TY - GEN
T1 - Enhancing mobile apps to use sensor hubs without programmer effort
AU - Shen, Haichen
AU - Balasubramanian, Aruna
AU - Lamarca, Anthony
AU - Wetherall, David
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/9/7
Y1 - 2015/9/7
N2 - Always-on continuous sensing apps drain the battery quickly because they prevent the main processor from sleeping. Instead, sensor hub hardware, available in many smartphones today, can run continuous sensing at lower power while keeping the main processor idle. However, developers have to divide functionality between the main processor and the sensor hub. We implement MobileHub, a system that automatically rewrites applications to leverage the sensor hub without additional programming effort. MobileHub uses a combination of dynamic taint tracking and machine learning to learn when it is safe to leverage the sensor hub without affecting application semantics. We implement MobileHub in Android and prototype a sensor hub on a 8-bit AVR micro-controller. We experiment with 20 applications from Google Play. Our evaluation shows that MobileHub significantly reduces power consumption for continuous sensing apps.
AB - Always-on continuous sensing apps drain the battery quickly because they prevent the main processor from sleeping. Instead, sensor hub hardware, available in many smartphones today, can run continuous sensing at lower power while keeping the main processor idle. However, developers have to divide functionality between the main processor and the sensor hub. We implement MobileHub, a system that automatically rewrites applications to leverage the sensor hub without additional programming effort. MobileHub uses a combination of dynamic taint tracking and machine learning to learn when it is safe to leverage the sensor hub without affecting application semantics. We implement MobileHub in Android and prototype a sensor hub on a 8-bit AVR micro-controller. We experiment with 20 applications from Google Play. Our evaluation shows that MobileHub significantly reduces power consumption for continuous sensing apps.
KW - Dynamic taint tracking
KW - Energy-efficiency
KW - Machine learning
KW - Mobile sensing
KW - Sensor hub
UR - https://www.scopus.com/pages/publications/84960940771
U2 - 10.1145/2750858.2804260
DO - 10.1145/2750858.2804260
M3 - Conference contribution
AN - SCOPUS:84960940771
T3 - UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
SP - 227
EP - 238
BT - UbiComp 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PB - Association for Computing Machinery, Inc
T2 - 3rd ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2015
Y2 - 7 September 2015 through 11 September 2015
ER -