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Using Approximate Majorization to Characterize Protocol
Fairness
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Authors
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Rishi Bhargava
ONI Systems
Ashish Goel <agoel@cs.usc.edu>
Department of Computer Science, University of Southern California
Adam Meyerson <awm@cs.stanford.edu>
Department of Computer Science, Stanford University
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Abstract
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A good measure of fairness is an essential prerequisite for a
systematic development of fair resource allocation protocols as well
as for a systematic evaluation of the fairness of existing
protocols. We propose the use of approximate majorization as a
framework for quantifying the fairness of a resource allocation
scheme. We demonstrate how approximate majorization subsumes and
generalizes several natural measures of fairness. We then relate
majorization to revenue maximization, and sketch (in the full
version of the paper) an efficient algorithm to compute the fairness
of a given allocation as well as to find the fairest possible
allocation. We believe that our framework is quite general and can
be applied to several routing, bandwidth allocation, load balancing,
and clustering problems. We use this framework to perform a
preliminary case study of the fairness of TCP as a bandwidth
allocation protocol in communication networks. We discover several
interesting trends about the fairness of TCP which merit further
study. The fairness of TCP improves as the buffer sizes and/or link
capacities are increased. In several realistic cases, the fairness
of TCP is comparable to or better than that of max-min fair
allocations.
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