Optimal Feature Selection from VMware ESXi 5.1 Feature Set

TL;DR

This paper applies feature selection and clustering algorithms to identify optimal resource parameters in VMware ESXi 5.1 servers, enhancing resource management for multiple virtual machines.

Contribution

It introduces a method combining feature selection and clustering indices to determine optimal server parameters in VMware ESXi 5.1 environments.

Findings

Optimal feature set identified for VMware ESXi 5.1

Clustering effectively groups VMs based on resource usage

Indices guide selection of best resource configuration

Abstract

A study of VMware ESXi 5.1 server has been carried out to find the optimal set of parameters which suggest usage of different resources of the server. Feature selection algorithms have been used to extract the optimum set of parameters of the data obtained from VMware ESXi 5.1 server using esxtop command. Multiple virtual machines (VMs) are running in the mentioned server. K-means algorithm is used for clustering the VMs. The goodness of each cluster is determined by Davies Bouldin index and Dunn index respectively. The best cluster is further identified by the determined indices. The features of the best cluster are considered into a set of optimal parameters.