How can RLNC - make our interconnected world work?
The simplicity of the RLNC algorithm means that all neighbouring devices can help the network as soon as the transfer starts, boosting speed and reliability. Coded and native packets can be re-coded by any node to increase the network’s robustness, without impacting latency or decoding complexity
RLNC's ability to enable intermediate devices to create redundancy as soon as they receive the first packet - without need to decode - enables true network cooperation, boosting reliability, slashing delay, and saving significant device energy
RLNC removes most of the retransmissions and device-by-device tracking that bogs down conventional multicast wireless and CDN systems. In addition, it enables cooperative broadcast and caching, yielding massive energy and latency reductions
RLNC facilitates the secure distribution of data across diverse systems and geographies. The added layer of security helps keep client data protected
Code On’s proprietary coding technology, Random Linear Network Coding (RLNC), enables the powerful, next-generation multicast features required for satellite, mobile 5G, connected cars, video streaming and much more.
Check out demo videos from our licensees:
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
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.
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
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.
