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Virtual machine live migration in cloud environments aims at reducing energycosts and increasing resource utilization. However, its potential has not beenfully explored because of simultaneous migrations that may cause userapplication performance degradation and network congestion. Research efforts onlive migration orchestration policies still mostly rely on system levelmetrics. This work introduces an Application-aware Live Migration Architecture(ALMA) that selects suitable moments for migrations using applicationcharacterization data. This characterization consists in recognizing resourceusage cycles via Fast Fourier Transform. From our experiments, live migrationtimes were reduced by up to 74% for benchmarks and by up to 67% for realapplications, when compared to migration policies with no application workloadanalysis. Network data transfer during the live migration was reduced by up to62%.

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