Dominant resource fairness: fair allocation of multiple resource types
University of California, Berkeley
Abstract
We consider the problem of fair resource allocation in a system containing different resource types, where each user may have different demands for each resource. To address this problem, we propose Dominant Resource Fairness (DRF), a generalization of max-min fairness to multiple resource types. We show that DRF, unlike other possible policies, satisfies several highly desirable properties. First, DRF incentivizes users to share resources, by ensuring that no user is better off if resources are equally partitioned among them. Second, DRF is strategy-proof, as a user cannot increase her allocation by lying about her requirements. Third, DRF is envy-free, as no user would want to trade her allocation with that…
Citation impact
- FWCI
- 71.99
- Percentile
- 100%
- References
- 32
Authors
6Topics & keywords
- Max-min fairness
- Resource allocation
- Computer science
- Resource management (computing)
- Fairness measure
- Generalization
- Throughput
- Resource (disambiguation)
- Decent work and economic growth