Time-dependent priority disciplines: A heavy traffic analysis

Carra, Damiano; Michiardi, Pietro
Research Report RR-11-251

heavy traffic





regime, and derive closed form expressions to evaluate the relativefinite buffers for both


difference - in terms of average waiting times - of requests that belong


to different priority classes.


Our analysis allows to derive the expected waiting time of requests in single


server queueing systems, under the assumption of


non-preemptive and preemptive cases. Additionally, we extend our results to


a distributed scenario composed of an interconnected set of a large number


of unreliable single server queueing systems.


We then describe a number of applications and illustrate how to use our


theoretic foundation to analyze and tune their performance. The accuracy of


our analysis is validated through a set of experiments that we performed in a


synthetic setting.




In this work, we revisit the theory underlying a range of time-dependent


priority disciplines, and extend it to include the requirements of a class of


applications that has not been studied in the past. Specifically, we target applications


and services in which a scarce resource, or a fraction thereof, has


to be awarded to a large number of concurrent requests. We thus consider an

Data Science
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