Polynomial time algorithms for network information flow

By Peter Sanders, S. Egner, L. Tolhuizen. ACM Symposium on Parallelism in Algorithms and Architectures, 2003

308 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4d8960e1f06f469aeba1224ac12f67f761042d7a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. A. Dimakis
2. Muriel Médard
3. Michelle Effros
4. Ralf Koetter
5. P. Chou
6. Kannan Ramchandran
7. T. Ho
8. J. L. Boudec

In Electrical and Electronic Engineering

1. Muriel Médard
2. Michelle Effros
3. A. Dimakis
4. Ralf Koetter
5. P. Chou
6. T. Ho
7. J. L. Boudec
8. J. Widmer

Citations in the corpus

• Polynomial time algorithms for multicast network code construction (2005, methodology): “Earlier versions of this algorithm were presented in [14], [22].”
• Network coding: an instant primer (2006, background): “There exist directed graphs where the throughput gains of network coding for multicasting can be very significant [24, 5].”
• On Randomized Network Coding (2003, background): “Sanders et al. [7] and Jaggi et al. [4] proposed centralized algorithms for single source multicast using a subgraph consisting of flow solutions to individual receivers, and showed that randomization with centralized testing could yield computational advantage.”
• Algebraic gossip: a network coding approach to optimal multiple rumor mongering (2006, background): “There is significant recent work on network coding [9], especially on the algorithmic aspects of construction of linear network codes [2], [14], [10], [19] for multicast connections.”
• Network Coding for Distributed Storage Systems (2007, background): “[23] further showed that random linear network coding over a sufficiently large finite field can (asym ptotically) achieve the multicast capacity.”
• A Random Linear Network Coding Approach to Multicast (2006, background): “operated in a burst [19], pipelined [26], or batched [3] fashion,”
• Minimum-energy multicast in mobile ad hoc networks using network coding (2004, methodology): “[15] [16] [17] showed for acyclic networks how to find the encoding and decoding coefficients in polynomial time.”
• Network coding for efficient communication in extreme networks (2005, background): “Much work has been published on optimal centralized network coding algorithms [19, 13].”