Fair Resource Allocation for Demands with Sharp Lower Tail Inequalities
This work addresses fairness in resource allocation for groups with predictable demands, but it is incremental as it builds on prior models and focuses on specific distribution types.
The paper tackles the problem of fair resource allocation among groups with known demand distributions, showing that a proportional allocation based on average demand performs well for distributions with sharp lower tail inequalities, achieving near fairness and efficiency with a Price of Fairness close to 1.
We consider a fairness problem in resource allocation where multiple groups demand resources from a common source with the total fixed amount. The general model was introduced by Elzayn et al. [FAT*'19]. We follow Donahue and Kleinberg [FAT*'20] who considered the case when the demand distribution is known. We show that for many common demand distributions that satisfy sharp lower tail inequalities, a natural allocation that provides resources proportional to each group's average demand performs very well. More specifically, this natural allocation is approximately fair and efficient (i.e., it provides near maximum utilization). We also show that, when small amount of unfairness is allowed, the Price of Fairness (PoF), in this case, is close to 1.