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A prediction method of web service QoS based on multivariate time series

A technology of multivariate time series and forecasting method, applied in the field of information, which can solve problems such as affecting forecasting accuracy and failing to reflect QoS attribute values.

Active Publication Date: 2019-07-12
HOHAI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, with the improvement of technology, the overall development trend of Web service QoS is dynamic and changeable with the change of service provider's strategy. Directly using historical data to make multi-step direct prediction cannot reflect the current QoS attribute value and affects the prediction accuracy.

Method used

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  • A prediction method of web service QoS based on multivariate time series
  • A prediction method of web service QoS based on multivariate time series
  • A prediction method of web service QoS based on multivariate time series

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Embodiment Construction

[0060] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0061] Such as figure 1 As shown, it is an overall step diagram of the Web Service QoS prediction method based on multivariate time series of the present invention, which mainly includes 5 steps:

[0062] Step 1: Collect the QoS attribute data of the determined single Web service;

[0063] Step 2: QoS attribute data preprocessing;

[0064] Step 3: Establish a RBF (radial basis) neural network prediction model based on multivariate time series;

[0065] Step 4: Set the error threshold δ, train t...

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Abstract

The invention discloses a method for predicting Web Service QoS based on multiple time series. This method mainly collects the historical data of QoS attributes and the QoS advertisement data information recently released by service providers, and combines the improved RBF neural network model to realize the direct multi-step prediction of QoS attributes after data preprocessing. Consider multiple attributes of QoS, and make predictions based on multivariate time series; there are intricate nonlinear relationships among QoS attributes. In order to describe this relationship, the collected historical QoS attribute data is reconstructed in phase space to approximately restore multiple QoS Non-linear relationship system of attributes; QoS data information released recently by service providers reflects future changes and development trends of QoS, and this part of information is combined with QoS attribute data after phase space reconstruction to form a comprehensive QoS data set; Do dynamic multi-step prediction of QoS attributes on the trained RBF neural network model.

Description

technical field [0001] The invention relates to a method for predicting Web Service QoS, in particular to a method for predicting Web Service QoS based on multivariate time series, and belongs to the field of information technology. Background technique [0002] With the rapid development and application of Web service technology, many Web services with similar functions appear on the Internet. In the process of selecting Web services that meet user needs, non-functional requirements are often ignored by people. In recent years, quality of service (QoS) as a non-functional factor has gradually been paid attention to, and more and more researchers have begun to devote themselves to the QoS prediction technology of Web services. [0003] The QoS attributes of Web services include performance-related response time (Response time), throughput (Throughput), reliability (Reliability), availability (Availability), scalability (Expandability), and non-performance-related price (Pric...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24H04L29/08
CPCH04L41/145H04L41/147H04L67/02H04L43/55
Inventor 张鹏程王丽艳江艳张雷刘琪何志鹏
Owner HOHAI UNIV
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