International Business Machines Corporation

Other

Yu-Cheng Hsu

Cheng-Chung Song

Michael T Benhase

Lawrence Yiumchee Chiu

John Norbert McCauley

Michael Howard Hartung

Stephen LaRoux Blinick

William Griswold Sherman

David Frank Mannenbach

Glenn Rowan Wightwick

Lokesh M Gupta

Andrew Dale Walls

Richard Anthony Ripberger

Sandeep R Patil

Matthew J Kalos

Kevin J Ash

William Joseph Armstrong

Sasikanth Eda

Joseph S Hyde, Ii

Sangeetha Seshadri

Paul Henri Muench

Deepak R Ghuge

Alfred Emilio Sanchez

Harry M Yudenfriend

Evangelos Stavros Eleftheriou

Roman Alexander Pletka

John Charles Elliott

Carl Evan Jones

David Darden Chambliss

Robert Haas

Shachar Fienblit

Sridhar R Muppidi

James Alan Ruddy

Vernon John Legvold

Chiahong Chen

Carol Spanel

Scott A Brewer

Lee Dale Cleveland

Clement Lambert Dickey

Lucien Mirabeau

Ricky Dean Rankin

Renato John Recio

Hubertus Franke

Joseph W Dain

Chung-Sheng Li

Ioannis Koltsidas

Pratap Chandra Pattnaik

David Bruce Lindquist

Susan Kay Candelaria

Jeffrey Alan Frey

Timothy Roy Block

Matt Richard Hogstrom

Robert Frederic Kern

Nagui Halim

Louis Alonso Rasor

James Chien-Chiung Chen

Brad L Brech

Piyush Chaudhary

Michael P Vageline

Michael D Williams

Dilip Dinkar Kandlur

Minh-Ngoc Le Huynh

Xiao-yu Hu

Juan J Ruiz

Scott W Crowder

Michael John Jones

Balachandar Rajaraman

Xiaoyu Hu

Smita J Raut

Richard B Stelmach

Gilad Sharaby

Radha P Ratnaparkhi

Sean Patrick Riley

Shajeer K Mohammed

Rodney A Smith

William Garrett Verdoorn, Jr

Stefan Pappe

Frank N Lee

James Alan Springer, Sr

Pratik Gupta

Erin M Farr

Aaron S Mahar

Angelique R Budaya

Herve Gilbert Philippe Andre

William G Verdoom, Jr

James Chien-Chung Chen

A computer-implemented method, according to one approach, includes: receiving, at an edge computing environment, internet of things (IoT) data generated by IoT devices in communication with the edge computing environment. One or more inference models are used at the edge computing environment to: classify the IoT data, and generate labeled metadata for the classified IoT data. The labeled metadata is further used at the edge computing environment to identify portions of the IoT data to transmit to a cloud computing environment. Copies of the identified portions of the IoT data are also sent to the cloud computing environment.

Metadata based data distribution

An embodiment identifies a fileset used by an executing application. An embodiment generates, at a first time, a first snapshot of the fileset, the first snapshot comprising a first state of the fileset at the first time and a first indicator corresponding to the first state of the fileset. An embodiment selects, at a recovery time later than the first time, from a sequence of snapshots of the fileset including the first snapshot, a recovery snapshot, the recovery snapshot comprising a recovery indicator, wherein the recovery indicator has a difference from the first indicator that is higher than a threshold value. An embodiment restores, using the recovery snapshot, the fileset to a state other than the first state, the restoring resulting in a restored application.

Application dependency based malware recovery

A computer-implemented method, according to one embodiment, includes: determining, for each pair of HCI systems where each pair includes a first HCI system coupled to another HCI system, a federation relationship setting that corresponds to each pair. The federation relationship settings are used to control a flow of data, as well as to control a flow of workload scheduling, between the first HCI system and the other HCI systems in the respective pairs. Moreover, determining a federation relationship setting that corresponds to a pair includes: determining whether a risk score which corresponds to the pair is outside a predetermined range. In response to determining that the risk score is outside the predetermined range, a restrictive federation relationship setting is assigned to the pair, and in response to determining that the risk score is not outside the predetermined range, a permissive federation relationship setting is assigned to the pair.

