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Improving the Performance of Smartphone Apps with Soft Hang Bug Detection and Dynamic Resource Management

Brocanelli, Marco
http://rave.ohiolink.edu/etdc/view?acc_num=osu1527609496701755

Abstract Details

2018, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.
Two critical quality factors for mobile devices (e.g., smartphones, tablets) are battery life and apps’ user perceived performance. For example, apps that require frequent user actions with the user interface should have high responsiveness, which indicates how fast an app reacts to user actions. On the other hand, apps used mostly for video/music play should have a high throughput, which allows for example a video to be played smoothly without perceivable frame rate loss. Two main causes of poor performance for these apps are soft hang bugs and resource contention. A soft hang bug causes the app to have soft hangs, i.e., the app’s response time of handling a certain user action is longer than a user-perceivable delay. A soft hang bug is a blocking operations that executes on the app's main thread and can be fixed by moving the execution of this operation to a background worker thread. Resource contention can cause concurrent foreground apps to miss their performance target. Indeed, during recent years, the improvements in mobile operating system performance and the increasing display size have brought these resource constrained devices to be able to execute multiple apps at the same time, e.g., watch a video while chatting with a friend. As a result, the resource contention among the apps sharing the screen can either cause performance degradation for at least one of the concurrent apps or cause an unnecessarily high energy consumption. In this dissertation, we first introduce Hang Doctor, a runtime soft hang detection and diagnosis methodology that runs in the wild on user devices. Hang Doctor helps developers track the responsiveness performance of their apps and provides diagnosis information for them to fix soft hangs. Hang Doctor exploits performance event counters to ensure high detection quality and low overhead. In particular, we propose a soft hang filter that examines the performance event counters during the app execution to automatically prune false positives. We have implemented Hang Doctor and tested it with the latest releases of 114 real-world apps. Hang Doctor has found 34 new soft hang bugs previously unknown to their developers. So far, 62% of the bugs have already been confirmed by the developers and 68% are missed by offline detection algorithms. Second, in order to ensure good user-perceived performance of concurrent apps and low energy consumption, we propose SURF, Supervisory control of User-perceived peRFormance. Specifically, first, SURF dynamically balances the performance of the concurrent apps to regulate the resource allocation among the concurrent apps according to their actual performance needs. Then, when the concurrent foreground apps have balanced performance, SURF manipulates CPU DVFS (dynamic voltage and frequency scaling) to ensure that the user-perceived performance of all the apps stay close to their desired values while minimizing the energy consumption. A key advantage of SURF is that it is designed rigorously based on supervisory control theory, which provides analytical stability and performance guarantees compared to heuristic solutions. We test SURF on several mobile device models with real-world open-source apps and show that it can reduce the CPU energy consumption by 30-90% compared to state-of-the-art solutions while causing no perceivable performance degradation.
Xiaorui Wang (Advisor)
Feng Qin (Committee Member)
Christopher Stewart (Committee Member)
109 p.
Computer Engineering
mobile devices; energy consumption; user-perceived performance; resource concurrency; soft hang bugs

Recommended Citations

Citations

  • Brocanelli, M. (2018). Improving the Performance of Smartphone Apps with Soft Hang Bug Detection and Dynamic Resource Management [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1527609496701755

    APA Style (7th edition)

  • Brocanelli, Marco. Improving the Performance of Smartphone Apps with Soft Hang Bug Detection and Dynamic Resource Management. 2018. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1527609496701755.

    MLA Style (8th edition)

  • Brocanelli, Marco. "Improving the Performance of Smartphone Apps with Soft Hang Bug Detection and Dynamic Resource Management." Doctoral dissertation, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1527609496701755

    Chicago Manual of Style (17th edition)

osu1527609496701755
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This open access ETD is published by The Ohio State University and OhioLINK.
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