Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification. One example operation may comprise one or more of identifying an updated software build, creating a hash based on the updated software build, storing the hash of the updated software build in a blockchain, and storing a binary representation of the updated software build in a distributed hash table (DHT).

Abstract: A virtual blockchain configuration may provide a distributed structure that uses a distributed hash configuration to reduce the complexity of blockchain transactions. One example method of operation may comprise one or more of storing a subset of blockchain data in a network device, accessing via the network device a virtual copy of a blockchain, accessing a blockchain block via the virtual copy of the blockchain, and writing blockchain transactions to the blockchain block via the network device.

Abstract: A method and associated systems for a workload-aware thin-provisioning system that allocates physical storage to virtual resources from pools of physical storage volumes. The system receives constraints that limit the amount of storage that can be allocated from each pool and the total workload that can be directed to each pool. It also receives lists of previous workloads and allocations associated with each volume at specific times in the past. The system then predicts future workloads and allocation requirements for each volume by regressing linear equations derived from the received data. If the predicted values indicate that a pool will at a future time violate a received constraint, the system computes the minimum costs to move each volume of the offending pool to a less-burdened pool. It then selects the lowest-cost combination of volume and destination pool and then moves the selected volume to the selected pool.

Abstract: A method and associated systems for optimized orchestration of a data-migration project. A data-migration orchestration system represents a hierarchical organization of each dataset to be migrated as a tree, where each leaf node of the tree represents data to be migrated and where a path between the leaf node and the root node represents a hierarchical directory pathname of sensitive data represented by the leaf node. Each tree is assigned a sensitivity signature that is proportional to the relative sensitivity and access frequency of the dataset represented by that tree. The signatures are organized into clusters as a function of the distances between each signature, and each signature is associated with a soft migration cost specific to that signature's cluster. A soft cost for migrating an application that requires multiple datasets may be determined by adding the migration costs associated with each of the multiple datasets.

Abstract: Methods and arrangements for managing user access to a graph database. Nodes are represented in a graph, along with edges which interconnect the nodes. One or more facts are associated with each of the edges, and an access control list is provided with respect to one or more facts associated with one or more of the edges. There is restricted user access to one or more facts associated with the one or more of the edges, based on the access control list. Other variants and embodiments are broadly contemplated herein.

Abstract: A computer-implemented method according to one embodiment includes identifying a storage volume comprising a plurality of files, calculating a file level input/output operations per second (IOPS) value for each of a subset of the plurality of files within the storage volume, creating a predictive model for the storage volume, using metadata determined for the subset of the plurality of files and the TOPS values calculated for each of the subset of the plurality of files within the storage volume, estimating file level TOPS values for each of the plurality of files in the storage volume, utilizing the predictive model, combining the estimated and calculated file level TOPS values and comparing the combined values to a calculated volume level TOPS value for the storage volume, conditionally adjusting one or more of the estimated file level TOPS values, based on the comparing, and returning the estimated file level IOPS values.

Abstract: A method for distributing data among storage devices. The method comprising one or more processors receiving a first graph workload that executes within a networked computing environment. The method further includes identifying data from the first graph workload that is utilized during the execution of the first graph workload that includes a plurality of data packets. The method further includes creating a first graph workload model representative of the graph structure of the first graph workload and determining two or more partitions that are representative of a distribution of the identified data utilized by the first graph workload based, at least in part, on the first graph workload model. The method further includes allocating a plurality of network accessible storage devices among the two or more partitions and copying a first set of data packets of the plurality of data packets to a network accessible storage device.

Abstract: Embodiments of the invention relate to recovering from a disaster associated with an information technology environment. An information technology environment is replicated to a service provider. A recovery plan is generated for the environment. The recovery plan includes two processes. In response to the service provider receiving a disaster recovery request associated with the environment, the service provider executes a disaster recovery protocol. The protocol includes simultaneously executes the first and second processes. The first process operates a workload in the form of one or more containers, and the second process is a background process that creates a replica of the environment. After completion of the replica creation, the workload is migrated to the replica.

Abstract: A method for performing efficient data sampling across a storage stack for training machine learning (ML) models. The method includes obtaining, by a processor, data. The processor clusters the data into clusters based on similarities of the obtained data across an entire storage stack including: storage infrastructure metrics, file metrics and application dependency taxonomy. The processor performs a random sampling process to sample representative data from each cluster. The sampled representative data are combined to generate training data for processing predictive analytics.

Abstract: According to an aspect, document-based requirement identification and extraction includes parsing a set of documents and identifying relationships among parsed components of the documents and applying the parsed components and identified relationships to a meta-model that defines requirements. The requirements include a statement expressing a need and/or responsibility. A further aspect includes identifying candidate requirements and their candidate topics from results of the applying. For each of the identified candidate topics, a feature vector is built from the corresponding candidate requirements. A further aspect includes training the meta-model with the feature vectors, validating the meta-model, and classifying output of the validating to identify a subset of the candidate requirements, and corresponding topics expressed in the set of documents.

