  The (ultra-)dense deployment of small-cell base stations (SBSs) endowed with
cloud-like computing functionalities paves the way for pervasive mobile edge
computing (MEC), enabling ultra-low latency and location-awareness for a
variety of emerging mobile applications and the Internet of Things. To handle
spatially uneven computation workloads in the network, cooperation among SBSs
via workload peer offloading is essential to avoid large computation latency at
overloaded SBSs and provide high quality of service to end users. However,
performing effective peer offloading faces many unique challenges in small cell
networks due to limited energy resources committed by self-interested SBS
owners, uncertainties in the system dynamics and co-provisioning of radio
access and computing services. This paper develops a novel online SBS peer
offloading framework, called OPEN, by leveraging the Lyapunov technique, in
order to maximize the long-term system performance while keeping the energy
consumption of SBSs below individual long-term constraints. OPEN works online
without requiring information about future system dynamics, yet provides
provably near-optimal performance compared to the oracle solution that has the
complete future information. In addition, this paper formulates a novel peer
offloading game among SBSs, analyzes its equilibrium and efficiency loss in
terms of the price of anarchy in order to thoroughly understand SBSs' strategic
behaviors, thereby enabling decentralized and autonomous peer offloading
decision making. Extensive simulations are carried out and show that peer
offloading among SBSs dramatically improves the edge computing performance.
