Abstract
Task offloading from smartphones to the cloud is a promising strategy to enhance the computing capability of smartphones and prolong their battery life. However, task offloading introduces a communication cost for those devices. Therefore, the consideration of the communication cost is crucial for the effectiveness of task offloading. To make task offloading beneficial, one of the challenges is to estimate the energy consumed in communication activities of task offloading. Accurate energy estimation models will enable these devices to make the right decisions as to whether or not to perform task offloading, based on the energy cost of the communication activities. Simply put, if the offloading process consumes less energy than processing the task on the device itself, then the task is offloaded to the cloud. To design an energy-aware offloading strategy, we develop energy models of the WLAN, third-generation, and fourth-generation interfaces of smartphones. These models make smartphones capable of accurately estimating the energy cost of task offloading. We validate the models by conducting an extensive set of experiments on five smartphones from different vendors. The experimental results show that our estimation models accurately estimate the energy required to offload tasks.
Original language | English |
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Article number | 7005449 |
Pages (from-to) | 384-398 |
Number of pages | 15 |
Journal | IEEE Transactions on Emerging Topics in Computing |
Volume | 3 |
Issue number | 3 |
DOIs | |
Publication status | Published - Sept 1 2015 |
Keywords
- 3G Energy
- 4G Energy
- Cloud Computing
- Energy Estimation
- Energy Saving
- Mobile Computing
- Offloading Decision
- Smartphones
- WLAN Energy
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Information Systems
- Human-Computer Interaction
- Computer Science Applications