Software metric evaluation on cloud based applications

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Unbound growth in the cloud computing service models have motivated the companies building traditional software to be migrated into the clouds. During the high demand of the traditional applications, the performance and quality of the software were evaluated by the popular and globally accepted metrics. Nevertheless, after the migration of the same applications into the cloud, the expectation and definition of performance and quality has been changed. The beneficiaries of these applications are setting new milestones for the applications. Hence, the recent demand of the research trend is to build new software metric models to match the trade of between the new expectations from the beneficiaries and the software quality policies for organization or individual or state. Thus this work makes an attempt to understand the traditional software quality metrics and try to justify the applicability of these parameters in the trend of cloud based software applications. This work also proposes a novel metric method for performance evaluation for the migrated applications into the cloud, with the intension of formalizing and standardizing the cloud based metric methods unlike the recent trends.


  • Keywords


    Software Metrics; Direct Analysis; Indirect Analysis; Cloud Data Centre Performance; Architectural metric model; Design metric model; Quality Index

  • References


      [1] Norman E. Fenton, 1991, Software Metrics, A Rigorous Approach, Chapman & Hall, London

      [2] A Survey of Software Metrics, Fabrizio Riguzzi, July 1996, DEIS Technical Report no. DEIS-LIA-96-010.

      [3] A.Mili .et.al. Semantic software metrics.2013.

      [4] Bohem, B.W, Brown,j.R. and Lipow, M, “Quantitve evaluation of software quality” proceedings of the second international conference on software engineering, 1976.

      [5] Norman E.Fenton, shari Lawerance Pfleeger. Software metrics Arigorous and practical approach. Second edition.PWS Publishing company. 20 park plaza Boston.

      [6] Dromy. R.G, “cornering the chimera” , IEEE software ,31(1),33- 34,1996.

      [7] Z. Zhang, X. Cheng, S. Su, Y. Wang, K. Shuang and Y. Luo "A unified enhanced particle swarm optimization-based virtual network embedding algorithm", Int. J. Commun. Syst., vol. 26, no. 8, pp.1054 -1073 2013

      [8] X. Cheng, S. Su, Z. Zhang, K. Shuang, F. Yang, Y. Luo and J. Wang "Virtual network embedding through topology awareness and optimization", Comput. Netw., vol. 56, no. 6, pp.1797 -1813 2012

      [9] G. Sun, V. Anand, H. Yu, D. Liao, Y. Cai and L. Li "Adaptive provisioning for evolving virtual network request in cloud-based data centers", Proc. IEEE GLOBECOM, pp.1617 -1622 2012

      [10] Christof Ebert and Reiner Dumke. Software Measurement: Establish, Extract, Evaluate, Execute. Springer V erlag, 2007

      [11] Norman E. Fenton and Shari Lawrence Pfleeger. Software Metrics: A Rigorous and Practical Approach. PWS Publishing Company, 1997.

      [12] G. Eason, B. Noble, and I. N. Sneddon, “On certain integrals of Lips Software Metrics SEI Curriculum Module, SEI-CM-12-1.1, December 1988.

      [13] A Survey on Metric of Software Complexity Sheng Yu, Shijie Zhou.

      [14] Survey on Impact of Software Metrics on Software Quality - (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, No. 1, 2012

      [15] McCabe T. A complexity metric. IEEE Transactions on Software Engineering, 1976, 2(4): 308-320.

      [16] Torn, A., T. Andersson and K. Enholm, 1999. A complexity metrics

      [17] Gall, C. S. Inf. Technol. & Syst. Center, Univ. of Alabama in Huntsville, Huntsville, AL Lukins, Stacy K.; Etzkorn, Letha H.; Gholston, Sampson; Farrington, Phillip A.; Utley, Dawn R.; Fortune, J.; Virani, Shamsnaz Semantic Metrics, Conceptual Metrics, and Ontology Metrics: Volume: 2 , Issue: 1 Page(s): 17 – 26.

      [18] Eric S. Raymond, the Art of Unix Programming, Addison-Wesley, New York, 2004.

      [19] Kunja Nagamani ; Ch. G. V. N. Prasad ; K. Shahu Chatrapati, A novel framework for optimal component based data center architecture, International Conference on Information Communication and Embedded Systems (ICICES), 2016, IEEE

      [20] Helali, Rasha Gaffer M. "Software semantic metrics: A Survey."

      [21] Dr. Seetaiah Kilaru, Harikishore K, Sravani T, Anvesh Chowdary L, Balaji T “Review and Analysis of Promising Technologies with Respect to fifth Generation Networks”, 2014 First International Conference on Networks & Soft Computing, ISSN:978-1-4799-3486-7/14,August2014.

      [22] S.V.Manikanthan and V.Rama“Optimal Performance Of Key Predistribution Protocol In Wireless Sensor Networks” International Innovative Research Journal of Engineering and Technology ,ISSN NO: 2456-1983,Vol-2,Issue –Special –March 2017.

      [23] T. Padmapriya, V.Saminadan, “Performance Improvement in long term Evolution-advanced network using multiple imput multiple output technique”, Journal of Advanced Research in Dynamical and Control Systems, Vol. 9, Sp-6, pp: 990-1010, 2017.

      [24] Rajesh, M., and J. M. Gnanasekar. "Path observation-based physical routing protocol for wireless ad hoc networks." International Journal of Wireless and Mobile Computing 11.3(2016): 244-257.


 

View

Download

Article ID: 9071
 
DOI: 10.14419/ijet.v7i1.5.9071




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.