An Automated Code Optimizer of Design Patterns for Reducing Energy Usage in Green Computing


  • Jamilah Din
  • Ooi Chiew Wei
  • Muhammed Basheer Jasser
  • . .





cloud data centre, energy efficiency, DVFS, cloud applications.


Cloud data center contains various resources which are utilized continuously without any break. The data center consumed large energy to keep the components to run 24/7 for achieving certain performances. Such energy usage becomes one of the major issues in the Cloud data center. It is due to the Cloud availability is highly demanded in network community. In this study, we formed an analysis on the energy consumption by considering the CPU usages through the existing Dynamic Voltage and Frequency Scaling (DVFS) techniques that proposed in existing researches. The aim of this work is to investigate and identify Cloud services application factors that can be employed on the DVFS for better energy management in Cloud data center. Our study expresses the areas of the Cloud service applications such as Business Application-as-a-Services, Consumer Application-as-a-Services and Scientific Application as-a Service that embedded in DVFS where it can be part of the energy saving contributors. We also analysed the two main factors in DVFS are proportional to time and frequency that can be adjusted towards energy efficient in the data center. The survey is also investigated on how far such functions can be manipulated for energy saving while investigating potential solutions for further enhancement.



[1] Beik, R.: Green cloud computing: An energy-aware layer in software architecture. In Engineering and Technology (S-CET), Spring Congress on (pp. 1-4). IEEE, (2012).

[2] Bunse, C., Schwedenschanze, Z., and Stiemer, S.:On the energy con- sumption of design patterns. In Proceedings of the 2nd Workshop EASED@ BUIS Energy Aware Software-Engineering and Development (pp. 7-8), (2013).

[3] Jagroep, E., van der Werf, J. M., Brinkkemper, S., Blom, L., and van Vliet, R.: Extending software architecture views with an energy con- sumption perspective. Computing, 1-21, (2016).

[4] Litke, A., Zotos, K., Chatzigeorgiou, A., and Stephanides, G.: Energy consumption analysis of design patterns. In Proceedings of the Interna- tional Conference on Machine Learning and Software Engineering (pp. 86-90), (2005).

[5] Noureddine, A., and Rajan, A.: Optimizing energy consumption of design patterns. In Proceedings of the 37th International Conference on Software Engineering-Volume 2 (pp. 623-626). IEEE Press, (2015).

[6] Ramirez, R. I., Rubio, E. H., Viveros, A. M., & Herna´ndez, I. M. T.: Differences of energetic consumption between Java and JNI Android apps. In Integrated Circuits (ISIC), 2014 14th International Symposium on (pp. 348-351). IEEE, (2014).

[7] Rangaraj, G., and Bahsoon, R.: Green software architectures: A market-based approach. In The Second International Workshop on Software Research and Climate Change (WSRCC), (2010).

[8] Sahin, C., Cayci, F., Gutie´rrez, I. L. M., Clause, J., Kiamilev, F., Pollock, L., and Winbladh, K.: Initial explorations on design pattern energy usage. In Green and Sustainable Software (GREENS), 2012 First International Workshop on (pp. 55-61). IEEE, (2012).

[9] Wang, D.: Meeting green computing challenges. In Electronics Pack- aging Technology Conference, 2008. EPTC 2008. 10th (pp. 121-126). IEEE, (2008).

[10] Williams, J., and Curtis, L.: Green: The new computing coat of arms? IT Professional Magazine, 10(1), 12, (2008).

[11] Zhong, B., Feng, M., and Lung, C. H.: A green computing based architecture comparison and analysis. In Proceedings of the 2010 IEEE/ACM Int’l Conference on Green Computing and Communications & Int’l Conference on Cyber, Physical and Social Computing (pp. 386-391). IEEE Computer Society, (2010, December).

[12] Lago, P., Kazman, R., Meyer, N., Morisio, M., Mu¨ ller, H.A. and Paulisch, F., . Exploring initial challenges for green software engineering: summary of the first GREENS workshop, at ICSE 2012. ACM SIGSOFT Software Engineering Notes, 38(1), pp.31-33, (2013).

[13] Gamez, N., Pinto, M., and Fuentes, L.: HADAS Green Assistant: de- signing energy-efficient applications. arXiv preprint arXiv:1612.08095, (2016).

[14] Procaccianti, G., Lago, P., Vetro`, A., Ferna´ndez, D. M., and Wieringa, R.: The green lab: Experimentation in software energy efficiency. In Proceedings of the 37th International Conference on Software Engineering Volume 2 (pp. 941-942). IEEE Press, (2015).

[15] Kern, E., Dick, M., Naumann, S., Guldner, A., & Johann, T.: Green software and green software engineering–definitions, measurements, and quality aspects., 87-94, (2013).

[16] Shenoy, S. S., and Eeratta, R.: Green software development model: An approach towards sustainable software development. In India Conference (INDICON), Annual IEEE (pp. 1-6). IEEE, (2011).

[17] Stier, C., Koziolek, A., Groenda, H., and Reussner, R.: Model- Based Energy Efficiency Analysis of Software Architectures. In European Con- ference on Software Architecture (pp. 221-238). Springer International Publishing, (2015).

[18] Rubyga, G., and SathiaBhama, P. R.: A survey of computing strategies for green cloud. In Science Technology Engineering and Management (ICONSTEM), Second International Conference on (pp. 141-145). IEEE, (2016).

[19] Gamez, N., Horcas, J. M., Pinto, M., and Fuentes, L.: A green program lifecycle supporting energy-efficient applications. arXiv preprint arXiv:1612.08073, (2016).

[20] Becker, C., Betz, S., Chitchyan, R., Duboc, L., Easterbrook, S. M., Penzenstadler, B. and Venters, C. C.: Requirements: The key to sustainability. IEEE Software, 33(1), 56-65, (2016).

[21] Manotas, I., Bird, C., Zhang, R., Shepherd, D., Jaspan, C., Sadowski, C. and Clause, J.: An empirical study of practitioners’ perspectives on green software engineering. In Proceedings of the 38th International Conference on Software Engineering (pp. 237-248). ACM, (2016).

[22] Feitosa, D., Alders, R., Ampatzoglou, A., Avgeriou, P., and Nakagawa, E. Y.: Investigating the effect of design patterns on energy consumption. Journal of Software: Evolution and Process, 2(29), (2017).

[23] Decorator pattern. Retrieved from, July 2018.

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How to Cite

Din, J., Chiew Wei, O., Basheer Jasser, M., & ., . (2018). An Automated Code Optimizer of Design Patterns for Reducing Energy Usage in Green Computing. International Journal of Engineering & Technology, 7(4.31), 511–515.
Received 2019-01-06
Accepted 2019-01-06
Published 2018-12-09