Art. 02 – Vol. 27 – No. 2 – 2017

Attributes and Associated Metersfor Quality Assessment
of Cloud Computing Services

Constanţa Zoie RĂDULESCU
radulescu@ici.ro
Delia Mihaela RĂDULESCU
delia.radulescu@ici.ro
National Institute for Research & Development of Informatics – ICI Bucharest

Abstract: The assessment of cloud services and cloud service providers is a complex issue, mainly due to the large and growing number of cloud providers, the level of quality and pricing of the services they provide. Based on the services cloud evaluation, a user will be able to select from the set of cloud providers the one that best meets their requirements. The article analyzes the attributes of the Service Measurement Index (SMI) and performs a classification of attributes in quantitative and qualitative attributes. Next, the attributes assessed in the Service Level Agreement (SLA) are presented according to the cloud type: Software as a Service (SaaS), Infrastructure as a Service IaaS) and platform as a service (PaaS). Finally, the calculation of the main quantitative attributes of cloud services is formalized.

Keywords: Evaluation, Cloud Computing, attributes, quality, Service Measurement Index, metrics, Service Level Agreement.

REFERENCES

  1. *** Gartner Report:
    https://www.cloudcomputing-news.net/news /2017/feb/22/gartner-public-cloud-market-reach-246bn-2017-iaas-and-saas-forefront/.
  2. ARDAGNA, D.; CASALE, G.; CIAVOTTA, M.; PEREZ J. F.; WANG W.: Quality-of-Service in cloud computing: modeling techniques and their applications, Journal of Internet Services and Applications, Vol: 5, Issue: 11, 2014, pp. 1-12.
  3. STANTCHEV, V.; SCHROPFER C.: Negotiating and enforcing QoS and SLAs in grid and cloud computing, in Proc. Int. Conf. on Advances in Grid and Pervasive Computing, GPC 09, 2009, pp. 25-33.
  4. WAGLE, S.; GUZEK, M.; BOUVRY, P.; BISDORFF R.: An Evaluation Model for Selecting Cloud Services from Commercially Available Cloud Providers, IEEE 7th International Conference on Cloud Computing Technology and Science, 2015.
  5. *** Cloud computing reference architecture, 2011, NIST, http://www.nist.gov/itl/antd/cloud-102214.cfm”.
  6. *** Service Measurement Index Framework Version 2.1, 2014, http://csmic.org/ downloads/SMI overview_TwoPointOne.pdf.
  7. *** Cloud Services Measurement Initiative Consortium, 2016, http://csmic.org/. “Selecting a cloud provider defining widely accepted measures for cloud services”.
  8. *** Cloud Service Measurement Index Consortium (CSMIC). “Service Measurement Index Version 1.0”, 2011.
  9. SAURABH KUMAR G..; VERSTEEG ; BUYYA R.: A framework for ranking of cloud computing services. Future Generation Computer Systems, Vol. 29, Issue 4, 2013, pp. 1012–1023.
  10. SUBRAMANIAN, T.; SAVARIMUTHU, N.: Application based brokering algorithm for optimal resource provisioning in multiple heterogeneous clouds. Vietnam J. Comput. Sci. 3, 2016, pp.57–70.
  11. HENNAN, J.; ROANE J., G.: Security monitoring tool for computer network. USPatent 7, 904, 456, issued March 8, 2011.
  12. BARTH, W., NAGIOS.: System and Network Monitoring, No Starch Press, 2008.
  13. QU LIE.; WANG YAN.; ORGUN MEHMET, A.; LIU LING.; BOUGUETTAYA ATHMAN.: Cloud service selection based on contextual subjective assessment and objective assessment. In: Proceedings of the 2014 International Conference on Autonomous Agents and Multi-Agent Systems, International Foundation for Autonomous Agents and Multiagent Systems, 2014, pp.1483–1484.
  14. SINGH S.; CHAND D.: Trust evaluation in cloud based on friends and third party’s recommendations. In: Engineering and Computational Sciences (RAECS), Recent Advances in, IEEE, 2014.

