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Quick-release Fair Scheduling James H. Anderson, Aaron Block, and Anand Srinivasan
 

Summary: Quick-release Fair Scheduling
James H. Anderson, Aaron Block, and Anand Srinivasan
Department of Computer Science
University of North Carolina at Chapel Hill
Abstract
In prior work on multiprocessor fairness, efficient techniques with provable properties for reallocating spare
processing capacity have been elusive. In this paper, we address this shortcoming by proposing a new notion of
multiprocessor fairness, called quick-release fair (QRfair) scheduling, which is a derivative of Pfair scheduling
that allows efficient allocation of spare capacity. Under QRfair scheduling, each task is specified by giving
both a minimum and a maximum weight (i.e., processor share). The goal is to schedule each task (as the
available spare capacity changes) at a rate that is (i) at least that implied by its minimum weight and (ii) at
most that implied by its maximum weight. Our contributions are fourfold. First, we present a quick-release
variant of the PD2
Pfair scheduling algorithm called PDQ
. Second, we formally prove that the allocations
of PDQ
always satisfy (i) and (ii). Third, we consider the problem of defining maximum weights in a way
that encourages a fair distribution of spare capacity. Fourth, we present results from extensive simulation
experiments that show the efficacy of PDQ
in allocating spare capacity.

  

Source: Anderson, James - Department of Computer Science, University of North Carolina at Chapel Hill

 

Collections: Computer Technologies and Information Sciences