International Business Machines Corporation

Sasikanth Eda

Sandeep R Patil

Deepak R Ghuge

Abhishek Jain

John Thomas Olson

Duane Mark Baldwin

Sachin Chandrakant Punadikar

William W Owen

Gandhi Sivakumar

Smita J Raut

Dean Hildebrand

Subhojit Roy

Manojkiran Eda

Pradipta Kumar Banerjee

Anbazhagan Mani

John Gerard Musial

Akshat Mithal

Kaustubh I Katruwar

Varun Mittal

Sarbajit Kumar Rakshit

Riyazahamad Moulasab Shiraguppi

Poornima Gupte

Peter A Balinski

Abhishek Dave

Sanjay Vipin Gandhi

Nataraj Nagaratnam

Yu-Cheng Hsu

Shah M R Islam

Brian Nelson

Trishali Satish Nayar

Karthik Iyer

Huzefa Pancha

Sukumar Vankadhara

Anil Laxman Palled

Rajan Dilavar Mithani

Pushkaraj Balasaheb Thorat

Sandeep Naik

Ashutosh V Mate

Lydia Mai Do

Christina Ann Lara

Ashish Pandey

Asmahan A Ali

Dileep Dixith

Ranjith R Nair

Amey P Gokhale

Shekhar Amlekar

Sanjay K Sudam

Ashwin M Joshi

Prayas Gupta

Digvijay Ukirde

Sridhar Puvvala

Nils Haustein

Sarvesh S Patel

Kushal S Patel

Pamela Ann Nesbitt

Krishnasuri Narayanam

Faried Abrahams

Sridhar R Muppidi

Rahul M Fiske

Dominic Mueller-Wicke

Phani Kumar V U Ayyagari

Wei Gong

Venkateswara Rao Puvvada

Guang Ya Liu

Gautam H Shah

Muthu Annamalai Muthiah

Piyush Sarwal

Archana Ravindar

Asmahan Ali

Aakanksha Mathur

Pravin Kailas Mahajan

Vikrant Malushte

Ramakrishna Vadla

Rezaul S Islam

Ravindra R Sure

Chhavi Agarwal

Samrat P Kannikar

Shailesh S Jeurkar

Shashank Shingornikar

Rahul Rahul

Mustafa Mah

Kumaran Rajaram

Sivakumar Gandhi

Karve Shrikant Vinod

Brijesh Chougule

Provided is a computer-implemented method, system, and computer program product for predictive service orchestration using threat modeling analytics. A processor may identify a plurality of attributes of a client computing environment. The processor may collect threat modeling content for a plurality of vendor computing environments. The processor may analyze the threat modeling content for the plurality of vendor computing environments. The processor may compare the analyzed threat modeling content for the plurality of vendor computing environments with the plurality of attributes of the client computing environment. The processor may generate, based on the comparing, a client threat model for the client computing environment.

Predictive service orchestration using threat modeling analytics

A method for more efficiently storing genomic includes designating multiple different data storage techniques for storing genomic data generated by a genomic pipeline. The method further identifies a file, made up of multiple blocks, generated by the genomic pipeline. The method determines which data storage technique is most optimal to store each block of the file. In doing so, the method may consider the type of the file, the stage of the genomic pipeline that generated the file, the access frequency for blocks of the file, the most accessed blocks of the file, and the like. The method stores each block using the data storage technique determined to be most optimal after completion of a designated stage of the genomic pipeline, such that blocks of the file are stored using several different data storage techniques. A corresponding system and computer program product are also disclosed.

Hybridized storage optimization for genomic workloads

A computer-implemented method for provisioning cloud computing clusters includes receiving a request to create a cloud computing cluster, the cloud computing cluster comprising a clustered filesystem and a requested number of processing nodes and attached storage devices associated with the cloud computing cluster and initiating an initialization process for a single processing node and a corresponding attached storage device responsive to receiving the request to create the cloud computing cluster. The method may also include, previous to completion of the initialization process, requesting and receiving an IP address for the single processing node and a device ID for the corresponding attached storage device from one or more cloud infrastructure controllers and configuring the clustered filesystem and a corresponding WAN cache using the received IP address and the received device ID. A system and computer program product corresponding to the above method are also disclosed herein.

Increasing resource utilization in cloud computing clusters

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 method for assigning and migrating files among tiers within a unified storage environment. The method includes one or more computer processors determining a plurality of files stored within a tiered storage environment that are accessed by a set executing applications. The method further includes determining that one or more files of the plurality of files are accessed utilizing two or more protocols. The method further includes identifying a group of two or more tiering policies utilized within a tiered storage environment. The method further includes determining protocol-based heat count values corresponding the plurality of files. The method further includes storing the plurality of files among tiers of the tiered storage environment based on the identified group of two or more tiering polices and the protocol-based heat count values corresponding to the plurality of files.

Storage tiering within a unified storage environment

This is an approach to the prediction of soil density and subsoil crop growth. The approach may include subsoil sensor which can monitor changes in soil pressure and moisture conditions. The sensor data can be sent to a computer module which can process the data using a machine learning model predicting the soil density around a subsoil crop and the yield of the subsoil crop. A soil maintenance plan can be generated from the soil density prediction and/or the crop yield prediction. The soil maintenance plan can be sent to soil management robots, which can execute the soil maintenance plan.