Utilizing federation relationship settings among different systems

A computer-implemented method, according to one approach, includes: monitoring actions of a user having access to a cluster, and in response to determining that the user has performed a risk event, incrementing a risk score assigned to the user. A determination is also made as to whether the incremented risk score is outside a predetermined range, and in response to determining that the incremented risk score is outside the predetermined range, a snapshot quota assigned to the user is dynamically reduced.

Dynamically throttling snapshot capture rates

A first logical partition in a first processing complex of a server cluster is operated in an active mode and a second logical partition in the processing complex is operated in a standby mode. Upon detection of a failure in a second processing complex of the server cluster. the standby mode logical partition in the first processing complex is activated to an active mode. In one embodiment, partition resources are transferred from an active mode logical partition to the logical partition activated from standby mode. Other embodiments are described and claimed.

Cluster availability management

An efficient cloning mechanism is provided for a distributed storage environment, where, for example, a private cloud computing environment and a public cloud computing environment are included in a hybrid cloud computing environment (on-premise object storage to off-premise computation resources), to improve computation workloads. The disclosed algorithm forms an efficient cloning mechanism in a hybrid storage environment where the read/write speed of data from the disk is not limited by its angular velocity.

Clone efficiency in a hybrid storage cloud environment

Provided are a method, system, and computer program product for processing read and write requests in a storage controller. A host adaptor in the storage controller receives a write request from a host system for a storage address in a storage device. The host adaptor sends write information indicating the storage address updated by the write request to a device adaptor in the storage controller. The host adaptor writes the write data to a cache in the storage controller. The device adaptor indicates the storage address indicated in the write information to a modified storage address list stored in the device adaptor, wherein the modified storage address list indicates modified data in the cache for storage addresses in the storage device.

Processing read and write requests

There is a method and system for capability-based resource allocation in a software-defined environment that performs the following steps (not necessarily in the following order): (i) determining a set of capability characteristics for a plurality of workload resources within a software-defined environment; (ii) determining a set of workload components for a specified workload; and (iii) identifying a set of workload resources from the plurality of workload resources to allocate to the specified workload based, at least in part, on the set of capability characteristics corresponding to each workload within the set of workload resources. A workload component of the set of workload components has a unique set of workload characteristics.

Capability-based abstraction of software-defined infrastructure

An I/O enclosure module is provided with one or more I/O enclosures having a plurality of slots for receiving electronic devices. A host adapter is connected a first slot of the I/O enclosure module and is configured to connect a host to the I/O enclosure. A device adapter is connected to a second slot of the I/O enclosure module and is configured to connect a storage device to the I/O enclosure module. A flash cache is connected to a third slot of the I/O enclosure module and includes a flash-based memory configured to cache data associated with data requests handled through the I/O enclosure module. A primary processor complex manages data requests handled through the I/O enclosure module by communicating with the host adapter, device adapter, and flash cache to manage to the data requests.

Integrating a flash cache into large storage systems

Processing read and write requests in a storage controller

A method for managing cache memories includes providing a computerized system including a shared data storage system (CS) configured to interact with several local servers that serve applications using respective cache memories, and access data stored in the shared data storage system; providing cache data information from each of the local servers to the shared data storage system, the cache data information comprising cache hit data representative of cache hits of each of the local servers, and cache miss data representative of cache misses of each of the local servers; aggregating, at the shared data storage system, at least part of the cache hit and miss data received and providing the aggregated cache data information to one or more of the local servers; and at the local servers, updating respective one or more cache memories used to serve respective one or more applications based on the aggregated cache data information.

Managing cache memories

Mechanisms are provided for extending cache for an external storage system into individual servers. Certain servers may have cards with cache in the form of dynamic random access memory (DRAM) and non-volatile storage, such as flash memory or solid-state drives (SSDs), which may be viewed as actual extensions of the external storage system. In this way, the storage system is distributed across the storage area network (SAN) into various servers. Several new semantics are used in communication between the cards and the storage system to keep the read caches coherent.

Extending cache for an external storage system into individual servers

Growing community of inventors

Tucson, AZ, United States of America

Yu-Cheng Hsu