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A Quantitative Measure Of Fairness And Discrimination For Resource Allocation In Shared Computer Systems
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1998
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Cluster ComputingEngineeringDynamic Resource AllocationResource Allocation SchemesDiscrimination IndexData ScienceShared Computer SystemsFair Data PrincipleQuantitative MeasureMechanism DesignComputer EngineeringFair Resource AllocationComputer ScienceFair DivisionEdge ComputingCloud ComputingAlgorithmic FairnessBusinessResource Allocation
Fairness is a key criterion in resource allocation, yet it is usually defined qualitatively and existing quantitative measures are either too application‑specific or have undesirable properties. The proposed index applies to any resource sharing problem and is independent of the resource quantity. The index ranges from 0 to 1, where a value of 0.10 indicates 90 % unfairness, and the complementary discrimination index is defined as 1 minus the fairness value.
Fairness is an important performance criterion in all resource allocation schemes, including those in distributed computer systems. However, it is often specified only qualitatively. The quantitative measures proposed in the literature are either too specific to a particular application, or suffer from some undesirable characteristics. In this paper, we have introduced a quantitative measure called Indiex of FRairness. The index is applicable to any resource sharing or allocation problem. It is independent of the amount of the resource. The fairness index always lies between 0 and 1. This boundedness aids intuitive understanding of the fairness index. For example, a distribution algorithm with a fairness of 0.10 means that it is unfair to 90% of the users. Also, the discrimination index can be defined as 1 - fairness index.