The maximum concurrent flow problem
Journal of the ACM (JACM)
Data networks (2nd ed.)
Cut problems and their application to divide-and-conquer
Approximation algorithms for NP-hard problems
Randomized rounding without solving the linear program
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Combining fairness with throughput: online routing with multiple objectives
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Phantom: a simple and effective flow control scheme
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IEEE/ACM Transactions on Networking (TON)
Approximating Fractional Multicommodity Flow Independent of the Number of Commodities
SIAM Journal on Discrete Mathematics
Approximation algorithms
Faster approximation schemes for fractional multicommodity flow problems
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Global Optimization Using Local Information with Applications to Flow Control
FOCS '97 Proceedings of the 38th Annual Symposium on Foundations of Computer Science
Faster and Simpler Algorithms for Multicommodity Flow and other Fractional Packing Problems.
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Fairness in Routing and Load Balancing
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Rate allocation in wireless sensor networks with network lifetime requirement
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Relating Reputation and Money in Online Markets
ACM Transactions on the Web (TWEB)
Pervasive and Mobile Computing
QoS protection optimisation for MPLS
International Journal of Communication Networks and Distributed Systems
B4: experience with a globally-deployed software defined wan
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
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Given a set of demands between pairs of nodes, we examine the traffic engineering problem of flow routing and fair bandwidth allocation where flows can be split to multiple paths (e.g., MPLS tunnels). This paper presents an algorithm for finding an optimal and global per-commodity max-min fair rate vector in a polynomial number of steps. In addition, we present a fast and novel distributed algorithm where each source router can find the routing and the fair rate allocation for its commodities while keeping the locally optimal max-min fair allocation criteria. The distributed algorithm is a fully polynomial epsilon-approximation (FPTAS) algorithm and is based on a primal-dual alternation technique. We implemented these algorithms to demonstrate its correctness, efficiency, and accuracy.