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IEEE World Forum plenary by Muriel Medard

October 3, 2019

Our co-founder Muriel Medard delivered a Plenary on Randomness and RLNC at IEEE 5G World fourm recently showcasing work with Intel, NYC DOT and bechmarking against RaptorQ to highlight both the maturity and the performance of RLNC technology. View the slides from Prof. Medard's Lecture here

Steinwurf publish insightful benchmarks comparing RLNC and RaptorQ performance

September 10, 2019

Our partners at Steinwurf have recently published some insightful results comparing their Kodo erasure coding library implementing Random Linear Network Coding (RLNC) codecs to Codornices RaptorQ (release 2) performance.  Find the comparison here.

MIT and Intel continue to develop RLNC further

August 27, 2019

Massachusetts Institute of Technology and Intel Corporation continue to develop RLNC further in joint efforts such as this work on "Adaptive casual network coding with feedback for delay and throughput guarantees" by Alejandro Cohen, Derya Malak, Vered Bar Bracha, & Muriel Medard. Check out the paper on ArXiv here

RLNC Ecosystem Partners

Code On seeks to enable the broad adoption of Random Linear Network Coding (RLNC). It does that by providing consulting services and working to build an ecosystem of partners who provide a range of enabling tools and services.