Semanteme service combination method based on dynamic planning

Abstract

The invention provides a semanteme service combination method based on dynamic planning. The semanteme service combination method based on the dynamic planning comprises firstly, decomposing a manufacturing service process model through a workflow engine, extracting requirements of each active node, and then obtaining all services which satisfy the active node through a service find matching process, and at last, selecting an appropriate candidate service from the services to generate a service combined scheme according to a certain strategy, achieving mapping a specific semanteme onto a task, and using a manufacturing service process which is described in a workflow model to translate a generating process of the semanteme service combined scheme into a dynamic evolution multistage decision process by combining characteristics of a networked manufacturing mode, using a data semanteme relationship between services as restraint, using comprehensive quality of the combined scheme as an optimization target, and using a dynamic planning method to generate a combined scheme which is globally optimum. The semanteme service combination method based on the dynamic planning has the advantages of enabling confirmation of a globally optimum solution to be easy, saving computing amount, being beneficial for providing abundant combined scheme results for a user, and improving performability of the combined scheme and automation degree of a combining process.

Description

technical field [0001] The invention relates to the technical field of combination of networked manufacturing services, in particular to a method for combining semantic services based on dynamic programming. Background technique [0002] Service composition is an effective way to construct business processes in a networked manufacturing environment and realize on-demand allocation of manufacturing resources. Existing service composition technologies can be classified into two categories. One is a workflow-based method, which uses a model similar to the classic workflow modeling method to describe composite services, which is simple to implement, but requires prior knowledge of the specific structure of the process and the functions and purposes of each activity in the process. The mapping from the workflow business model to the service environment can only be converted statically, and the degree of automation and dynamic adjustment of process operation is not high. The oth...

AI Technical Summary

Problems solved by technology

One is a workflow-based method, which uses a model similar to the classic workflow modeling method to describe composite services, which is simple to implement, but requires prior knowledge of the specific structure of the process and the functions and purposes of each activity in the process. The mapping from the workflow business model to the service environment can only be converted statically, and the degree of automation and dynamic adjustment of process operation is not high

The other is based on artificial intelligence methods, using ontology to carry out semantic annotation and business process modeling on the input and output parameters, premises and results of Web services, and to realize automatic matching of Web services through formal reasoning, and to obtain the combination sequence of services , but the complexity of this method is relatively high, and the combination of purely relying on computers to automatically perform Web services is not yet mature.

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