Prediction method for combinations of cloud manufacturing service quality of service (QoS)
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A technology that combines forecasting and cloud services. It is used in forecasting, manufacturing computing systems, instruments, etc., and can solve problems such as lack of time model summary.
Inactive Publication Date: 2017-04-26
BEIJING INSTITUTE OF TECHNOLOGYGY
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In the article "A Service Quality Prediction Method for Web Service" published by Shao Lingshuang and others in 2009, the user similarity and service similarity are
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Embodiment 1
[0076] This embodiment illustrates the process of a specific embodiment of the method of the present invention. figure 1 It is a flow chart of "a combined prediction method for manufacturing cloud service QoS" of the present invention.
[0077] Depend on figure 1 It can be seen that the process of a combined prediction method for manufacturing cloud service QoS in the present invention is as follows:
[0078] Step A input task request;
[0079] Step B task request modeling;
[0080] Acquisition of historical data for similar tasks in step C;
[0081] Step D input similar historical data of the task;
[0082] D.1 Input the historical data of the execution time, construct the BP neural network, and predict the execution time of the task on the candidate service;
[0083] D.2 Enter the historical data of availability, judge whether the task is a computing task, and perform the following operations:
[0084] D.2.1 If it is a computing task, the corresponding figure 1 Y in ,...
Embodiment 2
[0088] Taking the production of a certain part by an automobile manufacturing company as an example, the execution time of each subtask of the task request on the corresponding candidate service is predicted.
[0089] User task request modeling, specifically:
[0090] The enterprise submits the production task T to the manufacturing cloud service platform, and the cloud manufacturing management system decomposes the business process of the task T, and obtains the subtask set T={T 1 , T 2 , T 3 , T 4 , T 5}, where the ontology description language is used for subtask modeling, such as figure 2 shown.
[0091] From figure 2It can be seen that the tasks requested by users are connected with relations, attributes and concepts, and the representation of tasks can be described by relations, attributes and concepts. The relationship can be divided into inheritance relationship, composition relationship and function relationship; the attribute can be divided into shape attrib...
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Abstract
The invention relates to a prediction method for combinations of cloud manufacturing service quality of service (QoS), which belongs to the networked manufacturing field and comprises the steps of cloud manufacturing task modeling, cloud manufacturing service execution time predicting, cloud manufacturing service reliability predicting and service availability predicting. In the invention, the cloud manufacturing task is divided into a computer type task and a manufacturing and processing task; and based on this, predictions are made on the cloud manufacturing service QoS; a BP neural network is used to predict the cloud manufacturing service execution time; and a discrete Markov model is used to predict the service reliability; in combination with the continuous Markov model and a queuing model, predictions are made on the service availability. As different QoS indicators have different influential factors, different prediction methods are employed for the different indicators so that the prediction model is better than one individual model in terms of both efficiency and quality, the prediction accuracy is increased and that important data support can be provided for the service combination, resource optimized allocation and management in a cloud manufacturing environment.
Description
technical field [0001] The invention relates to a combined prediction method of manufacturing cloud service QoS, in particular to a combined prediction method of neural network and Markov model for manufacturing cloud service QoS, belonging to the field of networked manufacturing. Background technique [0002] The manufacturing industry occupies an important position in the national economy, and the traditional manufacturing industry is facing great challenges and new opportunities in the information age. The networked manufacturing model has become a new choice for the manufacturing industry, but there are many problems in the networked manufacturing models such as manufacturing grid and agile manufacturing in terms of service model, manufacturing resource sharing and allocation, physical terminal equipment access, and information security. In this context, cloud manufacturing came into being. Cloud manufacturing connects manufacturing resources to the network through embe...
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