  Multi-Access Edge Computing (MEC) is a paradigm for handling delay sensitive
services that require ultra-low latency at the access network. With it,
computing and communications are performed within one Base Station (BS) site,
where the computation resources are in the form of Virtual Machines (VMs)
(computer emulators) in the MEC server. MEC and Energy Harvesting (EH) BSs,
i.e., BSs equipped with EH equipments, are foreseen as a key towards
next-generation mobile networks. In fact, EH systems are expected to decrease
the energy drained from the electricity grid and facilitate the deployment of
BSs in remote places, extending network coverage and making energy
self-sufficiency possible in remote/rural sites. In this paper, we propose an
online optimization algorithm called ENergy Aware and Adaptive Management
(ENAAM), for managing remote BS sites through foresighted control policies
exploiting (short-term) traffic load and harvested energy forecasts. Our
numerical results reveal that ENAAM achieves energy savings with respect to the
case where no energy management is applied, ranging from 56% to 66% through the
scaling of computing resources, and keeps the server utilization factor between
30% and 96% over time (with an average of 75%). Notable benefits are also found
against heuristic energy management techniques.
