Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Dominant Resource Fairness: Fair Allocation of Heterogeneous Resources in Datacenters

Ali Ghodsi, Matei Zaharia, Benjamin Hindman, Andrew Konwinski, Scott Shenker and Ion Stoica

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2010-55
May 7, 2010

http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-55.pdf

This paper investigates how different resources can be fairly allocated among users that possibly prioritize them differently. We introduce a fairness policy, called Dominant Resource Fairness (DRF), which is an adaptation of max-min fairness from networking to datacenter environments. We show that DRF, unlike other policies which we investigated, satisfies a number of desirable properties that a fair datacenter scheduler should have, including guaranteeing that every user gets 1/N of some resource and that users can relinquish resources without hurting other users’ allocations. DRF is also envy-free, incentivizing users to correctly report their resource demand. When compared to other intuitive schedulers, as well as competing ones from microeconomic theory, DRF is more fair.


BibTeX citation:

@techreport{Ghodsi:EECS-2010-55,
    Author = {Ghodsi, Ali and Zaharia, Matei and Hindman, Benjamin and Konwinski, Andrew and Shenker, Scott and Stoica, Ion},
    Title = {Dominant Resource Fairness: Fair Allocation of Heterogeneous Resources in Datacenters},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2010},
    Month = {May},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-55.html},
    Number = {UCB/EECS-2010-55},
    Abstract = {This paper investigates how different resources can be fairly allocated among users that possibly prioritize them differently. We introduce a fairness policy, called Dominant Resource Fairness (DRF), which is an adaptation of max-min fairness from networking to datacenter environments. We show that DRF, unlike other policies which we investigated, satisfies a number of desirable properties that a fair datacenter scheduler should have, including guaranteeing that every user gets 1/N of some resource and that users can relinquish resources without hurting other users’ allocations. DRF is also envy-free, incentivizing users to correctly report their resource demand. When compared to other intuitive schedulers, as well as competing ones from microeconomic theory, DRF is more fair.}
}

EndNote citation:

%0 Report
%A Ghodsi, Ali
%A Zaharia, Matei
%A Hindman, Benjamin
%A Konwinski, Andrew
%A Shenker, Scott
%A Stoica, Ion
%T Dominant Resource Fairness: Fair Allocation of Heterogeneous Resources in Datacenters
%I EECS Department, University of California, Berkeley
%D 2010
%8 May 7
%@ UCB/EECS-2010-55
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-55.html
%F Ghodsi:EECS-2010-55