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In this article, based on the max min fairness notion, we propose a practical protocol to implement fair-based resource allocation in the winning coalition S. The main goal of the proposed algorithm is to distribute bandwidth for each user's communication as evenly as possible, without unduly reducing system efficiency.
The most common fairness notion is min max fairness.
Moreover, for most systems we obtain a fairness notion, which we refer to as SG+, such that SG+ is the strongest fairness notion that is both implementable and equivalence-robust.
In this paper, we study the system requirement for a completion to be strongly feasible and determine the strongest implementable completion for every given fairness notion.
To characterize this fairness notion, we follow the Jain's fairness index (F index) [25], which has been frequently used to measure the fairness of network resource allocations.
To characterize the fairness notion, we follow the Jain's fairness index [4], which has frequently been used to measure the fairness of network resource allocations.
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The computational complexity of checking whether a fair assignment exists is studied for these fairness notions.
We focus here on equivalence-robust fairness notions where equivalence computations are either all fair or all unfair.
This implies plenty of leeway in the design of fairness notions suitable for various applications.
The consideration of fairness notions has mainly been a wired network issue[12, 13].
We also provide a comprehensive comparison of SG+ and several well-known fairness notions and their minimal and maximal completions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com