Title: Energy Efficient Mobile Edge Computing in Dense Cellular Networks,
Abstract: Merging Mobile Edge Computing (MEC), which is an emerging paradigm to meet
the increasing computation demands from mobile devices, with the dense
deployment of Base Stations (BSs), is foreseen as a key step towards the next
generation mobile networks. However, new challenges arise for designing energy
efficient networks since radio access resources and computing resources of BSs
have to be jointly managed, and yet they are complexly coupled with traffic in
both spatial and temporal domains. In this paper, we address the challenge of
incorporating MEC into dense cellular networks, and propose an efficient online
algorithm, called ENGINE (ENErgy constrained offloadINg and slEeping) which
makes joint computation offloading and BS sleeping decisions in order to
maximize the quality of service while keeping the energy consumption low. Our
algorithm leverages Lyapunov optimization technique, works online and achieves
a close-to-optimal performance without using future information. Our simulation
results show that our algorithm can effectively reduce energy consumption
without sacrificing the user quality of service.