International Business Machines Corporation

Pure Storage, Inc.

Ilir Iljazi

Jason K Resch

Andrew D Baptist

Greg R Dhuse

Kumar Abhijeet

Gregory A Papadopoulos

Ethan S Wozniak

Niall John McShane

A computing device includes an interface configured to interface and communicate with a storage network (SN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. Based on a detected storage error, the computing device is configured to determine availability status of encoded data slices (EDSs) within a set of EDSs. When at least a decode threshold number of EDSs are available, the computing device is configured to initiate a rebuilding function to abate the detected storage error. When less than a decode threshold number of EDSs are available, the computing device is configured to initiate a data recovery function for at least one storage unit (SU) to abate the detected storage error.

Data recovery in a distributed storage network

A method for execution by a storage network begins by creating a plurality of vaults in memory addressable by the storage network, where a vault is a virtual memory block associated with a portion of storage network memory, and then determining dispersed storage error encoding parameters for each vault. The method then continues by creating a plurality of vault regions within each vault, wherein a vault region is configured to store a data type of a plurality of data types, where at least one data type of the plurality of data types is associated with a unique access restriction.

Creating and using virtual memory blocks in a storage network

A method for execution by a storage network begins by issuing a decode threshold number of read requests for a set of encoded data slices to a plurality of storage units of a set of storage units and continues by determining whether less than a decode threshold number of read requests has been received in a time window. The method continues by identifying one or more encoded data slices encoded data slices associated with read requests of the decode threshold number of read requests that have not been received and for an encoded data slice of the one or more encoded data slices, issuing a priority read request to a storage unit storing a copy of the encoded data slice. The method then continues by receiving a response from the storage unit storing the copy of the encoded data, where the storage unit storing the copy of the encoded data slice is adapted to delay one or more maintenance tasks in response to the priority read request.

Storage network with enhanced data access performance

A method for execution by a dispersed storage network (DSN) managing unit includes receiving access information from a plurality of distributed storage and task (DST) processing units via a network. Cache memory utilization data is generated based on the access information. Configuration instructions are generated for transmission via the network to the plurality of DST processing units based on the cache memory utilization data.

Allocating cache memory in a dispersed storage network

A computing device includes an interface configured to interface and communicate with a dispersed or distributed storage network (DSN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. The computing device receives first samples corresponding to inputs that characterize configuration of the DSN and receives second samples corresponding to outputs that characterize system behavior of the DSN. The computing device then processes the first and samples to generate a DSN model to generate predictive performance of the outputs based on various values of the inputs. In some instances, the DSN model is based on a neural network model that employs the inputs that characterize the configuration of the DSN and generates the outputs that characterize system behavior of the DSN.

Distributed storage network (DSN) configuration adaptation based on estimated future loading

A method for execution by a dispersed storage and task (DST) execution unit identifying a failing memory device based on memory device diagnostic data. A cloning task is executed by designating memory of a replacement memory device to store encoded slices stored in the failing memory device, where the cloning task is executed over a cloning duration time period. A write request is received via a network at a receiving time during the cloning duration time period that includes a new encoded slice, and the new encoded slice is assigned to a temporary memory device for storage based on an identifier of the new encoded. The new encoded slice is transferred from the temporary memory device to the replacement memory device in response to an elapsing of the cloning duration time period corresponding to completion of the execution of the cloning task.

Cloning failing memory devices in a dispersed storage network

A computing device includes an interface configured to interface and communicate with a dispersed storage network (DSN), a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. Based on a detected storage error, the computing device is configured to determine availability status of encoded data slices (EDSs) within a set of EDSs. When at least a threshold number of EDSs are available, the computing device is configured to initiate a rebuilding function to abate the detected storage error. When less than the threshold number of EDSs are available, the computing device is configured to initiate a slice repair function to at least one storage unit (SU) to abate the detected storage error.

External healing mode for a dispersed storage network memory

A method for a dispersed storage network (DSN) begins by determining an I/O (input/output) capacity of a storage level of DSN memory. The method continues by determining a required performance level to meet operational demands of services operating at the storage level. The method continues by setting a storage level throttle rate based on the I/O capacity and the required performance level and determining a remaining I/O performance of the DSN memory to be allocated to a higher storage level.

Throttling access requests at different layers of a DSN memory

A dispersed storage network (DSN) includes multiple storage units. A processing unit included in the DSN issues an access request to one of the storage units, and identifies the storage unit as a failing storage unit based, at least in part, on a rate of growth of a network queue associated with the storage unit. the processing unit then issues an error indicator to a recovery unit for further action.

Automated stalled process detection and recovery

Developing an accurate dispersed storage network memory performance model through training

A method begins with requesting access to a dispersed storage (DS) processing unit. The method continues by receiving, based on available access permits of the DS processing unit, an error indication denying access to the DS processing unit. The method continues by retrieving from a public directory a number of available access permits for a plurality of other DS processing units. The method continues by determining which of the other DS processing units have a plurality of available access permits and reissuing the access request to at least one of the other DS processing units.

Global access permit listing

A method begins by communicating memory management information between a dispersed storage (DS) management unit and a plurality of DS execution units. The method continues by generating, by the DS management unit, managing use information. The method continues by sending the managing use information to a DS optimization unit. The method continues by receiving from the DS optimization unit optimization information based on an analysis of the sent managing use information. The method continues by updating a DS management unit managing approach based on the received optimization information.

System for collecting end-user feedback and usability metrics

Handling failing memory devices in a dispersed storage network

An auto indexing method includes identifying a vault of a dispersed storage network for an auto indexing function. The method continues by obtaining search criteria for the auto indexing function. The method further includes scanning the plurality of metadata files to identify metadata files of the plurality of metadata files having at least one of the objective metadata and the subjective metadata corresponding to the search criterion. The method further includes updating an index file that includes the identity of the one or more metadata files of the plurality of metadata files having the at least one of the objective metadata and the subjective metadata corresponding to the search criterion and updating an index structure based on the index file. The method further includes utilizing the index structure to search for one or more data objects having one or more of the search criterion of the search criteria.

Auto indexing with customizable metadata

Methods for assigning data storage resources are disclosed. The methods includes obtaining memory resource availability information for a plurality of physical memory devices of a dispersed storage network, determining a number of logical storage units for the dispersed storage network, determining a memory capacity level for each of the logical storage units, determining a mapping in accordance with a mapping approach of at least some of the plurality of physical memory devices to achieve a corresponding memory capacity level, and when accessing encoded data slices associated with the logical storage unit by an accessing entity, communicating slice access messages with a dispersed storage unit associated with the logical storage unit. A dispersed storage managing unit and dispersed storage network are also disclosed.

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Chicago, IL, United States of America

Ilir Iljazi