More Web Proxy on the site http://driver.im/

article

Towards an accurate evaluation of quality of cloud service in service-oriented cloud computing

Authors:

Shangguang Wang,

Fangchun YangAuthors Info & Claims

Journal of Intelligent Manufacturing, Volume 25, Issue 2

Pages 283 - 291

https://doi.org/10.1007/s10845-012-0661-6

Published: 01 April 2014 Publication History

Abstract

Cloud computing promises to provide high quality, on-demand services with service-oriented architecture. However, cloud service typically come with various levels of services and performance characteristics, which makes Quality of Cloud Service (QoCS) high variance. Hence, it is difficult for the users to evaluate these cloud services and select them to fit their QoCS requirements. In this paper, we propose an accurate evaluation approach of QoCS in service-oriented cloud computing. We first employ fuzzy synthetic decision to evaluate cloud service providers according to cloud users' preferences and then adopt cloud model to computing the uncertainty of cloud services based on monitored QoCS data. Finally, we obtain the evaluation results of QoCS using fuzzy logic control. The simulation results demonstrate that our proposed approach can perform an accurate evaluation of QoCS in service-oriented cloud computing.

References

[1]

Adali, M. R., Taskin, M. F., & Taskin, H. (2009). Selecting the optimal shift numbers using fuzzy control model: a paint factory's facility application. Journal of Intelligent Manufacturing, 2, 267-272.

[2]

Ardagna, D., & Pernici, B. (2007). Adaptive service composition in flexible processes. IEEE Transactions on Software Engineering, 33, 369-384.

Digital Library

[3]

Chazalet, A. (2010a). Service level checking in the cloud computing context. In 3th IEEE international conference on cloud computing (pp. 297-304).

[4]

Chazalet, A. (2010b). Service level agreements compliance checking in the cloud computing: architectural pattern, prototype, and validation. In 5th International conference on software engineering advances (pp. 184-189).

[5]

Chuan, D., Lin, Y., Linru, M., & Yua, C. (2011). Towards a practical and scalable trusted software dissemination system. Journal of Convergence, 2, 53-60.

[6]

Chuang, S. N., & Chan, A. T. S. (2008). Dynamic QoS adaptation for mobile middleware. IEEE Transactions on Software Engineering, 34, 738-752.

Digital Library

[7]

Dominguez-Sal, D., Perez-Casany, M., & Larriba-Pey, J. L. (2010). Cooperative cache analysis for distributed search engines. International Journal of Information Technology, Communications and Convergence, 1, 41-65.

[8]

Erginel, N. (2010). Modeling and analysis of packing properties through a fuzzy inference system. Journal of Intelligent Manufacturing, 6, 869-874.

[9]

Ferretti, S., Ghini, V., Panzieri, F., Pellegrini, M., & Turrini, E. (2010). QoS-aware clouds. In 3th IEEE international conference on cloud computing (pp. 321-328).

[10]

Freeman, A. (1994). Fuzzy systems for control applications: The truck backer-upper. The Mathematica Journal, 4, 64-69.

[11]

Ghosh, R., Trivedi, K. S., Naik, V. K., & Kim, D. S. (2010). End-to-end performability analysis for infrastructure-as-a-service cloud: An interacting stochastic models approach. In 16th IEEE Pacific Rim international symposium on dependable computing (pp. 125-132).

[12]

Hoi, C., & Trieu, C. (2010). Ranking and mapping of applications to cloud computing services by SVD. In 1th IEEE/IFIP intenational workshops on network operations and management symposium (pp. 362-369).

[13]

Hwang, S. Y., Wang, H., Tang, J., & Srivastava, J. (2007). A probabilistic approach to modeling and estimating the QoS of web-services-based workflows. Information Sciences, 177, 5484-5503.

Digital Library

[14]

Jackson, K. R., Ramakrishnan, L., Muriki, K., Canon, S., Cholia, S., Shalf, J., et al. (2010). Performance analysis of high performance computing applications on the Amazonweb services cloud. In IEEE second international conference on in cloud computing technology and science (pp. 159-168).

