Balancing performance, resource efficiency and energy efficiency for virtual machine deployment in DVFS-enabled clouds: an evolutionary game theoretic approach.

This paper proposes and evaluates a multiobjective evolutionary game theoretic framework for adaptive and stable application deployment in clouds that support dynamic voltage and frequency scaling (DVFS) for CPUs. The proposed framework, called Cielo, aids cloud operators to adapt the resource allocation to applications and their locations according to the operational conditions in a cloud (e.g., workload and resource availability) with respect to multiple conflicting objectives such as response time performance, recourse utilization and power consumption. Moreover, Cielo theoretically guarantees that each application performs an evolutionarily stable deployment strategy, which is an equilibrium solution under given operational conditions. Simulation results verify this theoretical analysis; applications seek equilibria to perform adaptive and evolutionarily stable deployment strategies. Cielo allows applications to successfully leverage DVFS to balance their response time performance, resource utilization and power consumption.