  5G networks are expected to be highly energy efficient, with a 10 times lower
consumption than today's systems. An effective way to achieve such a goal is to
act on the backhaul network by controlling the nodes operational state and the
allocation of traffic flows. To this end, in this paper we formulate
energy-efficient flow routing on the backhaul network as an optimization
problem. In light of its complexity, which impairs the solution in large-scale
scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims
to both turn off idle nodes and concentrate traffic on the smallest possible
set of links, which in its turn increases the number of idle nodes. We
implement EMMA on top of ONOS and derive experimental results by emulating the
network through Mininet. Our results show that EMMA provides excellent energy
saving performance, which closely approaches the optimum. In larger network
scenarios, the gain in energy consumption that EMMA provides with respect to
the simple benchmark where all nodes are active, is extremely high, reaching
almost 1 under medium-low traffic load.
