RLNC vs Traditional Codes

RLNC has a number of unique features compared to other coding schemes.


Recoding is a unique RLNC feature. With recoding, coded symbols (i.e., packet / file / drive chunks) can be recombined without decoding. This feature is only possible in RLNC owing to the portability of the coding coefficients and the random nature of code selection (see white paper section). 

Recoding enables intermediate transport nodes and storage caches to combine coded packets/sectors to create new coded packets/sectors that are effective representations of all original packets/sectors involved in the first coding stage. This is illustrated in Figure (A) below, where plain-colored original packets can be combined using encoding, then re-combined with other encoded packets through recoding.

Recoding involves the linear combination of coded packets and the recalculation of new coding coefficients. It is a flexible process where data can be encoded as it becomes available, as shown in Figure (B), where recoding can combine a previously encoded packet with a previously absent original packet.

The unique flexibility of RLNC also allows for the removal of an original packet from a coded representation. This is illustrated in Figure (C) below, where the yellow packet is removed from existing coded packets. Figure (D) illustrates how recoding fits within the encoding and decoding scheme.

Recoding enables, for the first time, coding across mesh networks and distributed storage topologies. It allows powerful extensions and novel protocols in relay and mesh topologies. For instance, RLNC recoding alone can double the throughput of a single relay link. In a cooperative mobile mesh, this gain multiplies, while latency drops proportionally.

RLNC recoding also minimizes the total number of packet transmissions across a mesh network or storage system. The energy gains thus generated far exceed any encoding energy requirements.

Recoding is an integral part of Code On’s mesh, storage, multicast, and multipath solutions, where it brings significant latency, goodput, and reliability gains in all associated markets.

Please refer to our white papers for illustrative implementations and results.