2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS) (2015)
Dec. 11, 2015 to Dec. 13, 2015
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DSDIS.2015.57
Nowadays enormous amounts of energy are consumed by Cloud infrastructures and this trend is still growing. An existing solution to lower this consumption is to turn off as many servers as possible, but these solutions do not involve the user as a main lever to save energy. We introduce a system that proposes to the user to run her application with degraded performance. A user choosing an energy-efficient run promotes a better consolidation of the Virtual Machines in the Cloud and thus may help turning off more servers. We experimented our system on Grid'5000 and we used the Montage workflow as a benchmark. Experimentation results show promising outcomes. In energy-efficiency mode, the energy consumed can be significantly reduced to the cost of a low increase of the execution time.
Servers, Cloud computing, Energy consumption, Optimization, Biological system modeling, Context, Mathematical model
D. Guyon, A. Orgerie and C. Morin, "Energy-Efficient User-Oriented Cloud Elasticity for Data-Driven Applications," 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS), Sydney, Australia, 2016, pp. 376-383.