Abstract: An encoding method, a decoding method, an electronic device and a storage medium are disclosed. The encoding method includes: acquiring stored data in a storage system, and acquiring nodes corresponding to the stored data to obtain a number of the nodes; dividing the acquired stored data into a sequence of information vectors, and generating an information matrix according to the number of the nodes and a number of the sequence of information vectors; and calculating an encoded block according to each information vector and the information matrix to obtain a sequence of encoded blocks.

Abstract: Described herein are systems, methods, and other techniques for compatible packet separation for communication networks. A block comprising a plurality of packets to be transmitted over a network is received. The block includes a set of batches, and the plurality of packets are distributed between the set of batches. A pseudo interleaver depth is calculated for each of the set of batches to produce a set of pseudo interleaver depths. Blockwise adaptive recoding is performed using the set of pseudo interleaver depths to produce a number of recoded packets for each of the set of batches. A transmission sequence is generated using the number of recoded packets for each of the set of batches.

Abstract: Described herein are systems, methods, and other techniques for compatible packet separation for communication networks. A block comprising a plurality of packets to be transmitted over a network is received. The block includes a set of batches, and the plurality of packets are distributed between the set of batches. A pseudo interleaver depth is calculated for each of the set of batches to produce a set of pseudo interleaver depths. Blockwise adaptive recoding is performed using the set of pseudo interleaver depths to produce a number of recoded packets for each of the set of batches. A transmission sequence is generated using the number of recoded packets for each of the set of batches.

Abstract: BATS protocols may be utilized for high efficiency communication in networks with burst or dependent type losses. Systematic recoding at intermediate network nodes may be utilized to reduce the computational cost during recoding. A block interleaver based BATS protocol may be utilized to handle burst loss, where batches are recoded to a same number of packets. Adaptive recoding may be utilized to improve the throughput, where a batch with a higher rank is recoded to a larger number of packets. Using adaptive recoding, a non-block interleaver based BATS protocol may be utilized.

Abstract: Hardware acceleration for batched sparse (BATS) codes is enabled. Hardware implementation of some timing-critical procedures can effectively offload computationally intensive overheads, for example, finite field arithmetic, Gaussian elimination, and belief propagation (BP) calculations, and this can be done without direct mapping of software codes to a hardware implementation. Suitable acceleration hardware may include pipelined multipliers configured to multiply input data with coefficients of a matrix associated with a random linear network code in a pipelined manner, addition components configured to add multiplier output to feedback data, and switches to direct data flows to and from memory components such that valid result data is not overwritten and such that feedback data corresponds to most recent valid result data. Acceleration hardware components (e.g., number and configuration) may be dynamically adjusted to modify BATS code parameters and adapt to changing network conditions.

Abstract: Computationally efficient message encoding and decoding schemes for NCMA-based multiple access networks are enabled. Belief propagation decoding of fountain codes designed for NCMA-based multiple access networks may be enhanced using Gaussian elimination. Networks utilizing a network-coded slotted ALOHA protocol can benefit in particular. In such cases, Gaussian elimination may be applied locally to solve the linear system associated with each timeslot, and belief propagation decoding may be applied between the linear systems obtained over different timeslots. The computational complexity of such an approach may be of the same order as a conventional belief propagation decoding algorithm. The fountain code degree distribution may be tuned to optimize for different numbers of expected channel users.

Abstract: Hardware acceleration for batched sparse (BATS) codes is enabled. Hardware implementation of some timing-critical procedures can effectively offload computationally intensive overheads, for example, finite field arithmetic, Gaussian elimination, and belief propagation (BP) calculations, and this can be done without direct mapping of software codes to a hardware implementation. Suitable acceleration hardware may include pipelined multipliers configured to multiply input data with coefficients of a matrix associated with a random linear network code in a pipelined manner, addition components configured to add multiplier output to feedback data, and switches to direct data flows to and from memory components such that valid result data is not overwritten and such that feedback data corresponds to most recent valid result data. Acceleration hardware components (e.g., number and configuration) may be dynamically adjusted to modify BATS code parameters and adapt to changing network conditions.

Abstract: BATS protocols may be utilized for high efficiency communication in networks with burst or dependent type losses. Systematic recoding at intermediate network nodes may be utilized to reduce the computational cost during recoding. A block interleaver based BATS protocol may be utilized to handle burst loss, where batches are recoded to a same number of packets. Adaptive recoding may be utilized to improve the throughput, where a batch with a higher rank is recoded to a larger number of packets. Using adaptive recoding, a non-block interleaver based BATS protocol may be utilized.

Abstract: Computationally efficient message encoding and decoding schemes for NCMA-based multiple access networks are enabled. Belief propagation decoding of fountain codes designed for NCMA-based multiple access networks may be enhanced using Gaussian elimination. Networks utilizing a network-coded slotted ALOHA protocol can benefit in particular. In such cases, Gaussian elimination may be applied locally to solve the linear system associated with each timeslot, and belief propagation decoding may be applied between the linear systems obtained over different timeslots. The computational complexity of such an approach may be of the same order as a conventional belief propagation decoding algorithm. The fountain code degree distribution may be tuned to optimize for different numbers of expected channel users.

Abstract: The apparatus, systems, and methods described herein may operate to encode a first part of a message into an index, and to encode a second part of the message into a sequence of matrices such that at least one of row spaces or rank of the matrices is determined by the index. Additional apparatus, systems, and methods are described.

Abstract: A method for data encoding and associated decoding is based on the concept of batches that allows transmission of a large data file from a source node to multiple destination nodes through communication networks that may employ network coding wherein sparse matrix codes are employed in a network setting. A batch is a set of packets generated by a subset of the input packets using sparse matrix encoder. A sparse matrix encoder can be called repeatedly to generate multiple batches. The batches are generally independent of one another. During the transmission in a communication network, network coding can be applied to packets belonging to the same batch to improve the multicast throughput. A decoder recovers all or at least a fixed fraction of the input packets using received batches. The input packets can be pre-coded using a pre-code before applying sparse matrix codes. The data file can then be reconstructed by further decoding the pre-code.

Abstract: The apparatus, systems, and methods described herein may operate to encode a first part of a message into an index, and to encode a second part of the message into a sequence of matrices such that at least one of row spaces or rank of the matrices is determined by the index. Additional apparatus, systems, and methods are described.

Abstract: A method for data encoding and associated decoding is based on the concept of batches that allows transmission of a large data file from a source node to multiple destination nodes through communication networks that may employ network coding wherein sparse matrix codes are employed in a network setting. A batch is a set of packets generated by a subset of the input packets using sparse matrix encoder. A sparse matrix encoder can be called repeatedly to generate multiple batches. The batches are generally independent of one another. During the transmission in a communication network, network coding can be applied to packets belonging to the same batch to improve the multicast throughput. A decoder recovers all or at least a fixed fraction of the input packets using received batches. The input packets can be pre-coded using a pre-code before applying sparse matrix codes. The data file can then be reconstructed by further decoding the pre-code.