Estimating Energy usage of Transactions in Mobile Applications

International Journal of Computer Science and Engineering
© 2015 by SSRG - IJCSE Journal
Volume 2 Issue 7
Year of Publication : 2015
Authors : Vijaya Shetty S, Sarojadevi H, Navya K.M

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Citation:
MLA Style:

Vijaya Shetty S, Sarojadevi H, Navya K.M, "Estimating Energy usage of Transactions in Mobile Applications" SSRG International Journal of Computer Science and Engineering 2.7 (2015): 9-14 .

APA Style:

Vijaya Shetty S, Sarojadevi H, Navya K.M, (2015). Estimating Energy usage of Transactions in Mobile Applications. SSRG International Journal of Computer Science and Engineering 2.7, 9-14.

Abstract:

Performance of transactions in mobile applications is gaining importance due to the increased usage of these applications in mobile phones. The increased functionality of transactions in these applications incurs higher energy cost and results in degradation of performance in mobile phones. To improve the energy consumption of mobile application transactions, developers need detailed information about the energy consumption of transactions in their applications. This paper presents a review of different tools and techniques available for energy estimation of mobile applications. The paper also proposes a new technique which provides the code level energy estimation of transactions in mobile applications. This technique instruments the bytecode of the application to obtain execution paths of different transactions through the code, analyses the execution traces of the transactions and estimates the energy usage for each transaction and the application as a whole. The energy consumption feedback is given to the developer for further optimization of the code. The proposed technique does not require any expensive hardware for energy monitoring as it is based on bytecode instrumentation and profiling.

References:

[1] Vijaya Shetty S, H. Sarojadevi, ―e-Business Performance Issues, Quality Metrics and Development Frameworks‖, International Journal of Computer Applications, ISSN- 0975 – 8887, pp. 42-47, Volume 55– No.7, October 2012. 
[2] Vijaya Shetty S, Dr.H.Sarojadevi,‖Performance Analysis of Transactional Applications in AMD Quad-Core and Intel i5 Processor Systems‖, Advanced Research in Engineering and Technology, ISBN-978-81-910691-7-8, pp 381-388, Volume 8, Feb 2014. 
[3] S. V. Shetty, H. Sarojadevi, B. Sriram, "A Highly Robust Proxy Enabled Overload Monitoring System (P-OMS) for EBusiness Web Servers‖, Smart Innovation, Systems and Technologies , ISBN: 978-81-322-2201-9 (Print) 978-81- 322-2202-6 (Online), Volume 33,pp. 385-394, Dec 2014. 
[4] http://developer.android.com/tools/help/traceview.html, ―Traceview‖.
[5] https://play.google.com/store/apps/details?id=edu.umich.Pow erTutor&hl=enttp://developer.android.com/guide/component s/aidl.html
[6] https://developer.qualcomm.com/software/trepn-powerprofiler, ―Trepn Power Profiler‖.
[7] https://visualvm.java.net/, ―VisualVm 1.3.8‖.
[8] D. Li, S. Hao, W. G. Halfond, and R. Govindan, ―Calculating source line level energy information for android applications,‖ in Proceedings of the 2013 International Symposium on Software Testing and Analysis (ISSTA), July 2013. 
[9] T. Mudge, T. Austin, and D. Grunwald, ―The Reference Manual for the Sim-Panalyzer Version 2.0.‖ 
[10] D. Brooks, V. Tiwari, and M. Martonosi, ―Wattch: A framework for architectural-level power analysis and optimizations,‖ in Proceedings of the 27th International Symposium on Computer Architecture (ISCA),2000. 
[11] Shuai Hao, Ding Li, William G. J. Halfond, Ramesh Govindan,‖ Estimating Mobile Application Energy Consumption using Program Analysis‖,IEEE,2013. 
[12] T. Li and L. K. John, ―Run-time modeling and estimation of operating system power consumption,‖ ACM SIGMETRICS Performance Evaluation Review, 2003. 
[13] L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. Dick, Z. Mao, and L. Yang, "Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smartphone",in Proc. of IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis, pages 105–114. ACM, 2010. 
[14] L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. Dick, Z. Mao, and L. Yang. "Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smart phones", ACM, 2010. 
[15] A.Caroll and G.Heiser,"an analysis of power consumption in a smartphone",in USENIX ATC,2010. 
[16] D. Li and W. G. Halfond, ―An investigation into energysaving programming practices for android smartphone app development.‖ in Proceedings of the 3rd International Workshop on Green and Sustainable Software (GREENS), 2014. 
[17] Sona Mundody, Sudarshan. K, ―Evaluating the Impact of Android Best Practices on Energy Consumption‖ , International Conference on Information and Communication Technologies,2013. 
[18] M. Dong and L. Zhong. Sesame:"Self-Constructive System Energy Modeling for Battery-Powered Mobile Systems", MobiSys, 2011. 
[19] Simon Schubert, Dejan Kostic, Willy Zwaenrpoel, Kang G. Shin, " Profiling software for energy consumption", In IEEE international conference on green computing and communication,2012. 
[20] Luca Ardito, Giuseppe Procaccianti, Marco Torchiano, Giuseppe Migliore," Profiling Power Consumption on Mobile Devices", Third International Conference on Smart Grids, Green Communications and IT Energy-aware Technologies, Energy 2013. 
[21] J. Flinn and M. Satyanarayanan. Powerscope: A Tool for Profiling the Energy Usage of Mobile Applications. In Second IEEE Workshop on Mobile Computing Systems and Applications, pages 2–10. IEEE, 1999. 
[22] Yoon Chanmin, Kim Dongwon, Jung Wonwoo, Kang Chulkoo, Cha Hojung, "Appscope : Application energy metering framework for android smartphone using kernel activity",ACM,2012. 
[23] A. Pathak, Y. C. Hu, M. Zhang, P. Bahl, and Y.-M. Wang, "Where is the energy spent inside my app? Fine Grained Energy Accounting on Smart phones with Eprof", In Proc. of EuroSys, 2012. 
[24] Shuai Hao, Ding Li, William G. J. Halfond, Ramesh Govindan,‖ Estimating Android Applications CPU Energy Usage via Bytecode Profiling‖,IEEE,2012.

Key Words:

Performance, Mobile Application, Bytecode, Energy estimation, Profiling.