This should be a real boost for Mesh Networks and I wonder if this gets widely adopted if it has any implications for SAFEnet
Imagine an optimized SAFEmesh software running on OpenAirInterface:
OpenAirInterface.org is an open-source platform (GNU GPL v3) for experimentation in wireless systems primarily targeting cellular technologies (LTE/LTE-Advanced and beyond) and rapidly-deployable mesh/ad-hoc networks | Users can build an LTE compliant base station for less than 1900 Euros
Researchers at Aalborg University, MIT and Caltech have developed a new mathematically-based technique that can boost internet data speeds by up to 10 times, by making the nodes of a network much smarter and more adaptable. The advance also vastly improves the security of data transmissions, and could find its way into 5G mobile networks, satellite communications and the Internet of Things.
This company builds on their Kodo library
This page provides background information and useful guidelines about using Network Coding in common communication scenarios.
What is Network Coding?
Network coding is an interesting technique which can provide throughput improvements and a high degree of robustness in packet networks. It breaks with the “store-and-forward” principle of conventional communication networks by allowing any network node to recombine several input packets into one coded packet, instead of simple forwarding.
Overview of Random Linear Network Coding (RLNC)
The figure below gives a basic overview of the operations performed in a network coding system. If you intend to encode a large file then it should be split into several blocks, also called generations each consisting of g symbols. If the whole file was considered one big block, then the computational complexity of the encoding and decoding operations would be very high.
The top component in the figure is the encoder that generates and transmits linear combinations of some original symbols in a given generation. Addition and multiplication are performed over a Galois field, therefore a linear combination of several symbols will have the same size as a single symbol. Note that any number of encoded packets can be generated for a single generation. The middle layer in this system is the wireless channel where packet erasures may occur depending on the channel conditions. The network nodes receive a series of encoded packets that are passed to the decoder (the bottom component in the figure) which will be able to reconstruct the original symbols after receiving at least g linearly independent packets.
Network coding is useful for ensuring reliability and/or increasing throughput in a communication network. An obvious benefit of using network coding is that a network node is no longer required to gather all data packets one-by-one, instead it only has to receive enough linearly independent encoded packets.
Network Coding can be used to repair packet losses on a lossy link, just like any other Erasure Correcting Code. If a good estimate is available about the Packet Error Probability, then a certain amount of redundancy packets can be generated pro-actively to combat packet losses. This is known as Forward Error Correction (FEC) or simply “overshooting”.
Another approach is to repair packet losses retro-actively which typically requires some feedback from the receiver about the lost packets. Of course, the sender could simply retransmit the original packets without any coding. Network Coding helps in reducing the necessary feedback from the receiver, because it does not have to communicate which packets were lost, just how many. The sender can simply generate and send as many coded packets as the number of packets lost on the receiver.
Let’s assume that we want to reliably transmit some data from a mobile device or computer on the network to several nearby receivers via a lossy wireless link. The problem is that unicast transmissions provide a poor utilization of the available network resources for one-to-many scenarios. If all receivers are interested in the same content, we can efficiently utilize the wireless channel with broadcast transmissions.
Under ideal channel conditions all broadcast packets would be delivered to all nodes simultaneously. In real-life wireless networks packet losses frequently occur, thus some sort of retransmission scheme is necessary to ensure reliability. We need to correct packet losses at the receivers. A simple solution would be that the receiver nodes request all missing packets from the original source. This would imply that every lost packet is transmitted again, and if packet losses are uncorrelated then most retransmissions will not be useful to specific receivers since they have already received those packets in the first place. To put it differently, it is likely that a single retransmission will only benefit a single receiver.
By using Network Coding, we can simultaneously benefit multiple nodes with a single retransmission by sending a coded packet instead of choosing a specific original packet. Due to the uncorrelated nature of packet losses, the receivers usually hold different sets of packets. The source can create and send random linear combinations of the original data. One coded packet carries information which can potentially correct different errors at different nodes simultaneously.
Sometimes reliable data distribution is not a requirement or it is not possible at all. For example, consider video streaming to a large number of receivers on a wireless network where feedback would be impractical. In this case, Network Coding can help to maximize the impact of each retransmission to the receivers. Ideally, a number of redundancy packets should be transmitted for each generation to provide a sufficient degree of reliability for the majority of receivers. This redundancy ratio (also known as “overshoot”) should be adjusted according to the estimated Packet Error Probability.
Recoding and Multi-hop Networks
If the network nodes are constantly moving or if they are connected in a multi-hop fashion (where some devices can only be reached over multiple hops), then Network Coding offers even greater benefits due to the unique ability of recoding. This feature essentially allows all network nodes to generate new ”re-encoded” packets, thus new linear combinations of the packets that they have previously received. A sender can transmit recoded packets from partially decoded generations. In contrast, traditional end-to-end coding schemes require the original data set to be fully decoded before it can be encoded again.
In a multi-hop network, the individual nodes have limited or no information about the state of other devices, especially if those are several hops away. Even a small amount of coding operations can substantially increase the number of innovative transmissions as opposed to just re-transmitting the packets received from other nodes. A coded packet can contain new information with a high probability. If recoding is also enabled, then new recoded packets can be generated even before a generation is completely received. In general, Random Linear Network Coding helps to minimize signaling between two communicating devices as the random combinations provide an implicit solution for coordination.