Quantum-Enhanced Control of a Tandem Queue System

Controlling computer systems in an optimal way using quantum devices is an important step towards next generation infrastructures that will be able to harness the advantages of quantum computing. While the implications are promising, there is a need for evaluating new such approaches and tools in comparison with prevalent classical alternatives. In this work we contribute in this direction by studying the stabilization and control of a tandem queue system, an exemplary model of a computer system, using model predictive control and quantum annealing. The control inputs are obtained from the minimization of an appropriately constructed cost function and the optimal control problem is converted into a quadratic unconstrained binary optimization problem to be solved by the quantum annealer. We find that as the prediction horizon increases and the core optimization problem becomes complicated, the quantum-enhanced solution is preferable over classical simulated annealing. Moreover, there is a trade-off one should consider in terms of variations in the obtained results, quantum computation times and end-to-end communication times. This work shows a way for further experimentation and exploration of new directions and challenges and underscores the experience gained through utilization of the state-of-the-art quantum devices.