Abstract
Cellular network enables pervasive data access, but it also increases the power consumption of smartphones due to the long tail problem, where the cellular interface has to stay in the high-power state for some time after each data transmission. To reduce the tail energy, data that will be used in the future can be prefetched. However, prefetching unnecessary data may waste energy, and this problem becomes worse when the network quality is poor. In this paper, we generalize and formulate the prefetch-based energy optimization problem, where the goal is to find a prefetching schedule that minimizes the energy consumption of the data transmissions under the current network condition. To solve this nonlinear optimization problem, we first propose a greedy algorithm, and then propose a discrete algorithm with better performance. We have implemented and evaluated the proposed algorithms in two apps: in-app advertising and mobile video streaming. Evaluation results show that the proposed algorithms can significantly reduce the energy consumption.
| Original language | English (US) |
|---|---|
| Article number | 8100648 |
| Pages (from-to) | 693-706 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Wireless Communications |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2018 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics
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Prefetch-Based Energy Optimization on Smartphones. / Yang, Yi; Cao, Guohong.
In: IEEE Transactions on Wireless Communications, Vol. 17, No. 1, 8100648, 01.2018, p. 693-706.Research output: Contribution to journal › Article
TY - JOUR
T1 - Prefetch-Based Energy Optimization on Smartphones
AU - Yang, Yi
AU - Cao, Guohong
PY - 2018/1
Y1 - 2018/1
N2 - Cellular network enables pervasive data access, but it also increases the power consumption of smartphones due to the long tail problem, where the cellular interface has to stay in the high-power state for some time after each data transmission. To reduce the tail energy, data that will be used in the future can be prefetched. However, prefetching unnecessary data may waste energy, and this problem becomes worse when the network quality is poor. In this paper, we generalize and formulate the prefetch-based energy optimization problem, where the goal is to find a prefetching schedule that minimizes the energy consumption of the data transmissions under the current network condition. To solve this nonlinear optimization problem, we first propose a greedy algorithm, and then propose a discrete algorithm with better performance. We have implemented and evaluated the proposed algorithms in two apps: in-app advertising and mobile video streaming. Evaluation results show that the proposed algorithms can significantly reduce the energy consumption.
AB - Cellular network enables pervasive data access, but it also increases the power consumption of smartphones due to the long tail problem, where the cellular interface has to stay in the high-power state for some time after each data transmission. To reduce the tail energy, data that will be used in the future can be prefetched. However, prefetching unnecessary data may waste energy, and this problem becomes worse when the network quality is poor. In this paper, we generalize and formulate the prefetch-based energy optimization problem, where the goal is to find a prefetching schedule that minimizes the energy consumption of the data transmissions under the current network condition. To solve this nonlinear optimization problem, we first propose a greedy algorithm, and then propose a discrete algorithm with better performance. We have implemented and evaluated the proposed algorithms in two apps: in-app advertising and mobile video streaming. Evaluation results show that the proposed algorithms can significantly reduce the energy consumption.
UR - http://www.scopus.com/inward/record.url?scp=85033691496&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85033691496&partnerID=8YFLogxK
U2 - 10.1109/TWC.2017.2769646
DO - 10.1109/TWC.2017.2769646
M3 - Article
AN - SCOPUS:85033691496
VL - 17
SP - 693
EP - 706
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
SN - 1536-1276
IS - 1
M1 - 8100648
ER -