Machine learning-based power capping and virtual machine placement in cloud platforms

Machine learning-based power capping and virtual machine placement in cloud platforms

Systems and methods for machine learning-based power capping and virtual machine placement in cloud platforms are disclosed. A method includes applying a machine learning model to predict whether a request for deployment of a virtual machine corresponds to deployment of a user-facing (UF) virtual ma...

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Hauptverfasser: Fontoura, Marcus F, Manousakis, Ioannis, Bianchini, Ricardo G, Mahalingam, Nithish, Kumbhare, Alok Gautam, Azimi, Reza
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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creator Fontoura, Marcus F
Manousakis, Ioannis
Bianchini, Ricardo G
Mahalingam, Nithish
Kumbhare, Alok Gautam
Azimi, Reza
description Systems and methods for machine learning-based power capping and virtual machine placement in cloud platforms are disclosed. A method includes applying a machine learning model to predict whether a request for deployment of a virtual machine corresponds to deployment of a user-facing (UF) virtual machine or a non-user-facing (NUF) virtual machine. The method further includes sorting a list of candidate servers based on both a chassis score and a server score for each server to determine a ranked list of the candidate servers, where the server score depends at least on whether the request for the deployment of the virtual machine is determined to be a request for a deployment of a UF virtual machine or a request for a deployment of an NUF virtual machine. The method further includes deploying the virtual machine to a server with highest rank among the ranked list of the candidate servers.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
title Machine learning-based power capping and virtual machine placement in cloud platforms
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