International Business Machines Corporation

Lior Shlomov

Ariel Waizel

Ronen Gazit

Ron S Shapiro

Ofer Leneman

Michael Keller

Osnat Shasha

Guy-Arie Yur

Jonathan Amit

Danny Harnik

Sergey Marenkov

Chaim Koifman

Orit Nissan-Messing

Dmitry Sotnikov

Ehood Garmiza

Jonathan Fischer-Toubol

Afief Halumi

Assaf Yaari

Shai Taharlev

Nir Friedman

Provided are a computer program product, system, and method for generating master and wrapper keys for connected devices in a key generation scheme. For each of the devices, a wrapped master key comprising a master key for the device and a wrapper key is stored. The wrapper keys for a plurality of the devices are generated by another of the devices. For each of a plurality of the devices, the master key for the device is used to generate the wrapper key for a target device comprising another of the devices. For each of the devices, the wrapper key for the device is used to decrypt the stored wrapped master key. At least one of the devices uses the master key for the device to encrypt and decrypt data at the device.

Generating master and wrapper keys for connected devices in a key generation scheme

Provided are a computer program product, computer system, and method for smart selection of a storage module to be excluded when a connection between two storage modules is broken. An indication is received from a first storage module that a connection between the first storage module and a second storage module is broken. In response to determining that the second storage module is accessible, values of exclusion criteria for the first storage module are determined and summed to identify a first exclusion total. Then, values of exclusion criteria for the second storage module are determined and summed to identify a second exclusion total. In response to determining that the first exclusion total exceeds the second exclusion total, the second storage node is excluded from the cluster. In response to determining that the second exclusion total exceeds the first exclusion total, the first storage node is excluded from the cluster.

Smart selection of a storage module to be excluded

Methods, computing systems and computer program products implement embodiments of the present invention that include configuring a storage system to store multiple storage entities for access by one or more host computers in communication with the storage system, and specifying a compression condition including a minimum compression ratio. The storage system can then estimate an expected compression ratio for a given storage entity, compress the given storage entity upon the expected compression ratio meeting the compression condition, and provide, to a given host computer, access to the compressed given storage entity.

Storage data reduction analysis and forecast

Methods, computing systems and computer program products implement embodiments of the present invention that include configuring multiple storage system resources to manage a storage entity distributed among the storage system resources. Upon receiving, by a first given storage system resource from a host computer, an I/O request for data in the storage entity, a second given storage system resource responsible for managing the storage entity data referenced in the I/O request is identified, and the I/O request is forwarded to the second given storage system resource. Upon receiving the forwarded I/O request, the second given storage system resource performs a data compression operation while processing the I/O request, and conveys a result of the I/O operation to the first given storage system resource. Upon receiving the result from the second given storage system resource, the first given storage system resource forwards the result to the host computer.

Data compression for grid-oriented storage systems

Methods, computing systems and computer program products implement embodiments of the present invention that include configuring, at a first time, a clustered storage system comprising multiple modules to store and process storage requests for respective sets of data objects. While processing the storage requests, respective subsets of the data objects having one or more data errors are identified, and at a second time subsequent to the first time, respective modules storing each of the data objects having at least one data error are identified. computing, based on the identified modules, a frequency distribution of the identified data errors in the data objects over the multiple modules. Based on the frequency distribution, a failure in a given module is identified, and the identified module is removed from the storage system. In some embodiments, prior to the second time, the data objects can be redistributed among the modules of the storage system.

Isolating faulty components in a clustered storage system with random redistribution of errors in data

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Or Yehuda, Israel

Lior Shlomov