[15]

Jeguirim, S. E. G., Dhouib, A. B., Sahnoun, M., Cheikhrouhou, M., Schacher, L., & Adolphe, D. (2011). The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics. Journal of Intelligent Manufacturing, 6, 873-884.

[16]

Kryvinska, N., Thanh, D. V., & Strauss, C. (2010). Integrated management platform for seamless services provisioning in converged network. International Journal of Information Technology, Communications and Convergence, 1, 77-91.

[17]

Kuo, Y. F., & Chen, P. C. (2006). Selection of mobile value-added services for system operators using fuzzy synthetic evaluation. Expert Systems with Applications, 30, 612-620.

Digital Library

[18]

Lee, M., Yoon, H., Shin, H., & Lee, D. G. (2009). Intelligent dynamic workflow support for a ubiquitous Web service-based manufacturing environment. Journal of Intelligent Manufacturing, 20, 295-302.

[19]

Lee, M., Lee, J., Kim, K., & Park, S. S. (2011). Evaluating service description to guarantee quality of U-service ontology. Journal of Information Processing Systems, 7, 287-298.

[20]

Li, D., Cheung, D., Shi, X., & Ng, V. (1998). Uncertainty reasoning based on cloud models in controllers. Computers and Mathematics with Applications, 35, 99-123.

[21]

Li, F., Yang, F., Shuang, K., & Su, S. (2008). A policy-driven distributed framework for monitoring quality of web services. In 6th IEEE international conference on web services (pp. 708-715).

[22]

Lim, H., Jang, K., & Kim, B. (2010). A study on design and implementation of the ubiquitous computing environment-based dynamic smart on/off-line learner tracking system. Journal of Information Processing Systems, 6, 609-620.

[23]

Newton, P. C., & Arockiam, L. (2011). A novel prediction technique to improve quality of service (QoS) for heterogeneous data traffic. Journal of Intelligent Manufacturing 6, 867-872.

[24]

Oh, S. (2010). New role-based access control in ubiquitous e-business environment. Journal of Intelligent Manufacturing, 21, 607-612.

Digital Library

[25]

Pei, L., Comerio, M., Maurino, A., & De Paoli, F. (2009). An approach to non-functional property evaluation of web services. In 7th IEEE international conference on web services (pp. 1004-1005).

[26]

Pyshkin, E., & Kuznetsov, A. (2010). Approaches for web search user interfaces: How to improve the search quality for various types of information. Journal of Convergence, 1, 1-8.

[27]

Qi, Y., & Bouguettaya, A. (2010). Computing service skyline from uncertain QoWS. IEEE Transactions on Services Computing, 3, 16-29.

Digital Library

[28]

Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.

[29]

Shangguang, W., Qibo, S., & Fangchun, Y. (2010). An approach for QoS measure of web service with multifactor support. In IEEE GLOBECOM workshops on web and pervaisve seccurity (pp. 1586-1590).

[30]

Stantchev, V. (2009). Performance evaluation of cloud computing offerings. In 3th International conference on advanced engineering computing and applications in sciences (pp. 187-192).

[31]

Van Broekhoven, E., & De Baets, B. (2009). Only smooth rule bases can generate monotone Mamdani-Assilian models under center-of-gravity defuzzification. IEEE Transactions on Fuzzy Systems, 17, 1157-1174.

Digital Library

[32]

Wang, R. C., Chang, Y. C., & Chang, R. S. (2009). A semantic service discovery approach for ubiquitous computing. Journal of Intelligent Manufacturing, 20, 327-335.

[33]

Wang, S. G., Sun, Q. B., & Yang, F. C. (2010). Towards web service selection based on QoS estimation. International Journal of Web and Grid Services, 6, 424-443.

Digital Library

[34]

Yigitbasi, N., Iosup, A., Epema, D., & Ostermann, S. (2009). C-Meter: A framework for performance analysis of computing clouds. In 9th IEEE/ACM international symposium on cluster computing and the grid (pp. 472-477).

[35]

Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.

