Abstract
One of the major challenges that cloud providers face is minimizing power consumption of their data centers. To this point, majority of current research focuses on energy efficient management of resources in the Infrastructure as a Service model and through virtual machine consolidation. However, containers are increasingly gaining popularity and going to be major deployment model in cloud environment and specifically in Platform as a Service. This paper focuses on improving the energy efficiency of servers for this new deployment model by proposing a framework that consolidates containers on virtual machines. We first formally present the container consolidation problem and then we compare a number of algorithms and evaluate their performance against metrics such as energy consumption, Service Level Agreement violations, average container migrations rate, and average number of created virtual machines. Our proposed framework and algorithms can be utilized in a private cloud to minimize energy consumption, or alternatively in a public cloud to minimize the total number of hours the virtual machines leased.
| Original language | English |
|---|---|
| Title of host publication | 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS 2015), 11-13 December 2015, Sydney, N.S.W. |
| Publisher | IEEE |
| Pages | 368-375 |
| Number of pages | 8 |
| ISBN (Print) | 9781509002146 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | IEEE International Conference on Data Science and Data Intensive Systems - Duration: 11 Dec 2015 → … |
Conference
| Conference | IEEE International Conference on Data Science and Data Intensive Systems |
|---|---|
| Period | 11/12/15 → … |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- cloud computing
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