TY - GEN
T1 - CoSmart
T2 - 14th IEEE International Conference on Autonomic Computing, ICAC 2017
AU - Zheng, Kuangyu
AU - Beitman, Bruce
AU - Wang, Xiaorui
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/8
Y1 - 2017/8/8
N2 - Due to the increasing popularity of smartphones, many people are now equipped with both a smartphone and at least one desktop (or laptop) computer. Although the two computing devices are used for similar purposes (e.g., email, web browsing), they are often both kept on for the user's convenience, despite only one device is actively used at a time. Therefore, if one of the two computing devices can be put into an energy-saving mode when the other one is in use, a significant amount of energy can be saved for both the phone and the desktop.In this paper, we propose CoSmart, a light-weight solution that coordinates the smartphone with the desktop computer for joint energy savings. CoSmart dynamically degrades the smartphone to a feature phone with only basic GSM functions when the user is detected to be with the desktop, in order to save both computation and idle energy. The desktop is then put into sleep for energy savings when the user leaves it, while the phone can be turned back to a smartphone, such that the user can continue the operation with seamless task migration. There are several research challenges in the design of CoSmart, which include 1) predicting whether the user would stay long enough with the desktop to offset the migration overheads, and 2) determining the best time point for task migration that can result in the most energy savings. To this end, we propose a novel algorithm for dynamic idle time length prediction, and model joint energy savings as an optimization problem for the most energy savings. A prototype of CoSmart is implemented in Android and evaluated using different real user traces and popular apps. Results show CoSmart can achieve, on average, 61.3% energy savings for the smartphone and 46.7% energy savings for the desktop, which outperforms other baselines by as much as 17.2% to 19.0%.
AB - Due to the increasing popularity of smartphones, many people are now equipped with both a smartphone and at least one desktop (or laptop) computer. Although the two computing devices are used for similar purposes (e.g., email, web browsing), they are often both kept on for the user's convenience, despite only one device is actively used at a time. Therefore, if one of the two computing devices can be put into an energy-saving mode when the other one is in use, a significant amount of energy can be saved for both the phone and the desktop.In this paper, we propose CoSmart, a light-weight solution that coordinates the smartphone with the desktop computer for joint energy savings. CoSmart dynamically degrades the smartphone to a feature phone with only basic GSM functions when the user is detected to be with the desktop, in order to save both computation and idle energy. The desktop is then put into sleep for energy savings when the user leaves it, while the phone can be turned back to a smartphone, such that the user can continue the operation with seamless task migration. There are several research challenges in the design of CoSmart, which include 1) predicting whether the user would stay long enough with the desktop to offset the migration overheads, and 2) determining the best time point for task migration that can result in the most energy savings. To this end, we propose a novel algorithm for dynamic idle time length prediction, and model joint energy savings as an optimization problem for the most energy savings. A prototype of CoSmart is implemented in Android and evaluated using different real user traces and popular apps. Results show CoSmart can achieve, on average, 61.3% energy savings for the smartphone and 46.7% energy savings for the desktop, which outperforms other baselines by as much as 17.2% to 19.0%.
UR - https://www.scopus.com/pages/publications/85034450883
U2 - 10.1109/ICAC.2017.14
DO - 10.1109/ICAC.2017.14
M3 - 会议稿件
AN - SCOPUS:85034450883
T3 - Proceedings - 2017 IEEE International Conference on Autonomic Computing, ICAC 2017
SP - 167
EP - 176
BT - Proceedings - 2017 IEEE International Conference on Autonomic Computing, ICAC 2017
A2 - Wang, Xiaorui
A2 - Lei, Hui
A2 - Stewart, Christopher
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 July 2017 through 21 July 2017
ER -