Multiresource Allocation: Fairness-Efficiency Tradeoffs in a Unifying Framework

Quantifying the notion of fairness is underexplored when there are multiple types of resources and users request different ratios of the different resources. A typical example is data centers processing jobs with heterogeneous resource requirements on CPU, memory, network bandwidth, etc. In such cas...

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Bibliographic Details
Published inIEEE/ACM transactions on networking Vol. 21; no. 6; pp. 1785 - 1798
Main Authors Joe-Wong, Carlee, Sen, Soumya, Lan, Tian, Chiang, Mung
Format Journal Article
LanguageEnglish
Published IEEE 01.12.2013
Subjects
Bandwidth
Data center
efficiency
fairness
Indexes
Measurement
Memory management
multiresource allocation
resource allocation
Resource management
tradeoff
Vectors
Visualization
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Summary:Quantifying the notion of fairness is underexplored when there are multiple types of resources and users request different ratios of the different resources. A typical example is data centers processing jobs with heterogeneous resource requirements on CPU, memory, network bandwidth, etc. In such cases, a tradeoff arises between equitability, or "fairness," and efficiency. This paper develops a unifying framework addressing the fairness-efficiency tradeoff in light of multiple types of resources. We develop two families of fairness functions that provide different tradeoffs, characterize the effect of user requests' heterogeneity, and prove conditions under which these fairness measures satisfy the Pareto efficiency, sharing incentive, and envy-free properties. Intuitions behind the analysis are explained in two visualizations of multiresource allocation. We also investigate people's fairness perceptions through an online survey of allocation preferences.
ISSN:1063-6692
1558-2566
DOI:10.1109/TNET.2012.2233213