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: An optimizer process in a storage system automatically selects access activity data for storage devices in the system during periods of interest so that a volume-swapping optimization analysis is based on desired device performance information and thus yields improved optimization results. For each of a number of sampling intervals in an analysis period, workload statistics are collected for logical volumes in the system. From the workload statistics, a service time is calculated for each storage device for each sampling interval. A set of highest service times is identified from the service times for each device, such as those above the 80th percentile, and a service time measure is generated from the set of highest service times.

Abstract: During sampling intervals, pairs of swap scores are assigned to respective pairs of storage devices of a storage system, each swap score pair indicating an amount of system performance improvement for a swap of logical volumes between source and target storage devices of the pair of storage devices. The swap scores are summed over all the intervals. A subset of the storage devices are then selected for a full optimization process based on the summed swap scores, where the full optimization process exhaustively looks for some number of best swaps among the storage devices to improve system performance. By choosing the size of the subset of storage devices, the processing burden required to perform the analysis will be in line with the processing capacity of the processing platform on which the analysis is performed, while achieving system performance improvement commensurate with a worst-case process in which every storage device in the system is analyzed for candidate swaps.

Abstract: Restricting access to a device includes obtaining a passphrase for a user, obtaining access credentials for the user, obtaining a PIN value for the user, one-way encrypting at least the access credentials and the PIN using a secret key provided with the device. The user is allowed access to the device if the result of one-way encrypting equals the passphrase. The user is denied access to the device if the result of one-way encrypting does not equal the passphrase. The device may be a storage device. The access credentials may include a username that identifies the user and may include a role for the user. The access credentials may include a time period for which access is allowed. Access may be subsequently revoked in response to the current date and time being greater than the time period for which access is allowed.

Abstract: In a selective logical-volume swapping process, a subset of storage devices in a storage system are selected that represent good candidates for swaps that will improve system performance. Workload statistics are utilized from a number of sample intervals in a relatively long analysis interval. The workload statistics are aggregated over intermediate intervals of each analysis interval to yield a set of aggregated statistics much smaller than the set of workload statistics. Based on the aggregated statistics, a service processor searches for swaps of logical volumes, ranks the swaps according to expected system performance improvement, and selects source and target storage devices of the higher-ranked swaps. The service processor can then perform a full optimization analysis for this subset of storage devices utilizing the workload statistics from all the sample intervals.

Abstract: In an optimization dispatch process for a storage system, M storage devices are identified for an optimization analysis process to be executed to identify logical volume swaps for improving system performance. The M storage devices are identified by merging candidate storage devices obtained from separate identification algorithms employing distinct identification criteria. The analysis process is dispatched for execution based on the M storage devices until (i) a successful completion upon which a best swap has been identified, or (ii) a resource-based stop condition such as an execution time limit. M is adjusted for a subsequent iteration such that over time a desired rate of successful completions is achieved. For example, M is increased by a first amount upon a successful completion and decreased by a second amount upon the stop condition.

Abstract: A method for providing data indicative of the performance of a competing algorithm and an incumbent algorithm includes evaluating an incumbent-algorithm score indicative of a performance of an incumbent algorithm. The performance of a competing algorithm executing in place of the incumbent algorithm is then simulated. On the basis of the simulation, a competing-algorithm score predictive of a performance of the competing algorithm is evaluated. These scores are then provided to an output device.

Abstract: Described are techniques for performing compression and decompression of statistical data. This data may be used in connection with performing optimizations. A delta value for each statistic is determined representing a difference between a current value and a previous value. Delta values are stored in a statistics table in a compressed form using a monotonic compression scheme. Small tables are used to determine decompressed values estimating the observed values. Statistical information is stored and represented in a statistics table and an events table. Statistical information is selectively fetched and loaded into memory from a storage device. Indexing techniques are used to force physical continuity of the rows of the statistics table on a storage device in accordance with a specified retrieval order.

