  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%.
