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On death, taxes, and sleep disorder bugs in smartphones

Published: 03 November 2013 Publication History

Abstract

According to Benjamin Franklin, life holds but two certainties, death and taxes. As we enter the mobile era, the primary mobile device, i.e., the smartphone, faces the certainties of adopting agressive sleeping polices to conserve battery energy, requiring programmers to use explicit power control APIs to keep the SOC/CPU on, and a third certainty that unavoidably rises from these: sleep disorder bugs.
In this paper, we articulate the fate and destiny of smartphone apps, sleep disorder bugs, as a critical technical challenge in the mobile era. We then present a taxonomy of sleep disorder bugs, and a categorization of time-critical sections which are the root cause of sleep disorders, in apps, framework services and the Android kernel. Finally, we present a unified system for detecting the spectrum of sleep disorder bugs.

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cover image ACM Conferences
HotPower '13: Proceedings of the Workshop on Power-Aware Computing and Systems
November 2013
66 pages
ISBN:9781450324588
DOI:10.1145/2525526
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 November 2013

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HotPower '13 Paper Acceptance Rate 13 of 38 submissions, 34%;
Overall Acceptance Rate 20 of 50 submissions, 40%

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  • (2021)ExperienceProceedings of the 27th Annual International Conference on Mobile Computing and Networking10.1145/3447993.3483269(804-815)Online publication date: 25-Oct-2021
  • (2019)Security of Emergent Automotive Systems: A Tutorial Introduction and Perspectives on PracticeIEEE Design & Test10.1109/MDAT.2019.294408636:6(10-38)Online publication date: Dec-2019
  • (2019)iPerfDetector: Characterizing and detecting performance anti-patterns in iOS applicationsEmpirical Software Engineering10.1007/s10664-019-09703-y24:6(3484-3513)Online publication date: 17-Apr-2019
  • (2017)Bug Analysis of Android Applications Based on JPFSmart Computing and Communication10.1007/978-3-319-52015-5_18(173-182)Online publication date: 13-Jan-2017
  • (2016)User Intent-Oriented Video QoE with Emotion Detection Networking2016 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOCOM.2016.7842364(1-6)Online publication date: Dec-2016
  • (2016)Silent Battery Draining Attack against Android Systems by Subverting Doze Mode2016 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOCOM.2016.7842268(1-6)Online publication date: Dec-2016
  • (2015)Energy-Efficiency Comparison of Mobile Platforms and ApplicationsProceedings of the 16th International Workshop on Mobile Computing Systems and Applications10.1145/2699343.2699358(39-44)Online publication date: 12-Feb-2015
  • (2015)Andro LyzeProceedings of the 2015 IEEE International Conference on Mobile Services10.1109/MobServ.2015.20(73-80)Online publication date: 27-Jun-2015

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