CFP last date
22 April 2024
Reseach Article

Programmatic Effect of Optimized Smali Code on Saving Energy of Android Applications

by Marwa Dahdouh, Amer Bouchi, Souheil Khawatmi, Mouhamad Ayman Naal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 42
Year of Publication: 2020
Authors: Marwa Dahdouh, Amer Bouchi, Souheil Khawatmi, Mouhamad Ayman Naal
10.5120/ijca2020919928

Marwa Dahdouh, Amer Bouchi, Souheil Khawatmi, Mouhamad Ayman Naal . Programmatic Effect of Optimized Smali Code on Saving Energy of Android Applications. International Journal of Computer Applications. 177, 42 ( Mar 2020), 33-41. DOI=10.5120/ijca2020919928

@article{ 10.5120/ijca2020919928,
author = { Marwa Dahdouh, Amer Bouchi, Souheil Khawatmi, Mouhamad Ayman Naal },
title = { Programmatic Effect of Optimized Smali Code on Saving Energy of Android Applications },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2020 },
volume = { 177 },
number = { 42 },
month = { Mar },
year = { 2020 },
issn = { 0975-8887 },
pages = { 33-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number42/31186-2020919928/ },
doi = { 10.5120/ijca2020919928 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:48:27.436210+05:30
%A Marwa Dahdouh
%A Amer Bouchi
%A Souheil Khawatmi
%A Mouhamad Ayman Naal
%T Programmatic Effect of Optimized Smali Code on Saving Energy of Android Applications
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 42
%P 33-41
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the effect of saving Android application execution time on saving energy consumed by optimized applications. An algorithm for optimizing instructions on a Smali code-level proposes to provide execution time. The Smali optimization algorithm relies on replacing high execution times instructions with lower execution times ones and equivalent in behavior. MySMALI compiler is designed to support the proposed optimization algorithm and applied on Android applications. Optimized APK files are generated for optimized applications. Measurements of APKs execution times are taken. Measurements prove that the percentage of optimization in execution time is approximately 26.27%. The paper provides code-level estimates of the energy consumption of Android applications. A programmatic method about reading operating system files is applied to determine resource consumption by the applications. Energy measurements are also recorded by a power monitor (PowerTutor) for Android-based mobile platforms. The measurements of resources (Memory, CPU, Disk) consumption prove that the optimized compiler helps to save the consumption percentage of Android applications about 19.9%. The memory consumed is provided by the optimized compiler to approximately 20000 Kbyte and 31.7 KB size of files. The time that the optimized process of application consumes from the CPU time is reduced from 26% to 5%. The results demonstrate that the providing execution times of applications can save energy consumed to approximately 8.4%, and can save the power consumption by up to 14%.

