Abstract: A computer-implemented method, according to one embodiment, includes mapping hosts in communication with a storage system to compartment constructs that are logical partitions of the storage system, analyzing interoperability of the hosts and the compartment constructs and defining, based on the analysis, risk profiles for applications run on the hosts. Ownership of storage objects to the compartment constructs is assigned based on the risk profiles, where each of the storage objects define a logical partition of one of the hosts and a logical partition of a storage volume of the storage system.

Abstract: A method of mitigating risks in a service level agreement (SLA), including: identifying relationships between an infrastructure and an application associated with the SLA; identifying changes to a technological environment of the SLA based on collected data associated with the SLA and the identified relationships, the collected data including the infrastructure and the application; establishing a baseline for a service level objective (SLO) of the SLA by analyzing the collected data of the infrastructure and the application; determining risk impact to the SLA based on an assessment of requirements to the SLO and the changes to the technological environment of the SLA; generating a solution option for the SLA by applying an explainable artificial intelligence (XAI) model based on processing the risk impact with the baseline in the XAI model; and updating the SLA based on the solution option.

Abstract: An approach for providing solutions to ad in the process recovery in manufacturing systems to resume manufacturing activity is disclosed. The outcome of the approach can include the following advantages, minimizing waste, reducing cost of recovery, and increasing efficiency in a manufacturing process. The approach includes collecting initial factory data; identifying and categorizing one or more shop floor activities; determining initial recovery process; creating a digital twin copy of the factory; performing one or more initial simulation scenarios; generating factory improvement plan; and executing factory improvement plan.

Abstract: A tool for providing contextual policy-based computer vision control. The tool identifies one or more camera devices in an environment. The tool determines a plurality of vision areas in a field of view within the environment. The tool determines one or more contextual policies for the plurality of vision areas in the field of view. The tool determines one or more vision augmentations for the plurality of vision areas based, at least in part, on an aggregate computer vision capability of the one or more camera devices in the environment and the one or more contextual policies for the plurality of vision areas in the field of view. The tool applies the one or more vision augmentations to at least one of the one or more camera devices in the environment.

Abstract: A computer-implemented method, according to one embodiment, includes logically partitioning a storage system into a plurality of compartment constructs, and mapping hosts in communication with the storage system to the compartment constructs, thereby enabling interoperability among the hosts and the compartment constructs. The interoperability of the hosts and the compartment constructs is analyzed, and the interoperability is based on storage software and/or firmware versions being run by the hosts. The method further includes defining, based on the analysis, risk profiles for applications run on the hosts, and determining, based on the risk profiles, recommendations for assignment and mapping of the hosts with the compartment constructs. Ownership of storage objects is assigned to the compartment constructs based on the recommendations. Each of the storage objects define a logical partition of one of the hosts and a logical partition of a storage volume of the storage system.

Abstract: A computer-implemented method includes: advertising, by a computing device, at least one service including information from a learned knowledge base by a service provider vehicle within an autonomous vehicle ecosystem; connecting, by the computing device, the service provider vehicle to a service consumer vehicle within the autonomous vehicle ecosystem through a communication network; and sharing, by the computing device, the at least one service including the information from the learned knowledge base through a connection between the service provider vehicle and the service consumer vehicle using the communication network.

Abstract: A method of mitigating risks in a service level agreement (SLA), including: identifying relationships between an infrastructure and an application associated with the SLA; identifying changes to a technological environment of the SLA based on collected data associated with the SLA and the identified relationships, the collected data including the infrastructure and the application; establishing a baseline for a service level objective (SLO) of the SLA by analyzing the collected data of the infrastructure and the application; determining risk impact to the SLA based on an assessment of requirements to the SLO and the changes to the technological environment of the SLA; generating a solution option for the SLA by applying an explainable artificial intelligence (XAI) model based on processing the risk impact with the baseline in the XAI model; and updating the SLA based on the solution option.

Abstract: A computer-implemented method, according to one embodiment, includes logically partitioning a storage system into a plurality of compartment constructs, and mapping hosts in communication with the storage system to the compartment constructs, thereby enabling interoperability among the hosts and the compartment constructs. The interoperability of the hosts and the compartment constructs is analyzed, and the interoperability is based on storage software and/or firmware versions being run by the hosts. The method further includes defining, based on the analysis, risk profiles for applications run on the hosts, and determining, based on the risk profiles, recommendations for assignment and mapping of the hosts with the compartment constructs. Ownership of storage objects is assigned to the compartment constructs based on the recommendations. Each of the storage objects define a logical partition of one of the hosts and a logical partition of a storage volume of the storage system.

Abstract: A method of mitigating risks in a service level agreement (SLA), including: identifying relationships between an infrastructure and an application associated with the SLA; identifying changes to a technological environment of the SLA based on collected data associated with the SLA and the identified relationships, the collected data including the infrastructure and the application; establishing a baseline for a service level objective (SLO) of the SLA by analyzing the collected data of the infrastructure and the application; determining risk impact to the SLA based on an assessment of requirements to the SLO and the changes to the technological environment of the SLA; generating a solution option for the SLA by applying an explainable artificial intelligence (XAI) model based on processing the risk impact with the baseline in the XAI model; and updating the SLA based on the solution option.

