Abstract: Snapshots from a first LSU (R1) on a first storage system (A1) may be replicated to a second replica LSU (R2) on a second storage system (A2), for example, concurrently to remotely replicating (e.g., synchronously) write operations for R1 to R2. A process, P, on A1 executing the replication of the snapshots from R1 to R2 may be a separate process than the one or more processes on A1 executing remote replication of write operations for R1 to R2. During a consistency window on A1, outstanding write operations for R1 at the time the consistency window opened may be logged, and a pair of snapshots, SS11 and SS12 may be activated on R1 and R2, respectively. After the consistency window has closed, the SS12 snapshot metadata and snapshot data may be updated based on the outstanding write operations.

Abstract: Snapshots may be remotely replicated asynchronously from a first LSU (R1) on a first storage system (A) to a second replica LSU (R2) on a second storage system (A2). The storage system A1 may open a consistency window to suspend initiating processing of new write operations received on A1. While the consistency window is open, A1 may: take a first snapshot, SS11, of R1; record, in association with the first replication cycle, an indication to replicate SS11 on A2; and initiate a next replication cycle to record write operations of the next new write requests to be received from hosts. After initiating a next replication cycle, A1 may close the consistency and transmit the first replication cycle to A2. A2 may apply the write operations of the first replication cycle to R2, and then take a second snapshot SS12 of R2, which should be a replica of SS11.

Abstract: Snapshots may be remotely replicated asynchronously from a first LSU (R1) on a first storage system (A) to a second replica LSU (R2) on a second storage system (A2). The storage system A1 may open a consistency window to suspend initiating processing of new write operations received on A1. While the consistency window is open, A1 may: take a first snapshot, SS11, of R1; record, in association with the first replication cycle, an indication to replicate SS11 on A2; and initiate a next replication cycle to record write operations of the next new write requests to be received from hosts. After initiating a next replication cycle, A1 may close the consistency and transmit the first replication cycle to A2. A2 may apply the write operations of the first replication cycle to R2, and then take a second snapshot SS12 of R2, which should be a replica of SS11.

Abstract: Snapshots from a first LSU (R1) on a first storage system (A1) may be replicated to a second replica LSU (R2) on a second storage system (A2), for example, concurrently to remotely replicating (e.g., synchronously) write operations for R1 to R2. A process, P, on A1 executing the replication of the snapshots from R1 to R2 may be a separate process than the one or more processes on A1 executing remote replication of write operations for R1 to R2. During a consistency window on A1, outstanding write operations for R1 at the time the consistency window opened may be logged, and a pair of snapshots, SS11 and SS12 may be activated on R1 and R2, respectively. After the consistency window has closed, the SS12 snapshot metadata and snapshot data may be updated based on the outstanding write operations.

Abstract: A primary storage system appends a red-hot data indicator to each track of data transmitted on a remote data facility during an initial synchronization state. The red-hot data indicator indicates, on a track-by-track basis, whether the data associated with that track should be stored as compressed or uncompressed data by the backup storage system. The red-hot data indicator may be obtained from the primary storage system's extent-based red-hot data map. If the red-hot data indicator indicates that the track should remain uncompressed, or if the track is locally identified as red-hot data, the backup storage system stores the track as uncompressed data. If the red-hot data indicator indicates that the track should be compressed, the backup storage system compresses the track and stores the track as compressed data. After the initial synchronization process has completed, red-hot data indicators are no longer appended to tracks by the primary storage system.

Abstract: Various systems and methods for implementing computational storage are described herein.

Abstract: The system, devices, and methods disclosed herein relate to online data expansion in disaster recovery enabled data storage systems. We disclose embodiments that allow storage devices, which are coupled to one another in a disaster recovery, data replication-type scenario, to perform storage expansion in most cases without having to disable remote replication during the expansion. The teachings of this patent application facilitate methods of expansion for data storage device pairings where the data storage devices are the same size or where the primary storage device is smaller than the secondary storage device. In both of these situations, expansion occurs without disabling disaster recovery. In the situation where the secondary storage device is larger than the primary device, expansion is allowed, with the caveat that disaster recovery must be disabled briefly.

Abstract: Described is a process and device for accessing data stored in multiple logical volumes. The data are replicated on first and second storage elements, such as the redundant hard disk drives of a disk mirror. The multiple logical volumes are divisible into a first logical volume and a second logical volume. All read requests targeting the first logical volume are directed to one of the first and second storage elements. Read requests targeting the second logical volume are asymmetrically interleaved between the first and second storage elements. An asymmetric interleave ratio is determined and implemented that substantially balances the read requests to the multiple logical volumes between the first and second storage elements.

