Model-based Energy Consumption Prediction for Mobile Application
| dc.contributor.author | Willnecker, Felix | |
| dc.contributor.author | Brunnert, Andreas | |
| dc.contributor.author | Krcmar, Helmut | |
| dc.contributor.editor | Gómez, Jorge Marx | |
| dc.contributor.editor | Sonnenschein, Michael | |
| dc.contributor.editor | Vogel, Ute | |
| dc.contributor.editor | Winter, Andreas | |
| dc.contributor.editor | Rapp, Barbara | |
| dc.contributor.editor | Giesen, Nils | |
| dc.date.accessioned | 2019-09-16T03:13:07Z | |
| dc.date.available | 2019-09-16T03:13:07Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | Investigating the energy consumption of mobile applications (apps) is becoming a growing software engineering challenge due to the limited battery lifetime of mobile devices. Energy consumption is defined as the power demand integrated over time. Profiling the power demand of an app is a time consuming activity and the results are only valid for the target hardware used during the measurements. The energy consumption is influenced by the resource demands of an app, the hardware on which the app is running, and its workload. This work adapts resource profiles for enterprise applications to predict the energy consumption of mobile apps without the need to own a physical device. Resource profiles are models that represent all aspects influencing the energy consumption of an app. They can be used to predict the energy consumption for different hardware devices and evaluate the overall efficiency of an app. Moreover, the workload can be changed so that the impact of different usage patterns can be investigated. These capabilities lay the foundation for a platform-independent way of quantifying the energy consumption of mobile apps | de |
| dc.description.uri | http://enviroinfo.eu/sites/default/files/pdfs/vol8514/0747.pdf | de |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/25805 | |
| dc.publisher | BIS-Verlag | |
| dc.relation.ispartof | Proceedings of the 28th Conference on Environmental Informatics - Informatics for Environmental Protection, Sustainable Development and Risk Management | |
| dc.relation.ispartofseries | EnviroInfo | |
| dc.title | Model-based Energy Consumption Prediction for Mobile Application | de |
| dc.type | Text/Conference Paper | |
| gi.citation.publisherPlace | Oldenburg | |
| gi.conference.date | 2014 | |
| gi.conference.location | Oldenburg | |
| gi.conference.sessiontitle | Workshop Energy Aware Software Development |