Energy-Efficient Orchestration of Metro-Scale 5G Radio Access Networks

RAN energy consumption is a major OPEX source
for mobile telecom operators, and 5G is expected to increase these
costs by several folds. Moreover, paradigm-shifting aspects of the
5G RAN architecture like RAN disaggregation, virtualization and
cloudification introduce new traffic-dependent resource manage-
ment decisions that make the problem of energy-efficient 5G RAN
orchestration harder. To address such a challenge, we present a
first comprehensive virtualized RAN (vRAN) system model aligned
with 5G RAN specifications, which embeds realistic and dynamic
models for computational load and energy consumption costs. We
then formulate the vRAN energy consumption optimization as an
integer quadratic programming problem, whose NP-hard nature
leads us to develop GreenRAN, a novel, computationally efficient
and distributed solution that leverages Lagrangian decomposition
and simulated annealing. Evaluations with real-world mobile
traffic data for a large metropolitan area are another novel aspect
of this work, and show that our approach yields energy efficiency
gains up to 25% and 42%, over state-of-the-art and baseline
traditional RAN approaches, respectively