Cell phones as a research platform
Proceedings of the 5th international conference on Mobile systems, applications and services
MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones
Proceedings of the 5th international conference on Mobile systems, applications and services
A survey of platforms for mobile networks research
ACM SIGMOBILE Mobile Computing and Communications Review
Proceedings of the 8th international conference on Mobile systems, applications, and services
A first look at traffic on smartphones
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
AndWellness: an open mobile system for activity and experience sampling
WH '10 Wireless Health 2010
Greening wireless communications: Status and future directions
Computer Communications
ProfileDroid: multi-layer profiling of android applications
Proceedings of the 18th annual international conference on Mobile computing and networking
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
Smartphone applications usability evaluation: a hybrid model and its implementation
HCSE'12 Proceedings of the 4th international conference on Human-Centered Software Engineering
Performance evaluation of android IPC for continuous sensing applications
ACM SIGMOBILE Mobile Computing and Communications Review
Handset-Based Data Collection Process and Participant Attitudes
International Journal of Handheld Computing Research
Pogo, a middleware for mobile phone sensing
Proceedings of the 13th International Middleware Conference
Lifestreams: a modular sense-making toolset for identifying important patterns from everyday life
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
Enabling bring-your-own-device using mobile application instrumentation
IBM Journal of Research and Development
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By deploying several research applications, we found that capturing usage context (e.g., CPU and memory) is highly valuable for debugging and interpreting results, even if that context information appears unrelated to the application. We have developed a general tool called SystemSens to help researchers capture usage context in their deployments in an extendible way. This paper describes and motivates the design choices underlying our tool and evaluates its overheads in terms of phone resources and data.