Charging and Rate Control for Elastic Traac

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Fair Resource Allocation in Federated Learning (2019, background): “In particular, the above function represents zero fairness with α = 0 , proportional fairness [20] with α = 1 , harmonic mean fairness [7] with α = 2 , and max-min fairness [31] with α = + ∞ .”
Fair end-to-end window-based congestion control (1998, unknown): “Kelly [15] proposed proportionally fairness.”
A duality model of TCP and queue management algorithms (2003, background): “An optimal rate allocation problem is formulated in [13] where the goal is to choose source rates so as to maximize aggregate source utility subject to capacity constraints.”
REM: active queue management (2001, background): “Flow control is posed as an optimization problem in [6] where the objective is to maximize aggregate source utility (problem (5{6) in Section 3 below).”
Non-Discriminatory Machine Learning through Convex Fairness Criteria (2018, methodology): “In this paper, we draw inspiration from literature on rate control in communication networks (Kelly 1997) to offer fairness interpretation of a machine learning classifier.”