View full article

  1. *** IEEE Standards Association and Others, IEEE STD 1061–1998, IEEE standard for a software quality metrics methodology, 1998.
  2. LUDWIG, H.; KELLER, A.; KING DAN, A.; FRANCK, R.: Web service level agreement (WSLA) language specification. IBM Corporation 2003.
  3. ANDRIEUX, A.; CZAJKOWSKI, K.; DAN, A.; KEAHEY, K.; LUDWIG, H.; PRUYNE, J.; ROFRANO, J.; TUECKE, S.; XU, M.: Web services agreement specification (WS-Agreement). In: Global Grid Forum, 2004.
  4. BUYYA, R.; YEO, C. S.; VENUGOPAL, S.; BROBERG, J; BRANDIC, I:  Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility, Journal of Future Generation Computer Systems, Vol 25, Issue 6, 2009, pp. 559-616.
  5. *** Practical Guide to Cloud Service Level Agreements: http://www.cloud-council.org/ deliverables/ CSCC-Practical-Guide-to-Cloud-Service-Agreements.pdf.
  6. CHEN, Y.M.; Peng, Y.J.: A QoS aware services mashup model for cloud computing applications, Journal of Industrial Engineering and Management5(2), 2012, pp. 457-472.
  7. CHEN, T.; BAHSOON, R.: Self-Adaptive and Sensitivity-Aware QoS Modeling for the Cloud. In: Software Engineering for Adaptive and Self-Managing Systems (SEAMS ’13), 2013, pp. 44-52, San Francisco, CA, USA.
  8. YE, Z.; BOUGUETTAYA, A.; Zhou, X: QoS-aware cloud service composition based on economic models. In: Proceedings of the 10th International Conference on Service-Oriented Computing, ICSOC’12, Shanghai, China, 2012, pp. 111–126.
  9. WU, X.; DENG M.; Zhang, R.; ZENG, B.; ZHOU, S.: A task scheduling algorithm based on QoS-driven. In: Cloud Computing Information Technology and Quantitative Management (ITQM’13), 2013, pp.1162-1169.
  10. CHANG, V.; RAMACHANDRAN, M.: Quality of Service for Financial Modeling and Prediction-as-a-Service. In: Emerging Software-as-a-Service and Analytics Workshop, in conjunction with CLOSER, 20 – 22 May
  11. BUYYA, R.; RANJAN, R.; CALHEIROS, R. N.: InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services, Algorithm and Architectures for Parallel Processing. Lecture Notes in Computer Science, Vol. 6081/2010, (2010 a), pp. 13-31.
  12. BUYYA, R.; BELOGLAZOV1, A.; ABAWAJY, J.: Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges. PDPTA’10 – The International Conference on Parallel and Distributed Processing Techniques and Applications, 12-15 July, Las Vegas,USA, (2010 b).
  13. PASCHKE, A.; SCHNAPPINGER-GERULL, :A Categorization Scheme for SLA Metrics. Multikonferenz wirtschafts informatik 2006: Passau, Germany, Service Oriented Electronic Commerce, 2006, pp. 25-40.
  14. ALJOUMAH ; FAJER AL-MOUSAWI.: SLA in Cloud Computing Architectures: A Comprehensive Study –  Imtiaz Ahmad, Maha Al-Shammri and Zahraa Al-Jady. International Journal of Grid Distribution Computing Vol. 8, No.5, 2015, pp.7-32.
  15. ALHAMAD, M.; DILLON, T.; CHANG, E.: Conceptual SLA Framework for Cloud Computing, 4th IEEE International Conference on Digital Ecosystems and Technologies, 13-16 April 2010, Australia, pp. 606 – 610.
  16. PAN, H.: Green Data Centers monthly newsletter February 2010, Information Gatekeepers Inc.
  17. *** RACKSPACE.: Cloud servers, URL: http://www.rackspace.com.
  18. RăDULESCU, C. Z.: Cloud providers’ services evaluation using triangular fuzzy numbers. In Proceedings of the 21th International Conference on Control Systems and Computer Science (CSCS21, May 29 to May 31, 2017.
  19. RăDULESCU, C. Z.; BALOG, A.; RăDULESCU, D. M.; DUMITRACHE, M.: A decision making framework for weighting and ranking criteria for Cloud provider selection. Proceedings of the 20th International Conference on System Theory, Control and Computing, October 13-15, 2016, Sinaia, Romania, pp. 590-595.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

| Designed by ICI București
© Copyright 2008-2023, All Rights Reserved