Abstract: A method for storage and manipulation of storage system metrics incorporates a self-describing format wherein each data file includes a header block that contains the description and order of the periodic data. The header block is followed by a data block in which the data items are presented in the order that they appear in the data description block for that category. Two types of data are managed, including Base Metrics and Derived Metrics. Base Metrics are metrics that appear in the data file sent by an agent. Derived Metrics are computed based on a set of functions that derive new metrics from the base metrics as well as from previously defined derived metrics. A subset of the data block or file describes the configuration of the storage system at the time that the data file was created. Thus the data file contains a header section that in addition to describing the metrics also describes the configuration.

Abstract: A seek minimizing process for use in storage controller of a data storage system is presented. The process collects statistics for physical devices storing mirrored logical volumes. The statistics include utilization and activity level. The process determines from the statistics the top n busiest physical devices. The process evaluates each of the n physical devices for mirror policy adjustment that will result in reduced seek time when the utilization of the physical device is greater than a threshold, for example, 50%.

Abstract: A data management and archive method and apparatus, such as for implementation in an automated system to monitor and manage status, performance and configuration data for a plurality of networked storage components. Analysis and cross-correlation of data related to the plurality of storage components can be done individually, collectively and/or comparatively. A collection manager component of a workload analyzer is implemented to start and stop data collection in the context of a system comprising at least one storage component (or at least two networked storage components). The collection manager includes a command and control module that coordinates requests of data from at least one collection agent configured on at least one host connected to the storage component(s).

Abstract: A data management and archive method and apparatus, such as for implementation in an automated system to monitor and manage status, performance and configuration data for a plurality of networked storage components. Analysis and cross-correlation of data related to the plurality of storage components can be done individually, collectively and/or comparatively. A collection manager component of a workload analyzer is implemented to start and stop data collection in the context of a system comprising at least one storage component (or at least two networked storage components). The collection manager includes a command and control module that coordinates requests of data from at least one collection agent configured on at least one host connected to the storage component(s). The collection manager manages collection of data and effects file transfer of collected data according to a user specified policy, and maintains status of the data collected.

Abstract: Described are techniques for performing compression and decompression of statistical data. This data may be used in connection with performing optimizations. A delta value for each statistic is determined representing a difference between a current value and a previous value. Delta values are stored in a statistics table in a compressed form using a monotonic compression scheme. Small tables are used to determine decompressed values estimating the observed values when information is retrieved for use to within a predetermined relative error. Statistical information is stored and represented in a statistics table and an events table. Statistical information is selectively fetched and loaded into memory from a storage device. Indexing techniques are used to force physical continuity rows of the tables in accordance with a specified retrieval order.

Abstract: A prefetch process that generates prefetch tasks for short sequences that are no longer than n tracks in length. The value of n is selected as 8. The prefetch process maintains a history of short sequences, uses that history to predict an expected length of a current sequence and generates a short prefetch task based on that prediction. The historical short sequence data is stored in histograms, each histogram being associated with a different logical volume. The histograms store a cumulative count of sequence occurrences of a given sequence length for each sequence length in a range of 1 track to n tracks. The process applies a probability-based threshold to its prediction to control the aggressiveness of the prefetch task to be generated. The threshold is adjusted based on system activity level metrics, such as processor utilization and average memory access time.

Abstract: Techniques and criteria are used in connection with promoting a slot within a cache in the form of a replacement queue. A cache slot may be promoted based on an inequality that considers the following criteria: probability of losing a cache hit, gaining a cache hit, and the price or cost associated with promoting a slot. The foregoing criteria may be used in accordance with a predetermined promotion policy when the replacement queue is in a locked state and an unlocked state, or only when the replacement queue is in a locked state. Different costs may be associated with the state of the replacement queue as locked or unlocked as the replacement queue may be locked in connection with operations that are performed on the replacement queue. The cost associated with a locked replacement queue may be different than the cost associated with an unlocked replacement queue. Different thresholds and values associated with the foregoing criteria may be specified as dynamic system parameters.