References
  1. Claas Wilke et al, 2013, "Energy-Aware Development and Labeling for Mobile Applications", Technischen University Dresden.
  2. Shuai Hao, Ding Li, William G. J. Halfond, Ramesh Govindan, 2013, "Estimating Mobile Application Energy Consumption using Program Analysis", IEEE.
  3. Grace Metri, 2014, "Energy Efficiency Analysis And Optimization For Mobile Platforms", Wayne State University Dissertations.
  4. Irene Manotas Gutierrez, 2017, "Developing A Software Engineer's Energy-Optimization Decision Support Framework", University of Delaware.
  5. Anton Georgiev, Alberto Sillitti, Giancarlo Succi, 2016, "Open Source Mobile Virtual Machines: An Energy Assessment of Dalvik vs. ART", HAL Id: hal-01373061.
  6. Xueliang Li John P. Gallagher, 2016, "Energy Optimization of Source Code Guided by a Fine-Grained Energy Model", arXiv:1605.05234v1.
  7. Cagri Sahin, Mian Wan et al, 2016," How does code obfuscation impact energy usage?", JOURNAL OF SOFTWARE: EVOLUTION AND PROCESS.
  8. Abhijeet Banerjee, Abhik Roychoudhury, 2016, "Automated Re-factoring of Android Apps to Enhance Energy-efficiency", ACM.
  9. Shuai Hao, Ding Li et al, 2012," Estimating Android Applications’ CPU Energy Usage via Bytecode Profiling", IEEE.
  10. Hina Anwar et al, 2019, "Evaluating the impact of code smell refactoring on the energy consumption of Android applications", 45th Euromicro Conference on SEAA.
  11. Shaiful Chowdhury et al, 2017, "An exploratory study on assessing the energy impact of logging on Android applications", Springer Science.
  12. Fabio Palomba et al, 2018, "On the Impact of Code Smells on the Energy Consumption of Mobile Applications", Information and Software Technology.
  13. Marco Couto, J_acome Cunha et al, 2015,"Analyzing and Classifying Energy Consumption in Android Applications", Science of Computer Programming.
  14. Luis Corral, Anton B. Georgiev, Alberto Sillitti, Giancarlo Succi, 2014, "Can execution time describe accurately the energy consumption of mobile apps? An experiment in Android", ACM.
  15. Marco Couto, Tiago et al, 2014, "Detecting Anomalous Energy Consumption in Android Applications", Springer International Switzerland.
  16. Roberto Verdecchia et al, 2018, "Empirical Evaluation of the Energy Impact of Refactoring Code Smells", EPiC Series in Computing,Volume 52, Pages 365-383.
  17. Abhijeet Banerjee, Abhik Roychoudhury, 2016, "Future of Mobile Software for Smartphones and Drones: Energy and Performance", National University of Singapore.
  18. Marwa DAHDOUH, Amer BOUCHI, Souheil KHAWATMI, Mouhamad Ayman NAAL, 2019, "Structural Analysis of Smali Language to Enhance Performance of Android Applications", Research Journal-University of Aleppo, Volume 151.
  19. Marwa Dahdouh, Mouhamad Ayman Naal, Souheil Khawatmi, Amer Bouchi, 2019, "Design an Optimized Compiler to Enhance Performance of Android Applications", IJCA.
  20. Xueliang Li, John P. Gallagher, 2015, "A Top-to-Bottom View: Energy Analysis for Mobile Application Source Code", Roskilde University arXiv:1510.04165v1.
  21. Ruben Saborido, Foutse Khomh et al, 2018, "An App Performance Optimization Advisor for Mobile Device App Marketplaces", Sustainable Computing: Informatics and Systems.
  22. Inmaculada Ayala et al, 2019, "An Energy Efficiency Study of Web-Based Communication in Android Phones", Hindawi,Scientific Programming
  23. Yan Hu et al, 2017, "Lightweight Energy Consumption Analysis and Prediction for Android Applications", Science of Computer Programming.
  24. Luis Cruz et al, 2019, "EMaaS: Energy Measurements as a Service for Mobile Applications", IEEE/ACM 41st International Conference on Software Engineering.
  25. MOHAMMAD ASHRAFUL HOQUE et al, 2015, "Modeling, Profiling, and Debugging the Energy Consumption of Mobile Devices", ACM.
  26. Ding Li, Shuai Hao, William G.J. Halfond, Ramesh Govindan, 2013, "Calculating Source Line Level Energy Information for Android Applications", ACM.
  27. Lide Zhang, Birjodh Tiwana et al, 2010,"Accurate Online Power Estimation and Automatic Battery Behavior Based Power Model Generation for Smartphones", ACM.
  28. Lin-Tao Duan et al, 2013, "Energy analysis and prediction for applications on smartphones", Journal of Systems Architecture.
  29. https://github.com/81813780/AVLoadingIndicatorView/blob/master/apk/app-debug.apk. [Accessed 1/9/2019].
Index Terms

Computer Science
Information Sciences

Keywords

Smali Code Optimization Energy Consumption Power Usage Measurement Optimized Compiler Execution Time.