  The control of large queueing networks is a notoriously difficult problem.
Recently, an interesting new policy design framework for the control problem
called h-MaxWeight has been proposed: h-MaxWeight is a natural generalization
of the famous MaxWeight policy where instead of the quadratic any other
surrogate value function can be applied. Stability of the policy is then
achieved through a perturbation technique. However, stability crucially depends
on parameter choice which has to be adapted in simulations. In this paper we
use a different technique where the required perturbations can be directly
implemented in the weight domain, which we call a scheduling field then.
Specifically, we derive the theoretical arsenal that guarantees universal
stability while still operating close to the underlying cost criterion.
Simulation examples suggest that the new approach to policy synthesis can even
provide significantly higher gains irrespective of any further assumptions on
the network model or parameter choice.
