Embodiments of the present disclosure relate to a binary clustered forward error correction encoding scheme. Systems and methods are disclosed that define binary clustered encodings of the media packets from which forward error correction (FEC) packets are computed. The different encodings specify which media packets in a frame are used to compute each FEC packet (a frame includes M media packets). The different encodings may be defined based on the quantity of media packets in a frame, M≤floor(2.sup.N), where each bit of the binary representation of N is associated with a different cluster pair encoding of the media packets. Each cluster pair includes a cluster for which the bit=0 and a cluster for which the bit=1. Computing FEC packets using at least two cluster pair encodings provides redundancy for each media packet, thereby improving media packet recovery rates.

Provided is a memory system comprising an error correction code (ECC) decoder configured to receive data from a memory. The ECC decoder includes a syndrome generator configured to calculate at least one of syndrome vector and an erasure value, the calculation being devoid of erasure location information and an error-location polynomial generator configured to determine error location and error/erasure value polynomials responsive to syndrome and erasure calculation values output from the syndrome generator. An error value generator confirms error values at one or more known error locations based upon the determined error/erasure value polynomials, and an error location generator search for an error evaluation value to confirm the known error locations based upon the determined error location polynomials. Outputs of the error value generator and the error location generator are combined to produce corrected data.

A packet processing method includes generating, by a processor of a network device, a first encoding task based on M original packets in a to-be-processed first data stream, where M is a positive integer, and where the first encoding task instructs to encode the M original packets; and performing, by a target hardware engine of the network device and based on the first encoding task, forward error correction (FEC) encoding on the M original packets to obtain R redundant packets, where R is a positive integer.

A technique provides efficient data protection, such as erasure coding, for data blocks of volumes served by storage nodes of a cluster. Data blocks associated with write requests of unpredictable client workload patterns may be compressed. A set of the compressed data blocks may be selected to form a write group and an erasure code may be applied to the group to algorithmically generate one or more encoded blocks in addition to the data blocks. Due to the unpredictability of the data workload patterns, the compressed data blocks may have varying sizes. A pool of the various-sized compressed data blocks may be established and maintained from which the data blocks of the write group are selected. Establishment and maintenance of the pool enables selection of compressed data blocks that are substantially close to the same size and, thus, that require minimal padding.

A method for adjustable error correction in a storage cluster is provided. The method includes determining health of a non-volatile memory of a non-volatile solid-state storage unit of each of a plurality of storage nodes in a storage cluster on a basis of per flash package, per flash die, per flash plane, per flash block, or per flash page. The determining is performed by the storage cluster. The plurality of storage nodes is housed within a chassis that couples the storage nodes as the storage cluster. The method includes adjusting erasure coding across the plurality of storage nodes based on the health of the non-volatile memory and distributing user data throughout the plurality of storage nodes through the erasure coding. The user data is accessible via the erasure coding from a remainder of the plurality of storage nodes if any of the plurality of storage nodes are unreachable.

A method begins by a load balancing module of a distributed storage network (DSN) determining availability of a plurality of DSN processing units of a set of DSN processing units based on availability information associated with the plurality of DSN processing units and in response to determined availability, selecting a DSN processing unit form the set to process a data access request. The method continues with the load balancing module receiving an indication that the DSN processing unit is no longer available from the DSN processing unit while the DSN processing unit continues to process previously pending data access requests. The method continues with the load balancing module cancelling selection of the DSN processing unit to process the data access request; and receiving a second indication from the DSN processing unit indication that the DSN processing unit is available.

An error correction and fault tolerance method and system for an array of disks is presented. The array comprises k+5 disks, where k disks store user data and 5 disks store computed parity. The present invention further comprises a method and a system for reconstituting the original content of each of the k+5 disks, when up to 5 disks have been lost, wherein the number of disks at unknown locations is E and the number of disks wherein the location of the disks is known is Z. All combinations of faulty disks wherein Z+2×E≤4 are reconstituted. Some combinations of faulty disks wherein Z+2×E≥5 are either reconstituted, or errors are limited to a small list.

A memory system includes a non-volatile memory and a controller. The controller is configured to perform iterative correction on a plurality of frames of data read from the non-volatile memory. The iterative correction includes performing a first error correction on each of the frames including a first frame having errors not correctable by the first error correction, generating a syndrome on a set of second frames that include the first frame, performing a second error correction on the second frames using the syndrome, and performing a third error correction on the first frame. Each of the frames includes user data and first parity data used in the first error correction, the first parity data of the first frame also being used in the third error correction.

A method of reading from a storage medium to recover a group of information sectors, each comprising a respective information payload. The medium stores redundancy data comprising a plurality of separate redundancy codes for the group, each code being a linear sum of terms, each term in the sum being the information payload from a different respective one of the information sectors in the group weighted by a respective coefficient of a set of coefficients for the redundancy code. The method comprises, after the redundancy data has already been stored on the medium: identifying a set of k′ information sectors to be recovered; selecting k′ of the redundancy codes; determining a square matrix E of the k′ information sectors by the k′ sets of coefficients of the selected codes; determining a matrix D being a matrix inverse of E; and recovering the k′ information payloads from the inverse matrix D.

A memory system includes a non-volatile memory and a controller. The controller is configured to perform iterative correction on a plurality of frames of data read from the non-volatile memory. The iterative correction includes performing a first error correction on each of the frames including a first frame having errors not correctable by the first error correction, generating a syndrome on a set of second frames that include the first frame, performing a second error correction on the second frames using the syndrome, and performing a third error correction on the first frame. Each of the frames includes user data and first parity data used in the first error correction, the first parity data of the first frame also being used in the third error correction.