# data[].attributes.body
Certification Date:
Jan 2018 – Present

# data[].attributes.attachment_link.title
Python for Data Science was issued by IBM to Steven Wong Tong Sheng.

# data[].attributes.attachment_link.description
The badge earner is able to write their own Python scripts and perform basic hands-on data analysis using IBM's Jupyter-based lab environment.

# data[].attributes.body
https://www.linkedin.com/in/steven-wong-tong-sheng-336410124/

# data[].attributes.body
A pleasant guy who are currently pursing his master at MMU.
Love spending time doing his research on machine learning for predict future and meaningful data.

# data[].attributes.body
1. Python
2. Java
3. R
4. C#(ASP.NET)
5. C++

(Constantly Learning)

# data[].attributes.headline
A Machine Learning Model for Detection and Prediction of Cloud Quality of Service Violation. 

# data[].attributes.subject
A Machine Learning Model for Detection and Prediction of Cloud Quality of Service Violation. 

# data[].attributes.body
Tong-Sheng Wong, Gaik-Yee Chan, and Fang-Fang Chua (2018)

ICCSA 2018: Computational Science and Its Applications – ICCSA 2018 pp 498-513

https://link.springer.com/chapter/10.1007/978-3-319-95162-1_34

# data[].attributes.attachment_link.readable_text
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10960)

Abstract

Cloud services connect user with cloud computing platform where services range from Infrastructure as a Service, Software as a Service and Platform as a Service. It is important for Cloud Service Provider to provide reliable cloud services which are fast in performance and to predict possible service violation before any issue emerges so then remedial action can be taken. In this paper, we therefore experiment with five different machine learning algorithms namely Support Vector Machine, Random Forest, Naïve Bayes, Neural Network, and k-Nearest Neighbors for the detection and prediction of cloud quality of service violations in terms of response time and throughput. Experimental results show that the model created using SVM incorporated with 16 derived cloud quality of service violation rules has consistent accuracy of greater than 99%. With this machine learning model coupled with 16 decision rules, the Cloud Service Provider shall be able to know before hand, whether violation of services based on response time and throughput is occurring. When transactions tend to go beyond the threshold limits, system administrator shall be alerted to take necessary preventive measures to bring the system back to normal conditions. This shall reduce the chance for violation to occur, hence mitigating lose or costly penalty.

Keywords

Cloud services Machine learning Quality of service violations

This is a preview of subscription content, log in to check access.

References

1. Musa, S.M., Yousif, A., Bashi, M.B.: SLA violation detection mechanism for cloud computing. Int. J. Comput. Appl. 133, 8-11 (2016)

2. Leitner, P., Wetzstein, B., Rosenberg, F., Michlmayr, A., Dustdar, S., Leymann, F.: Runtime prediction of service level agreement violations for composite services. In: Dan, A., Gittler, F., Toumani, F. (eds.) ICSOC/ServiceWave -2009. LNCS, vol. 6275, pp. 176-186. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16132-2_17

3. Popescu, M.C., Balas, V.E., Perescu-Popescu, L., Mastorakis, N.: Multilayer perceptron and neural networks. WSEAS Trans. Circ. Syst. 8, 579-588 (2009)

4. Bishop, C.M.: Neural Networks for Pattern Recognition. Clarendon Press, Oxford (1995)

5. Guo, G., Wang, H., Bell, D., Bi, Y., Greer, K.: KNN model-based approach in classification. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) OTM 2003. LNCS, vol. 2888, pp. 986-996. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-39964-3_62

6. Hossin, M., Sulaiman, M.N.: A review on evaluation metrics for data classification evaluations. Int. J. Data Min. Knowl. Manag. Process (IJDKP) 5(2), 1-11 (2015). https://doi.org/10.5121/ijdkp.2015.5201

7. McHugh, M.L.: Interrater reliability: the kappa statistic. Biochem. Med. 22(3), 276-282 (2012)

# data[].attributes.attachment_link.title
A Machine Learning Model for Detection and Prediction of Cloud Quality of Service Violation

# data[].attributes.attachment_link.description
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10960) Cloud services connect user with cloud computing platform where services range from Infrastructure as a Service, Software as a Service and Platform as a Service.