An Axiomatic Theory of Fairness in Network Resource Allocation

Abstract

We present a set of five axioms for fairness measures in resource allocation. A family of fairness measures satisfying the axioms is constructed. Well-known notions such as alpha-fairness, Jain's index, and entropy are shown to be special cases. Properties of fairness measures satisfying the axioms are proven, including Schur-concavity. Among the engineering implications is a generalized Jain's index that tunes the resolution of the fairness measure, a new understanding of alpha-fair utility functions, and an interpretation of "larger alpha is more fair". We also construct an alternative set of four axioms to capture efficiency objectives and feasibility constraints.