DRF was presented by Ali Ghodsi, Matei Zaharia, Benjamin Hindman, Andy Konwinski, Scott Shenker and Ion Stoica in 2011.
But in cloud computing, it is required to share different types of resource, such as: memory, CPU, bandwidth and disk-space.
DRF solves the problem by maximizing the minimum amount of the dominant resource given to a user (then the second-minimum etc., in a leximin order).
DRF aims to find the maximum x such that all agents can receive at least x of their dominant resource.
On the other hand, they show that DRF may yield poor utilitarian social welfare, that is, the sum of utilities may be only 1/m of the optimum.
However, they prove that any mechanism satisfying one of proportionality, envy-freeness or strategyproofness may suffers from the same low utilitarian welfare.
They also extend DRF to the setting in which the users' demands are indivisible (as in fair item allocation).
Wang, Li and Liang[3] present DRFH - an extension of DRF to a system with several heterogeneous servers.
DRF was first implemented in Apache Mesos - a cluster resource manager, and it led to better throughput and fairness than previously used fair-sharing schemes.