• Media type: E-Article
  • Title: Price-based protocols for fair resource allocation : Convergence time analysis and extension to leontief utilities : Convergence time analysis and extension to leontief utilities
  • Contributor: Goel, Ashish; Nazerzadeh, Hamid
  • Published: Association for Computing Machinery (ACM), 2014
  • Published in: ACM Transactions on Algorithms, 10 (2014) 2, Seite 1-14
  • Language: English
  • DOI: 10.1145/2556949
  • ISSN: 1549-6325; 1549-6333
  • Keywords: Mathematics (miscellaneous)
  • Origination:
  • Footnote:
  • Description: We analyze several distributed, continuous time protocols for a fair allocation of bandwidths to flows in a network (or resources to agents). Our protocols converge to an allocation that is a logarithmic approximation, simultaneously, to all canonical social welfare functions (i.e., functions that are symmetric, concave, and nondecreasing). These protocols can be started in an arbitrary state. Although a similar protocol was known before, it only applied to the simple bandwidth allocation problem, and its stability and convergence time were not understood. In contrast, our protocols also apply to the more general case of Leontief utilities, where each user may place a different requirement on each resource. Furthermore, we prove that our protocols converge in polynomial time. The best convergence time we prove is O ( n log nc MAX a MAX / c MIN a MIN ), where n is the number of agents in the network, c MAX and c MIN are the maximum and minimum capacity of the links, and a max , a min are respectively the largest and smallest Leontief coefficients. This time is achieved by a simple Multiplicative Increase, Multiplicative Decrease (MIMD) protocol that had not been studied before in this setting. We also identify combinatorial properties of these protocols that may be useful in proving stronger convergence bounds. The final allocations by our protocols are supported by usage-sensitive dual prices that are fair in the sense that they shield light users of a resource from the impact of heavy users. Thus, our protocols can also be thought of as efficient distributed schemes for computing fair prices.