Computation peer offloading for energy-constrained mobile edge computing in small-cell networks



SOURCE  IEEE/ACM Trans. Netw., 2018, 26(4):1619-1632

Published Date:2018-06


The (ultra-)dense deployment of small-cell base
stations (SBSs) endowed with cloud-like computing functionalities
paves the way for pervasive mobile edge computing, 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 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 online peer offloading (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 with the oracle solution that has the complete future
information. In addition, this paper formulates a peer offloading
game among SBSs and analyzes its equilibrium and efficiency
loss in terms of the price of anarchy 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.

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