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The (ultra-)dense deployment of small-cell base stations (SBSs) endowed withcloud-like computing functionalities paves the way for pervasive mobile edgecomputing (MEC), enabling ultra-low latency and location-awareness for avariety of emerging mobile applications and the Internet of Things. To handlespatially uneven computation workloads in the network, cooperation among SBSsvia workload peer offloading is essential to avoid large computation latency atoverloaded SBSs and provide high quality of service to end users. However,performing effective peer offloading faces many unique challenges in small cellnetworks due to limited energy resources committed by self-interested SBSowners, uncertainties in the system dynamics and co-provisioning of radioaccess and computing services. This paper develops a novel online SBS peeroffloading framework, called OPEN, by leveraging the Lyapunov technique, inorder to maximize the long-term system performance while keeping the energyconsumption of SBSs below individual long-term constraints. OPEN works onlinewithout requiring information about future system dynamics, yet providesprovably near-optimal performance compared to the oracle solution that has thecomplete future information. In addition, this paper formulates a novel peeroffloading game among SBSs, analyzes its equilibrium and efficiency loss interms of the price of anarchy in order to thoroughly understand SBSs' strategicbehaviors, thereby enabling decentralized and autonomous peer offloadingdecision making. Extensive simulations are carried out and show that peeroffloading among SBSs dramatically improves the edge computing performance.

Computation Peer Offloading for Energy-Constrained Mobile Edge Computing in Small-Cell Networks