are caching factors, diverse and complex service responses, evolving web services, and complex network transports (such as congestion control and retransmissions)

There is currently no mature method for the prediction of bandwidth consumption and the prediction of response time involving bandwidth

None of the existing model-based approaches can address these issues, therefore, for web systems, we believe there is a need for a dedicated network modeling and simulation approach for what-if analysis in terms of bandwidth

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