Cited By

Liu YZhan LHao J(2024)Static Cloud Vector for Computing the General Quality performance of Outsourcing components in Complex Product Supply ChainProceedings of the 2024 International Conference on Digital Economy and Computer Science10.1145/3705618.3705622(20-24)Online publication date: 20-Sep-2024
https://dl.acm.org/doi/10.1145/3705618.3705622
Alkalbani AAl Ruqeishi KSalah AMohamed M(2023)Virtual machine placement in service-oriented computing environmentsService Oriented Computing and Applications10.1007/s11761-023-00362-y17:2(119-127)Online publication date: 18-Apr-2023
https://dl.acm.org/doi/10.1007/s11761-023-00362-y
Khoda Parast FSindhav CNikam SIzadi Yekta HKent KHakak S(2022)Cloud computing securityComputers and Security10.1016/j.cose.2021.102580114:COnline publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.cose.2021.102580
Show More Cited By

Towards an accurate evaluation of quality of cloud service in service-oriented cloud computing
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Intelligent Manufacturing

Journal of Intelligent Manufacturing Volume 25, Issue 2

April 2014

148 pages

ISSN:0956-5515

Issue’s Table of Contents

Copyright © Copyright © 2014 Springer Science+Business Media New York.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 April 2014

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

35
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 17 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Liu YZhan LHao J(2024)Static Cloud Vector for Computing the General Quality performance of Outsourcing components in Complex Product Supply ChainProceedings of the 2024 International Conference on Digital Economy and Computer Science10.1145/3705618.3705622(20-24)Online publication date: 20-Sep-2024
https://dl.acm.org/doi/10.1145/3705618.3705622
Alkalbani AAl Ruqeishi KSalah AMohamed M(2023)Virtual machine placement in service-oriented computing environmentsService Oriented Computing and Applications10.1007/s11761-023-00362-y17:2(119-127)Online publication date: 18-Apr-2023
https://dl.acm.org/doi/10.1007/s11761-023-00362-y
Khoda Parast FSindhav CNikam SIzadi Yekta HKent KHakak S(2022)Cloud computing securityComputers and Security10.1016/j.cose.2021.102580114:COnline publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.cose.2021.102580
Li GZhou MFeng ZLi MJiang H(2022)Research on Key Influencing Factors of E-Government Cloud Service SatisfactionWireless Personal Communications: An International Journal10.1007/s11277-021-08567-0127:2(1117-1135)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1007/s11277-021-08567-0
Yi H(2021)A post-quantum secure communication system for cloud manufacturing safetyJournal of Intelligent Manufacturing10.1007/s10845-020-01682-y32:3(679-688)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s10845-020-01682-y
Hosseinzadeh MHama HGhafour MMasdari MAhmed OKhezri H(2020)Service Selection Using Multi-criteria Decision Making: A Comprehensive OverviewJournal of Network and Systems Management10.1007/s10922-020-09553-w28:4(1639-1693)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s10922-020-09553-w
Yin SBao JZhang JLi JWang JHuang X(2020)Real-time task processing for spinning cyber-physical production systems based on edge computingJournal of Intelligent Manufacturing10.1007/s10845-020-01553-631:8(2069-2087)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1007/s10845-020-01553-6
Feng YHuang B(2020)Cloud manufacturing service QoS prediction based on neighbourhood enhanced matrix factorizationJournal of Intelligent Manufacturing10.1007/s10845-018-1409-831:7(1649-1660)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s10845-018-1409-8
Zhang GZhang YZhong RWu Y(2019)Extending augmented Lagrangian coordination for the optimal configuration of cloud-based smart manufacturing services with production capacity constraintRobotics and Computer-Integrated Manufacturing10.1016/j.rcim.2019.01.00958:C(21-32)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1016/j.rcim.2019.01.009
Liono JJayaraman PQin ANguyen TSalim F(2019)QDaSJournal of Parallel and Distributed Computing10.1016/j.jpdc.2018.03.013127:C(196-208)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1016/j.jpdc.2018.03.013
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents