Detecting display energy hotspots in Android apps

被引:15
|
作者
Wan, Mian [1 ]
Jin, Yuchen [1 ]
Li, Ding [1 ]
Gui, Jiaping [1 ]
Mahajan, Sonal [1 ]
Halfond, William G. J. [1 ]
机构
[1] Univ Southern Calif, Dept Comp Sci, Los Angeles, CA 90089 USA
来源
基金
美国国家科学基金会;
关键词
display; energy; mobile applications; optimization; power; GRAPHICAL USER INTERFACES; MOBILE APPLICATIONS; POWER ESTIMATION; IMPACT; CONSUMPTION;
D O I
10.1002/stvr.1635
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The energy consumption of mobile apps has become an important consideration for developers as the underlying mobile devices are constrained by battery capacity. Display represents a significant portion of an app's energy consumptionup to 60% of an app's total energy consumption. However, developers lack techniques to identify the user interfaces in their apps for which energy needs to be improved. This paper presents a technique for detecting display energy hotspotsuser interfaces of a mobile app whose energy consumption is greater than optimal. The technique leverages display power modeling and automated display transformation techniques to detect these hotspots and prioritize them for developers. The evaluation of the technique shows that it can predict display energy consumption to within 14% of the ground truth and accurately rank display energy hotspots. Furthermore, the approach found 398 display energy hotspots in a set of 962 popular Android apps, showing the pervasiveness of this problem. For these detected hotspots, the average power savings that could be realized through better user interface design was 30%. Taken together, these results indicate that the approach represents a potentially impactful technique for helping developers to detect energy related problems and reduce the energy consumption of their mobile apps.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Detecting Display Energy Hotspots in Android Apps
    Wan, Mian
    Jin, Yuchen
    Li, Ding
    Halfond, William G. J.
    [J]. 2015 IEEE 8TH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION (ICST), 2015,
  • [2] Detecting Energy Bugs and Hotspots in Mobile Apps
    Banerjee, Abhijeet
    Chong, Lee Kee
    Chattopadhyay, Sudipta
    Roychoudhury, Abhik
    [J]. 22ND ACM SIGSOFT INTERNATIONAL SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (FSE 2014), 2014, : 588 - 598
  • [3] Detecting Antipatterns in Android Apps
    Hecht, Geoffrey
    Rouvoy, Romain
    Moha, Naouel
    Duchien, Laurence
    [J]. 2ND ACM INTERNATIONAL CONFERENCE ON MOBILE SOFTWARE ENGINEERING AND SYSTEMS MOBILESOFT 2015, 2015, : 148 - 149
  • [4] Detecting Energy Bugs in Android Apps Using Static Analysis
    Jiang, Hao
    Yang, Hongli
    Qin, Shengchao
    Su, Zhendong
    Zhang, Jian
    Yan, Jun
    [J]. FORMAL METHODS AND SOFTWARE ENGINEERING, ICFEM 2017, 2017, 10610 : 192 - 208
  • [5] Detecting Connectivity Issues in Android Apps
    Mazuera-Rozo, Alejandro
    Escobar-Velasquez, Camilo
    Espitia-Acero, Juan
    Linares-Vasquez, Mario
    Bavota, Gabriele
    [J]. 2022 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION AND REENGINEERING (SANER 2022), 2022, : 697 - 708
  • [6] On Automatically Detecting Similar Android Apps
    Linares-Vasquez, Mario
    Holtzhauer, Andrew
    Poshyvanyk, Denys
    [J]. 2016 IEEE 24TH INTERNATIONAL CONFERENCE ON PROGRAM COMPREHENSION (ICPC), 2016,
  • [7] Display of Major Risk Categories for Android Apps
    Chen, Jing
    Ge, Huangyi
    Moore, Scott
    Yang, Weining
    Li, Ninghui
    Proctor, Robert W.
    [J]. JOURNAL OF EXPERIMENTAL PSYCHOLOGY-APPLIED, 2018, 24 (03) : 306 - 330
  • [8] Detecting and Measuring Misconfigured Manifests in Android Apps
    Yang, Yuqing
    Elsabagh, Mohamed
    Zuo, Chaoshun
    Johnson, Ryan
    Stavrou, Angelos
    Lin, Zhiqiang
    [J]. Proceedings of the ACM Conference on Computer and Communications Security, 2022, : 3063 - 3077
  • [9] Defining and Detecting Environment Discrimination in Android Apps
    Hong, Yunfeng
    Hu, Yongjian
    Lai, Chun-Ming
    Wu, S. Felix
    Neamtiu, Iulian
    McDaniel, Patrick
    Yu, Paul
    Cam, Hasan
    Ahn, Gail-Joon
    [J]. SECURITY AND PRIVACY IN COMMUNICATION NETWORKS, SECURECOMM 2017, 2018, 238 : 510 - 529
  • [10] Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers
    Wang, Wei
    Li, Yuanyuan
    Wang, Xing
    Liu, Jiqiang
    Zhang, Xiangliang
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 78 : 987 - 994