Abstract: Disclosed are techniques for dynamically prioritizing subsets of data within datasets based on context. Historical analysis logs, the underlying datasets for the historical analysis logs, and context data are used to train a machine learning model to determine subsets of data within an input dataset when provided the input dataset and a context information input set. When an input dataset and context information input set are received, the machine learning model determines subsets of data (if any) that should be prioritized for processing ahead of other sets of data in the input dataset, based on the context information input set. Subsets of data within an input dataset with higher priority values are processed before other sets of data within the input dataset.

Abstract: An approach for providing solutions to ad in the process recovery in manufacturing systems to resume manufacturing activity is disclosed. The outcome of the approach can include the following advantages, minimizing waste, reducing cost of recovery, and increasing efficiency in a manufacturing process. The approach includes collecting initial factory data; identifying and categorizing one or more shop floor activities; determining initial recovery process; creating a digital twin copy of the factory; performing one or more initial simulation scenarios; generating factory improvement plan; and executing factory improvement plan.

Abstract: A method includes identifying, by a computing device, activities of a machine using a digital twin of a machine; running, by the computing device, simulations of the activities on the digital twin; determining, by the computing device, a performance issue in the machine using the simulations; and deploying, by the computing device, a capability to address the performance issue.

Abstract: A computing environment is transformed from one technological state to another technological state. Data relating to the computing environment is obtained, and the data includes life-cycle information of one or more computing resources of the computing environment and one or more requests of an entity to use the computing environment. Based at least on the data that is obtained, a plurality of sets of transformation tasks to be used to transform a selected infrastructure of the computing environment from one technological state to another technological state is automatically derived. Based on at least one set of transformation tasks of the plurality of sets of transformation tasks, one or more actions is taken to transform the selected infrastructure from the one technological state to the other technological state.

Abstract: Mitigating the impact of data center thermal environmental issues on production applications includes retrieving, by a computer, from a centralized repository first data corresponding to I/O and processing activities of an infrastructure component executing one or more applications, second data corresponding to an application-to-infrastructure map, and third data corresponding to a business priority of the one or more applications. Based on the first data and the second data, the one or more applications are mapped to heat generation values of the infrastructure component, and based on the mapping a thermal load of the one or more applications on the infrastructure component is determined using data analytics. Using the third data, the computer identifies an execution priority for the one or more applications, generates a correlative mapping between the execution priority and the thermal load of the one or more applications, and generates a resolution plan based on the correlative mapping.

Abstract: Application consistent dataset recovery using a cognitive control plane is provided. Sequence and timestamp of snapshots of volumes in a consistency group across heterogenous storage components corresponding to an application are recorded to facilitate operational recovery of application consistent datasets for the application. The cognitive control plane establishes a framework to manage, monitor, analyze, and update the consistency group and metadata to facilitate application consistent data recovery. A set of snapshots needed for the operational recovery of the application consistent datasets for the application is identified by mapping the sequence and timestamp of the snapshots of the volumes in the consistency group across the heterogenous storage components corresponding to the application in response to the computer determining that the operational recovery of the application consistent datasets for the application has been requested.

Abstract: A processor may receive object data associated with a position and an orientation of a first object in an environment from IoT sensors. The processor may generate a digital twin simulation of the first object. In some embodiments, the digital twin simulation may include data associated with the relative positions and orientations of one or more other objects to the first object. The processor may calculate forces acting on the first object. The processor may identify whether the first object is in a state of instability.

Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include collecting organism data and analyzing the organism data. The operations may also include predicting a organism movement pattern based on the organism data and relaying the organism movement pattern to a participant.

Abstract: A method for optimizing device-to-device communication protocol selection in an edge computing environment is provided. The method includes: receiving a request for a service from a user device, wherein the computing system is one of plural edge computing devices in an edge computing environment; determining computational tasks performed in providing the service; selecting, using a machine learning model, a set of the edge computing devices to perform the computational tasks and communication protocols for the set of the edge computing devices to use while performing the computational tasks, wherein the machine learning model is configured to select the set of the edge computing devices and the communication protocols based on minimizing a time to perform the computational tasks; and sending instructions to perform the computational tasks, thereby causing the set of the edge computing devices to perform the service in response to the request from the user device.

Abstract: Policy deviations for distributed computing environments are detected and recorded an immutable ledger of transaction provenance from end to end transactions performed in the distributed computing environment. From the immutable ledger, persona data for transaction types is plotted as an bipartite graph. Edge weights of the bipartite graphs are correlated to trust levels between personas from the persona data and the transaction types from the immutable ledger. Trust levels from the edge weights are correlated to rules illustrating when the transaction provenance indicate a policy deviation in the distributed computing environment. The rules are then employed to detect in real time end to end provenance when a policy deviation in the distributed computing environment is occurring. An alert of policy deviations may be sent to stakeholders for the distributed computing environment.

Abstract: Policy deviations for distributed computing environments are detected and recorded an immutable ledger of transaction provenance from end to end transactions performed in the distributed computing environment. From the immutable ledger, persona data for transaction types is plotted as an bipartite graph. Edge weights of the bipartite graphs are correlated to trust levels between personas from the persona data and the transaction types from the immutable ledger. Trust levels from the edge weights are correlated to rules illustrating when the transaction provenance indicate a policy deviation in the distributed computing environment. The rules are then employed to detect in real time end to end provenance when a policy deviation in the distributed computing environment is occurring. An alert of policy deviations may be sent to stakeholders for the distributed computing environment.