  The digital transformation that Telecommunications and ICT domains are
crossing today, is posing several new challenges to Telecom Operators. These
challenges require solving complex problems such as: dimensioning and
scheduling of virtual/real resources in data centers; automating real-time
management/control and orchestration of networks processes; optimizing energy
consumption; and overall, ensuring networks and services stability. These
problems are usually tackled with methods and algorithms that find suboptimal
solutions, for computational efficiency reasons. In this work, we consider a
Virtual Data Center scenario where virtual machine consolidation must be
performed with joint minimization of network/servers power consumption. For
this scenario, we provide an ILP model, the equivalent binary model and the
steps towards the equivalent Quadratic Unconstrained Binary Optimization (QUBO)
model that is suitable for being solved by means of quantum optimization
algorithms. Finally, we compare the computational complexity of classical and
quantum solvers from a theoretical perspective.
