Volume 12 Number 1 (Jan. 2017)
Home > Archive > 2017 > Volume 12 Number 1 (Jan. 2017) >
JCP 2017 Vol.12(1): 48-56 ISSN: 1796-203X
doi: 10.17706/jcp.12.1.48-56

QoS-Based Web Services Selection Using a Hidden Markov Model

Daniel G. Canton-Puerto, Francisco Moo-Mena, Víctor Uc-Cetina
Facultad de Matemáticas, Universidad Autónoma de Yucatán, Anillo Periférico Norte, Tablaje Cat. 13615, Colonia Chuburná Hidalgo Inn, Mérida Yucatán, México.
Abstract—Web services are a technology that has been growing rapidly since its inception earlier this century. They are so popular nowadays that they are being used for numerous purposes, spanning business, healthcare, education and government applications. They are used for accessing diverse types of data in domains such as the financial, climate forecasting and sports, among others. As a result of this increased popularity, it is very common to find a large number of applications providing exactly the same service. Having a large number of applications to choose from, one that integrates a selection mechanism using quality criteria for selecting the best choice, has an advantage over other applications that do not provide this feature. However, the selection of the best Web service, among various services with the same functionality, is not an easy task. Therefore, the design of a worthwhile technique to determine the best Web service by assessing its quality of service is important. Hidden Markov models are probabilistic methods that allow us to build behavior models of the Web services. Such models can be used to predict their behavior in the near future. In this paper, we propose a method for selecting Web services based on the response time QoS parameter and hidden Markov models.

Index Terms—Hidden Markov models, QoS, selection, web services.

[PDF]

Cite: Daniel G. Canton-Puerto, Francisco Moo-Mena, Víctor Uc-Cetina, "QoS-Based Web Services Selection Using a Hidden Markov Model," Journal of Computers vol. 12, no. 1, pp. 48-56, 2017.

General Information

ISSN: 1796-203X
Frequency: Monthly (2006-2014); Bimonthly (Since 2015)
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
  • Sep 26, 2017 News!

    Papers published in JCP Volume 12 have all been indexed by DBLP   [Click]

  • Sep 02, 2016 News!

    Vol 11, No 3 has been indexed by EI (Inspec)   [Click]

  • Sep 22, 2017 News!

    Vol 13, No 6 has been published with online version 11 papers are published in this issue after peer review   [Click]

  • Aug 14, 2017 News!

    Vol 13, No 5 has been published with online version   [Click]

  • Jun 21, 2017 News!

    Vol 13, No 4 has been published with online version   [Click]

  • Read more>>