Abstract
In recent years Machine Learning techniques have proven to reduce energy consumption when applied to cloud computing systems. Reinforcement Learning provides a promising solution for the reduction of energy consumption, while maintaining a high quality of service for customers. We present a novel single agent Reinforcement Learning approach for the selection of virtual machines, creating a new energy efficiency practice for data centres. Our dynamic Reinforcement Learning virtual machine selection policy learns to choose the optimal virtual machine to migrate from an over-utilised host. Our experiment results show that a learning agent has the abilities to reduce energy consumption and decrease the number of migrations when compared to a state-of-the-art approach.
| Original language | English (Ireland) |
|---|---|
| Title of host publication | A Reinforcement Learning Approach for Dynamic Selection of Virtual Machines in Cloud Data Centres |
| Number of pages | 6 |
| Publication status | Published - 1 Jan 2016 |
Authors (Note for portal: view the doc link for the full list of authors)
- Authors
- Duggan, M,Flesk, K,Duggan, J,Howley, E,Barrett, E,