An information-theoretic characterization of weighted α-proportional fairness in network resource allocation

Masato Uchida*, Jim Kurose

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


This paper provides a characterization of fairness concepts in network resource allocation problems from the viewpoint of information theory. The fundamental idea underlying this paper is to characterize the utility functions in optimization problems, which motivate fairness concepts, based on a trade-off between user and network satisfaction. User satisfaction is evaluated using information divergence measures, which were originally used in information theory, to evaluate the difference between an implemented resource allocation and a requested resource allocation. The requested resource allocation is assumed to be ideal in some sense from the user's point of view. Network satisfaction is evaluated based on the efficiency of resource usage in the implemented resource allocation. The results in this paper indicate that the well-known fairness concept called weighted α-proportional fairness can be characterized using the α-divergence measure, which is a general class of information divergence measures, as an equilibrium of the trade-off. Some typical examples of applications demonstrate how the presented characterization works.

Original languageEnglish
Pages (from-to)4009-4023
Number of pages15
JournalInformation Sciences
Issue number18
Publication statusPublished - 2011 Sept 15
Externally publishedYes


  • Information divergence measures
  • Trade-off between user and network satisfaction
  • Weighted α-proportional fairness

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence


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