Robustness of threshold policies in beneficiary-donor model

Abstract

A common problem in multiserver systems is deciding how to allocate resources among jobs so as to minimize mean response time. Since good parameter settings typically depend on environmental conditions such as system loads, an allocation policy that is optimal in one environment may provide poor performance when the environment changes, or when the prediction of the environment is wrong. We say that such a policy is not robust. In this paper, we analytically compare the robustness of several threshold-based allocation policies, in a dual server beneficiary-donor model. We introduce two types of robustness: static robustness , which measures robustness against mis-estimation of the true load, and dynamic robustness , which measures robustness against fluctuations in the load. We find that policies employing multiple thresholds offer significant benefit over single threshold policies with respect to static robustness. Yet they surprisingly offer much less benefit with respect to dynamic robustness.