Soil density prediction for subsoil crops

A computer-implemented method according to one aspect includes determining and storing characteristics of a plurality of cloud vendors; dividing a workload into a plurality of logical stages; determining characteristics of each of the plurality of logical stages; and for each of the plurality of logical stages, assigning the logical stage to one of the plurality of cloud vendors, based on a comparison of the characteristics of the plurality of cloud vendors to the characteristics of the logical stage. Data migration between the cloud vendors is performed during an implementation of the workload to ensure data is located at necessary cloud vendors during the corresponding tasks of the workload.

Implementing workloads in a multi-cloud environment with data migration between cloud vendors

A computer-implemented method, according to one embodiment, includes: receiving, at a clustered filesystem from a formatted filesystem, a request to perform a data integrity check for a portion of data. A determination is made as to whether the request includes a filesystem type of the portion of data, and in response to determining that the request includes a filesystem type of the portion of data, another determination is made as to whether the clustered filesystem supports the data integrity check for the filesystem type. In response to determining the clustered filesystem supports the data integrity check, another determination is made as to whether the portion of data is currently available. Furthermore, the computer-implemented method includes causing the data integrity check to be performed in response to determining that the portion of data is currently available. Results of performing the data integrity check are also sent to the formatted filesystem.

Deduplicating data integrity checks across systems

Disclosed are techniques for programmatically mapping workloads for storage in different classes of a networked computer data storage environment, using a set of rules or data storage hints and properties of the workloads themselves. With the set of data storage hints, metadata sets are assigned to files of the incoming workloads to the networked computer data storage environment based on the properties of the workloads. Then, a target storage class is determined for each file of the workload from the plurality of storage classes present in the networked computer data storage environment. The workload files are then mapped to a logical bucket that is associated with the plurality of storage classes through a shared namespace, with the assigned metadata set for a file cueing the filesystem modules as to which storage class within the logical bucket to direct the various files of the workload to.

Programmatically mapping workloads to networked object storage

Embodiments of the present invention determine a curiosity of a user based on data received from an electronic device associated with the user, where the data includes audible speech captured from user and one or more facial expressions of the user. Embodiments of the present invention identify a first wavelength for audible speech from the user to initiate a command detection mode based on a plurality of wavelengths associated with a user profile for the user. Embodiments of the present invention identify a topic for the audible speech from the user and responsive to determining an intelligent virtual assistant is an intended recipient based on the topic, suspend an activation word for the intelligent virtual assistant.

Curiosity based activation and search depth

A computer-implemented method according to one embodiment includes determining patterns of an application that utilizes a filesystem and/or properties of queries of the application. Data of the filesystem is stored across a plurality of replication sites of a data storage system. Based on the determined patterns of the application and/or the determined proper-ties of the queries of the application, a utility of storing at least some of the data of the filesystem in different variations at more than one of the replication sites is estimated. The estimated utility is compared against a predetermined utility threshold, and in response to a determination that the estimated utility is greater than the predetermined utility threshold, a write system call offered by the filesystem is modified to store the data in different variations at more than one of the replication sites.

Storing variations of data across different replication sites

Provided is a method for performing a file system consistency check. The method comprises calculating, by a first thread that does not have access to an inode table, file block addresses for one or more files to be checked by the thread. The method further comprises collecting validity information for the one or more files. The method further comprises reading information relating to the one or more files from the inode table. The reading is performed in response to the thread being given access to the inode table after the calculating operation. The method further comprises validating the information by comparing the information from the inode table to the validity information.

Reducing file system consistency check downtime

A computational device configures a storage system that supports a plurality of submission queues. A file system monitors characteristics of received writes to distribute the writes among the plurality of submission queues. The computational device categorizes the writes into full track writes, medium track writes, and small track writes, measures a frequency of different categories of writes determined based on the categorization of the writes, and generates arbitrations of the writes with varying priorities for distributing the writes for processing in the submission queues. A full track write includes writing incoming data blocks of the writes received to a fresh track, in response to a total size of the incoming data blocks being equal to or more than a size of one full track. A medium track write includes overwriting an existing data track. A small track write includes staging the incoming data blocks to a caching storage.

File system operations for a storage supporting a plurality of submission queues

A method for managing commands utilizing command boundaries includes establishing a first command boundary for a first intelligent virtual assistant operating on a first electronic device. The method also includes, responsive to receiving audio from a plurality of sources within a vicinity of the first electronic device, identifying a portion of the audio from the plurality of sources within the first command boundary. The method also includes, responsive to determining a command is identifiable in the portion of the audio from the plurality of sources within the first command boundary, sending the command to the first intelligent virtual assistant on the first electronic device.

Operational command boundaries

A data storage system has multiple tiers of data storage including an upper tier having a lower access latency and a lower tier having a higher access latency. A storage controller of the data storage system receives, via an interface, an access request of a workload for a target file system object, where the target file system object has an associated temperature. In response to the access request for the target file system object, the storage controller accesses the target file system object in the data storage and conditions update of the associated temperature of the target file system object based on at least one of a set including the interface and the workload. The storage controller distributes a collection of file system objects including the target file system object among the multiple tiers based on respective heats of file system objects in the collection.

Workload and interface cognizant heat-tiered storage

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Vijayawada, India

Sasikanth Eda