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Lightweight measurement and estimation of mobile ad energy consumption
| Content Provider | ACM Digital Library |
|---|---|
| Author | Li, Ding Gui, Jiaping Halfond, William G. J. Wan, Mian |
| Abstract | Mobile ads are an important component of the app ecosystem. Typically, developers use ads to generate revenue and, in return, end users get a "free" app. However, recent work has shown that apps with ads actually have significant hidden costs to end users in terms of energy, network usage, and performance. These can affect the ratings and reviews an app receives. Therefore, it is desirable for developers to balance the usage of ads with these potential negative costs. However, for energy, developers lack techniques to help them measure ad costs to their apps. To address this problem, we propose and evaluate several lightweight statistical approaches for measuring and predicting ad related energy consumption. We evaluate our approaches on real-world market apps and find that they are able to accurately and quickly estimate the energy cost without requiring expensive infrastructure or extensive developer effort. |
| Starting Page | 1 |
| Ending Page | 7 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781450341615 |
| DOI | 10.1145/2896967.2896970 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-05-14 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
