Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Cellular data network infrastructure characterization and implication on mobile content placement
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Catch me if you can: performance bug detection in the wild
Proceedings of the 2011 ACM international conference on Object oriented programming systems languages and applications
Full-system analysis and characterization of interactive smartphone applications
IISWC '11 Proceedings of the 2011 IEEE International Symposium on Workload Characterization
ADEL: an automatic detector of energy leaks for smartphone applications
Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Revisiting storage for smartphones
ACM Transactions on Storage (TOS)
AppInsight: mobile app performance monitoring in the wild
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
Carat: collaborative energy diagnosis for mobile devices
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
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Improving and optimizing user-perceived smartphone performance requires understanding device, system, and application behavior for real-world workloads. However, measuring such performance is challenging due to the multi-threaded, asynchronous programming paradigms used in modern applications and the multiple layers of hardware and software used to respond to user input events. We address this challenge with Panappticon, a lightweight, system-wide, fine-grained event tracing system for Android that automatically identifies critical execution paths in user transactions. Panappticon monitors the application, system, and kernel software layers and can identify performance problems stemming from application design flaws, underpowered hardware, and harmful interactions between apparently unrelated applications. We carried out a 14-user, one-month study of an Android smartphone system instrumented with Panappticon, which revealed a number of specific problems and areas for improvement that may be of interest to system designers, application developers, and device manufactures.