  The convergence of communication and computing has lead to the emergence of
Multi-access Edge Computing (MEC), where computing resources (supported by
Virtual Machines (VMs)) are distributed at the edge of the Mobile Network (MN),
i.e., in Base Stations (BSs), with the aim of ensuring reliable and ultra-low
latency services. Moreover, BSs equipped with Energy Harvesting (EH) systems
can decrease the amount of energy drained from the power grid resulting in
energetically self-sufficient MNs. The combination of these paradigms is
considered here. Specifically, we propose an online optimization algorithm,
called ENergy Aware and Adaptive Management (ENAAM), based on foresighted
control policies exploiting (short-term) traffic load and harvested energy
forecasts, where BSs and VMs are dynamically switched on/off towards energy
savings and QoS provisioning. Our numerical results reveal that ENAAM achieves
energy savings with respect to the case where no energy management is applied,
ranging from 57% and 69%. Moreover, the extension of ENAAM within a cluster of
BSs provides a further gain ranging from 9% to 16% in energy savings with
respect to the optimization performed in isolation for each BS.
