Open Access
ARTICLE
Prediction of Web Services Reliability Based on Decision Tree Classification Method
Zhichun Jia1, 2, Qiuyang Han1, Yanyan Li1, Yuqiang Yang1, Xing Xing1, 2, *
1 College of Information Science and Technology, Bohai University, Jinzhou, 121013, China.
2 School of Engineering, The University of New Mexico, Albuquerque, NM 87131, USA.
* Corresponding Author: Xing Xing. Email: .
Computers, Materials & Continua 2020, 63(3), 1221-1235. https://doi.org/10.32604/cmc.2020.09722
Received 16 January 2020; Accepted 24 February 2020; Issue published 30 April 2020
Abstract
With the development of the service-oriented computing (SOC), web service
has an important and popular solution for the design of the application system to various
enterprises. Nowadays, the numerous web services are provided by the service providers
on the network, it becomes difficult for users to select the best reliable one from a large
number of services with the same function. So it is necessary to design feasible selection
strategies to provide users with the reliable services. Most existing methods attempt to
select services according to accurate predictions for the quality of service (QoS) values.
However, because the network and user needs are dynamic, it is almost impossible to
accurately predict the QoS values. Furthermore, accurate prediction is generally timeconsuming. This paper proposes a service decision tree based post-pruning prediction
approach. This paper first defines the five reliability levels for measuring the reliability of
services. By analyzing the quality data of service from the network, the proposed method
can generate the training set and convert them into the service decision tree model. Using
the generated model and the given predicted services, the proposed method classifies the
service to the corresponding reliability level after discretizing the continuous attribute of
service. Moreover, this paper applies the post-pruning strategy to optimize the generated
model for avoiding the over-fitting. Experimental results show that the proposed method
is effective in predicting the service reliability.
Keywords
Cite This Article
APA Style
Jia, Z., Han, Q., Li, Y., Yang, Y., Xing, X. (2020). Prediction of web services reliability based on decision tree classification method. Computers, Materials & Continua, 63(3), 1221-1235. https://doi.org/10.32604/cmc.2020.09722
Vancouver Style
Jia Z, Han Q, Li Y, Yang Y, Xing X. Prediction of web services reliability based on decision tree classification method. Comput Mater Contin. 2020;63(3):1221-1235 https://doi.org/10.32604/cmc.2020.09722
IEEE Style
Z. Jia, Q. Han, Y. Li, Y. Yang, and X. Xing "Prediction of Web Services Reliability Based on Decision Tree Classification Method," Comput. Mater. Contin., vol. 63, no. 3, pp. 1221-1235. 2020. https://doi.org/10.32604/cmc.2020.09722
Citations