Analysis of the increase and decrease algorithms for congestion avoidance in computer networks
Computer Networks and ISDN Systems
Impact of fairness on Internet performance
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A Linear Programming Based Approach for Computing Optimal Fair Splittable Routing
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
On Efficient Max-Min Fair Routing Algorithms
ISCC '03 Proceedings of the Eighth IEEE International Symposium on Computers and Communications
Routing, Flow, and Capacity Design in Communication and Computer Networks
Routing, Flow, and Capacity Design in Communication and Computer Networks
Computing optimal max-min fair resource allocation for elastic flows
IEEE/ACM Transactions on Networking (TON)
Lexicographically Minimum and Maximum Load Linear Programming Problems
Operations Research
Computing optimal max-min fair resource allocation for elastic flows
IEEE/ACM Transactions on Networking (TON)
A general branch-and-bound algorithm for fair division problems
Computers and Operations Research
Maximum migration time guarantees in dynamic server consolidation for virtualized data centers
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
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In this paper, we provide a study of Max-Min Fair (MMF) multi-commodity flows and focus on some of their applications to multi-commodity networks. We first present the theoretical background for the problem of MMF and recall its relations with lexicographic optimization as well as a polynomial approach for achieving leximin maximization. We next describe two applications to telecommunication networks, one on routing and the second on load-balancing. We provide some deeper theoretical analysis of MMF multi-commodity flows, show how to solve the lexicographically minimum load network problem for the link load functions most frequently used in telecommunication networks. Some computational results illustrate the behavior of the obtained solutions and the required CPU time for a range of random and well-dimensioned networks.