Abstract: Predictions of congestion conditions for a traffic stream in a communication network are applied to modify an initial congestion window size for the traffic stream; and dynamic bandwidth control is thereafter applied to the traffic stream. This dynamic bandwidth control may include modulating inter-packet bandwidths of the traffic stream according to a capacity of a bottleneck in a communication path through which the traffic stream passes in the communication network. The predictions of congestion conditions may be based on monitoring packet losses and/or round trip times within the communication network for a selected period of time. The monitoring may be performed on at least one of a traffic stream-by traffic stream basis, a connection-by-connection basis, a link-by-link basis, or a destination-by-destination basis.

Abstract: Packet round trip times (RTT) within a communication network are measured and from those measurements information regarding congestion conditions within the network is extracted. The RTT measurements are organized into an invariant distribution (a histogram) and an analytical tool which is designed to reveal periodicity information (such as a Fourier or wavelet transform, etc.) is applied to the distribution to obtain a period plot. From this period plot, bandwidth information (indicative of the congestion conditions and/or link capacities within the network) can be obtained.

Abstract: A method of self-testing includes transmitting a plurality of self-test signals and receiving the plurality of self-test signals. In addition, the method includes storing the received self-test signal in a first database; and comparing the received self-test signal with data from a second database. An self-testing apparatus and a method of for assuring substantially continued calibrated function of a testing device.

Abstract: Congestion within a traffic stream of interest in a communication network is characterized as self-induced congestion or cross-induced congestion by analyzing a correlation result of a time series of throughput data of the traffic stream of interest and making the characterization based on power spectrum features found in the correlation result. The correlation result may be obtained through a Fourier analysis, a wavelet analysis or any mathematical process based on locating periodicities in the time series. In some cases, the characterization is made at a node in the communication network that is downstream from the congestion, while in other cases, the characterization is made at a node in the communication network that is upstream of the congestion.

Abstract: Congestion within a communication is controlled by rate limiting packet transmissions over selected communication links within the network and modulating the rate limiting according to buffer occupancies at control nodes within the network. Preferably, though not necessarily, the rate limiting of the packet transmissions is performed at an aggregate level for all traffic streams utilizing the selected communication links. The rate limiting may also be performed dynamically in response to measured network performance metrics; such as the throughput of the selected communication links input to the control points and/or the buffer occupancy level at the control points. The network performance metrics may be measured according to at least one of: a moving average of the measured quantity, a standard average of the measured quantity, or another filtered average of the measured quantity.

Abstract: Predictions of congestion conditions for a traffic stream in a communication network are applied to modify an initial congestion window size for the traffic stream; and dynamic bandwidth control is thereafter applied to the traffic stream. This dynamic bandwidth control may include modulating inter-packet bandwidths of the traffic stream according to a capacity of a bottleneck in a communication path through which the traffic stream passes in the communication network. The predictions of congestion conditions may be based on monitoring packet losses and/or round trip times within the communication network for a selected period of time. The monitoring may be performed on at least one of a traffic stream-by traffic stream basis, a connection-by-connection basis, a link-by-link basis, or a destination-by-destination basis.

Abstract: Congestion within a traffic stream of interest in a communication network is characterized as self-induced congestion or cross-induced congestion by analyzing a correlation result of a time series of throughput data of the traffic stream of interest and making the characterization based on power spectrum features found in the correlation result. The correlation result may be obtained through a Fourier analysis, a wavelet analysis or any mathematical process based on locating periodicities in the time series. In some cases, the characterization is made at a node in the communication network that is downstream from the congestion, while in other cases, the characterization is made at a node in the communication network that is upstream of the congestion.

Abstract: Congestion within a communication is controlled by rate limiting packet transmissions over selected communication links within the network and modulating the rate limiting according to buffer occupancies at control nodes within the network. Preferably, though not necessarily, the rate limiting of the packet transmissions is performed at an aggregate level for all traffic streams utilizing the selected communication links. The rate limiting may also be performed dynamically in response to measured network performance metrics; such as the throughput of the selected communication links input to the control points and/or the buffer occupancy level at the control points. The network performance metrics may be measured according to at least one of: a moving average of the measured quantity, a standard average of the measured quantity, or another filtered average of the measured quantity.