Exploiting Workload Cycles for Orchestration of Virtual Machine Live Migrations in Clouds

TL;DR

This paper presents ALMA, an application-aware architecture that leverages workload cycle analysis via FFT to optimize VM live migration timing, significantly reducing migration time and network transfer.

Contribution

Introduces ALMA, a novel workload cycle-based approach for orchestrating VM live migrations, improving efficiency by analyzing application resource usage patterns.

Findings

Migration times reduced by up to 74% for benchmarks.

Migration times reduced by up to 67% for real applications.

Network data transfer reduced by up to 62%.

Abstract

Virtual machine live migration in cloud environments aims at reducing energy costs and increasing resource utilization. However, its potential has not been fully explored because of simultaneous migrations that may cause user application performance degradation and network congestion. Research efforts on live migration orchestration policies still mostly rely on system level metrics. This work introduces an Application-aware Live Migration Architecture (ALMA) that selects suitable moments for migrations using application characterization data. This characterization consists in recognizing resource usage cycles via Fast Fourier Transform. From our experiments, live migration times were reduced by up to 74% for benchmarks and by up to 67% for real applications, when compared to migration policies with no application workload analysis. Network data transfer during the live migration was reduced by up to 62%.