Virtual Machine Placement Method with Compressed Sensing-Based Traffic Volume Estimation

In a cloud computing environment, a virtual machine placement (VMP) problem is considered for traffic load balancing, where each VM is placed on a physical host according to traffic loads in the physical hosts. In particular, VM is referred to as a node and a pair of nodes is considered a flow. To a...

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Bibliographic Details
Main Authors: Yamamoto, Ami, Yumoto, Kenta, Matsuda, Takahiro, Higuchi, Junichi, Kodama, Takeshi, Ueno, Hitoshi, Shiraishi, Takashi
Format: Conference Proceeding
Language:English
Subjects:
Cloud computing
compressed sensing
Load management
Optimization
Sensors
Telecommunication traffic
traffic volume estimation
virtual machine
Virtual machining
VM placement
Volume measurement
Online Access:Request full text
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Summary:In a cloud computing environment, a virtual machine placement (VMP) problem is considered for traffic load balancing, where each VM is placed on a physical host according to traffic loads in the physical hosts. In particular, VM is referred to as a node and a pair of nodes is considered a flow. To achieve load balancing, identifying flows that transfer heavy traffic volumes is necessary. We propose a VMP method with compressed sensing (CS)-based traffic volume estimation. In the proposed method, all flow traffic volumes are estimated by CS from the traffic volumes that nodes transmit and receive. VMs are placed according to the estimated flow traffic volumes by solving a combinatorial optimization problem. We validate the proposed method via simulation experiments.
ISSN:2575-8284
DOI:10.1109/ICCE-Taiwan58799.2023.10226756