  The rapid cloud computing growth has turned data center energy consumption
into a global problem. At the same time, modern cloud providers operate
multiple geographically-distributed data centers. Distributed data center
infrastructure changes the rules of cloud control, as energy costs depend on
current regional electricity prices and temperatures. Furthermore, to account
for emerging technologies surrounding the cloud ecosystem, a maintainable
control solution needs to be forward-compatible. Existing cloud controllers are
focused on VM consolidation methods suitable only for a single data center or
consider migration just in case of workload peaks, not accounting for all the
aspects of geographically distributed data centers. In this paper, we propose a
pervasive cloud controller for dynamic resource reallocation adapting to
volatile time- and location-dependent factors, while considering the QoS impact
of too frequent migrations and the data quality limits of time series
forecasting methods. The controller is designed with extensible decision
support components. We evaluate it in a simulation using historical traces of
electricity prices and temperatures. By optimising for these additional
factors, we estimate 28.6% energy cost savings compared to baseline dynamic VM
consolidation. We provide a range of guidelines for cloud providers, showing
the environment conditions necessary to achieve significant cost savings and we
validate the controller's extensibility.
