Many-Sources Large Deviations for Max-Weight Scheduling

作者:Subramanian Vijay G*; Javidi Tara; Kittipiyakul Somsak
来源:IEEE Transactions on Information Theory, 2011, 57(4): 2151-2168.
DOI:10.1109/TIT.2011.2110850

摘要

In this paper, a many-sources large deviations principle (LDP) for the transient workload of a multiqueue single-server system is established where the service rates are chosen from a compact, convex, and coordinate-convex rate region and where the service discipline is the max-weight policy. Under the assumption that the arrival processes satisfy a many-sources LDP, this is accomplished by employing Garcia's extended contraction principle that is applicable to quasi-continuous mappings. For the traditional single-server queue (simplex rate-region), an LDP for the stationary workload is also established under the additional requirements that the scheduling policy be work-conserving and that the arrival processes satisfy certain mixing conditions. The LDP results can be used to calculate asymptotic buffer overflow probabilities accounting for the multiplexing gain, e. g., when the arrival process is an average of i.i.d. processes. The rate function for the stationary workload is expressed in term of the rate functions of the finite-horizon workloads when the arrival processes have i.i.d. increments.

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