Multi-objective dynamic virtual machine consolidation in the cloud using ant colony system

TL;DR

This paper introduces a multi-objective ant colony system algorithm for VM consolidation in cloud data centers, aiming to maximize physical machine release while minimizing migrations, and demonstrates its superior performance over existing methods.

Contribution

It presents a novel multi-objective ant colony algorithm specifically designed for VM consolidation, optimizing multiple goals simultaneously in cloud environments.

Findings

Outperforms existing ant colony algorithms in PM release

Reduces number of VM migrations

Provides efficient VM consolidation solutions

Abstract

In this paper, we present a novel multi-objective ant colony system algorithm for virtual machine (VM) consolidation in cloud data centers. The proposed algorithm builds VM migration plans, which are then used to minimize over-provisioning of physical machines (PMs) by consolidating VMs on under-utilized PMs. It optimizes two objectives that are ordered by their importance. The first and foremost objective in the proposed algorithm is to maximize the number of released PMs. Moreover, since VM migration is a resource-intensive operation, it also tries to minimize the number of VM migrations. The proposed algorithm is empirically evaluated in a series of experiments. The experimental results show that the proposed algorithm provides an efficient solution for VM consolidation in cloud data centers. Moreover, it outperforms two existing ant colony optimization based VM consolidation algorithms in terms of number of released PMs and number of VM migrations.