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Optimal Multicommodity Flow Through the Complete Graph with Random Edge Capacities

Published online by Cambridge University Press:  14 July 2016

Mustafa Khandwawala*
Affiliation:
Indian Institute of Science
Rajesh Sundaresan*
Affiliation:
Indian Institute of Science
*
Postal address: Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore 560012, India.
Postal address: Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore 560012, India.
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Abstract

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We consider a multicommodity flow problem on a complete graph whose edges have random, independent, and identically distributed capacities. We show that, as the number of nodes tends to infinity, the maximum utility, given by the average of a concave function of each commodity flow, has an almost-sure limit. Furthermore, the asymptotically optimal flow uses only direct and two-hop paths, and can be obtained in a distributed manner.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2010 

References

[1] Aldous, D. J., McDiarmid, C. and Scott, A. (2009). Uniform multicommodity flow through the complete graph with random edge-capacities. Operat. Res. Lett. 37, 299302.Google Scholar
[2] Chayes, J. T. and Chayes, L. (1986). Bulk transport properties and exponent inequalities for random resistor and flow networks. Commun. Math. Phys. 105, 133152.Google Scholar
[3] Georgiadis, L., Neely, M. J. and Tassiulas, L. (2006). Resource allocation and cross-layer control in wireless networks. Foundations Trends Networking 1, 1144.Google Scholar
[4] Grimmett, G. and Kesten, H. (1984). First-passage percolation, network flows and electrical resistances. Z. Wahrscheinlichkeitsth. 66, 335366.Google Scholar
[5] Grimmett, G. R. and Stirzaker, D. R. (1992). Probability and Random Processes, 2nd edn. Clarendon Press, Oxford.Google Scholar
[6] Kapoor, S. and Vaidya, P. M. (1996). Speeding up Karmarkar's algorithm for multicommodity flows. Math. Program. A 73, 111127.Google Scholar
[7] Kelly, F. P., Maulloo, A. K. and Tan, D. K. H. (1998). Rate control for communication networks: shadow prices, proportional fairness and stability. J. Operat. Res. Soc. 49, 237252.Google Scholar
[8] Leighton, T. et al. (1995). Fast approximation algorithms for multicommodity flow problems. J. Comput. System Sci. 50, 228243.Google Scholar
[9] Megiddo, N. (1974). Optimal flows in networks with multiple sources and sinks. Math. Program. 7, 97107.Google Scholar
[10] Mo, J. and Walrand, J. (2000). Fair end-to-end window-based congestion control. IEEE/ACM Trans. Networking 8, 556567.Google Scholar
[11] Zhang, Y. (2000). Critical behavior for maximal flows on the cubic lattice. J. Statist. Phys. 98, 799811.Google Scholar