An axiomatic theory of fairness in network resource allocation

Authors:
Tian Lan;David Kao;Mung Chiang;Ashutosh Sabharwal
Affiliations:
Department of Electrical Engineering, Princeton University, NJ;Department of Electrical and Computer Engineering, Rice University, TX;Department of Electrical Engineering, Princeton University, NJ;Department of Electrical and Computer Engineering, Rice University, TX
Venue:
INFOCOM'10 Proceedings of the 29th conference on Information communications
Year:
2010

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Abstract

We present five axioms for fairness measures in resource allocation. A family of fairness measures satisfying the axioms is constructed. Special cases of this family include a-fairness, Jain's index, and entropy. Properties of fairness measures satisfying the axioms are proven, including Schurconcavity. Among the engineering implications is a generalized Jain's index that tunes the resolution of fairness measure, a new understanding of a-fair utility functions, and an interpretation of "larger a is more fair". We also construct an alternative set of axioms to capture system efficiency and feasibility constraints.