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ABSTRACT
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 which is a logarithmic approximation, simultaneously, to all canonical social welfare functions (i.e. functions which are symmetric, concave, and non-decreasing). These protocols can be started in an arbitrary state. While a similar protocol was known before, it only applied to the simple bandwidth allocation problem, and its stability and convergence time was 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. Further, we prove that our protocols converge in polynomial time. The best convergence time we prove is O(n log ncmaxamax/cminamin), where n is the number of agents in the network, cmax and cmin are the maximum and minimum capacity of the links, and amax, amin are the largest and smallest Leontief coefficients, respectively. This time is achieved by a simple MIMD (multiplicative increase, multiplicative decrease) protocol which 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 which 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.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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4
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5
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6
|
S. Cho and A. Goel. Bandwidth allocation in networks: a single dual-update subroutine for multiple objectives. Proceedings of the first Workshop on Combinatorial and Algorithmic Aspects of Networks, 3405:28--41, 2004.
|
 |
7
|
|
| |
8
|
B. Codenotti, B. McCune, S. Penumatcha, and k. Varadarajan. Market equilibrium for ces exchange economies: Existence, multiplicity, and computation. FSTTCS, 2005.
|
 |
9
|
Bruno Codenotti , Amin Saberi , Kasturi Varadarajan , Yinyu Ye, Leontief economies encode nonzero sum two-player games, Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm, p.659-667, January 22-26, 2006, Miami, Florida
[doi> 10.1145/1109557.1109629]
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10
|
|
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11
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|
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12
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13
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A. Goel and A. Meyerson. Simultaneous optimization via approximate majorization for concave profits or convex costs. Algorithmica, 44(4):301--323, May 2006.
|
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14
|
|
 |
15
|
|
| |
16
|
G. H. Hardy, J. E. Littlewood, and G. Polya. Some simple inequalities satisfied by convex functions. Messenger Math., 58:145--152, 1929.
|
| |
17
|
G. H. Hardy, J. E. Littlewood, and G. Polya. Inequalities. 1st ed., 2nd ed. Cambridge University Press, London and New York., 1934, 1952.
|
| |
18
|
F. P. Kelly, A. K. Maulloo, and D. K. H. Tan. Rate control in communication networks: shadow prices, proportional fairness and stability. Journal of the Operational Research Society, 49:237--252, 1998.
|
| |
19
|
|
| |
20
|
|
 |
21
|
|
| |
22
|
A. W. Marshall and I. Olkin. Inequalities: theory of majorization and its applications. Academic Press (Volume 143 of Mathematics in Science and Engineering), 1979.
|
| |
23
|
|
| |
24
|
Y. Ye. A note on exchange market equilibria with leontief's utility: Freedom of pricing leads to rationality. Proceeding of The 1st International Workshop On Internet and Network Economics, 2005.
|
|