Abstract. This paper continues the development of policy synthesis techniques for large processing networks based upon a linear
uid model. It is shown that (i) A relaxation of the
uid model based on workload leads to an optimization problem of lower dimension. The relaxed control problem admits a pathwise optimal solution in many instances. (ii) A translation to the original
uid model is almost optimal, with vanishing relative error as the network load approaches one. It is pathwise optimal after a short transient period, provided a pathwise optimal solution exists for the relaxed control problem. (iii) A similar translation to the stochastic network model is almost pathwise optimal in heavy trac, again with vanishing relative error. The regret is of order j log(1 )j.
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