Abstract: A computer-implemented method is provided for predicting cloud enablement from storage and data metrics harnessed from across stack. The computer-implemented method includes identifying a corpus of data to be classified, and configuring at least one access threshold and at least one sensitivity threshold. The computer-implemented method also includes classifying at least a portion the data within the corpus based on the at least one access threshold and the at least one sensitivity threshold. Finally, the computer-implemented method includes outputting a model, based on the classification, that identifies at least a portion of the data for migration for enabling a hybrid cloud environment.

Abstract: Methods and arrangements for managing user access to a graph database. Nodes are represented in a graph, along with edges which interconnect the nodes. One or more facts are associated with each of the edges, and an access control list is provided with respect to one or more facts associated with one or more of the edges. There is restricted user access to one or more facts associated with the one or more of the edges, based on the access control list. Other variants and embodiments are broadly contemplated herein.

Abstract: A method for simulating a textured appearance on a uniform substrate includes using variable halftone dot orientations. A texture description is provided for generating electronic data representing a three-dimensional texture. Texture regions of the texture description are identified using pixel cells in the electronic data. Halftone dot orientations are assigned for each pixel cell based on a value of the pixel cell. The halftone dot orientation represents a recessed or a raised surface portion.

Abstract: A comprehensive system to enhance the aesthetic quality of the photographs captured by mobile consumers provides on-site composition and aesthetics feedback through retrieved examples. Composition feedback is qualitative in nature and responds by retrieving highly aesthetic exemplar images from the corpus which are similar in content and composition to the snapshot. Color combination feedback provides confidence on the snapshot to contain good color combinations. Overall aesthetics feedback predicts the aesthetic ratings for both color and monochromatic images. An algorithm is used to provide ratings for color images, while new features and a new model are developed to treat monochromatic images. This system was designed keeping the next generation photography needs in mind and is the first of its kind. The feedback rendered is guiding and intuitive in nature. It is computed in situ while requiring minimal input from the user.

Abstract: What is disclosed is a novel system and method for preserving user-applied markings made to a hardcopy of an original document and for generating a new composite document containing the user markings which can be reprinted without loss of image quality. In one embodiment, an original document is scanned to produce a digital representation thereof. One or more marked documents containing the user markups are scanned. The user markings are identified in each of the marked document by an iterative comparison between the marked document and the image of the original document. The identified user markings are stored to records. Thereafter, the stored user markings are retrieved and combined into an image of the original document to produce a new composite document containing selected user markings. The new file is smaller in file size and has no loss of image quality during subsequent reprints. Various embodiments have been disclosed.

Abstract: Embodiments include a method for managing processes. The method includes collecting data from first processes and second processes stored in memory, the first processes differing from the second processes by at least one of a formality level and a log detail level. The method includes identifying commonalities among the first processes and second processes and organizing the first processes and second stored processes into clusters based on the commonalities.

Abstract: Embodiments include a method for analyzing processes. The method includes receiving, by a processor, a process query and parsing, by the processor, the process query to extract one or more key features from the process query. The method includes determining a relationship between the process query and one or more stored clusters of processes organized at least according to key features based on the parsing of the process query, where the one or more stored clusters are less than all of the stored clusters. The method also includes comparing the one or more key features of the process query with processes in the one or more stored clusters and generating a list of one or more stored processes being the most similar to the process query based on the comparing of the one or more key features of the process query with the processes in the one or more stored clusters.

Abstract: Embodiments include an apparatus for managing processes including a processing circuit for obtaining process data corresponding to a plurality of processes from at least one of storage, an external device, and a user, and for performing a method. The method includes parsing the process data to identify key features of the plurality of processes and recognizing, by the processor, commonality among two or more of the plurality of processes based on the key features. The method further includes generating suggestions for transforming one or more of the plurality of processes based on the commonality among the two or more of the plurality of processes.

Abstract: Embodiments include a method for managing processes. The method includes collecting, by a processor, data from a plurality of processes. The method also includes recognizing, by the processor, commonality among two or more of the plurality of processes based on the data. The method also includes generating suggestions for transforming one or more of the plurality of processes based on the commonality.

Abstract: A method includes receiving a primary image as input data and receiving textured image data for rendering a perceived non-uniform texture on a printed output of the primary image. The primary image input data is used for determining a low coverage portion and a high coverage portion. The method then includes applying clear toner to the low coverage portion and applying colored toner at variable anisotropic orientations to the high coverage portion.