Emc IP Holding Company LLC

Dell Products Inc.

Taiwan Semiconductor Manufacturing Comp. Ltd.

The Macgregor Group, Inc.

Hat Trick Software Limited

Said Tabet

Stephen J Todd

William Jeffery White

Mohamed Sohail

Robert Anthony Lincourt, Jr

Dragan Savic

Qing Ye

Rowland Shaw

Assaf Natanzon

John S Harwood

Nikhil Sharma

Randall Marvin Anderson

John Doulamis

Rolando Rabines

Khaled Ahmed

Robert A Lincourt

Judith A Furlong

Aidan O Mahony

Kelly G Kanellakis

David Stephen Reiner

Adrian Michaud

Nihar Nanda

George Currie

Xin Ma

Jeffery White

Calvin Donahue Smith

Michael John Crichton Paull

Alex William Durham Wilkinson

Mohamed Abdullah Gommaa Sohail

Martin Andrew West

Marina Zeldin

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a global controller, an DMC environment management request from a user, and the DMC environment management request is associated with scheduling an application in the DMC environment; and in response to obtaining the request: providing acknowledgment that the request is received to the user; obtaining an order identifier and a manifest from the user; providing a correlation identifier associated with the request to the user; parsing the manifest to extract application deployment information; scheduling the application to target domains of the DMC based on the application deployment information; and providing the user with the correlation identifier, a success indicator, and application information.

Method and system for processing a manifest to provision an application in a distributed multi- tiered computing environment

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes identifying, by a global controller, a load management prediction event; in response to identifying the load management prediction event: obtaining offline data from local controllers associated with a plurality of DMC domains of the DMC environment; generating load management predictions using the offline data; adjusting local controller scheduling policies based on the load management predictions; adjusting global controller scheduling policies based on the load management predictions; making a first determination that the load management predictions require infrastructure adjustments; and in response to the first determination: initiating infrastructure capacity adjustment based on the load management predictions.

Method and system for managing a distributed multi-tiered computing environment based on load predictions

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by an endpoint controller associated with a device, an initial resource buffer from a local controller; in response to obtaining the initial resource buffer: maintaining the initial resource buffer during task provision for the device; obtaining device metrics based on performance of tasks on the device; making a determination that a resource buffer change event is identified; and in response to the determination: updating the initial resource buffer based on the resource buffer change event.

Method and system for managing resource buffers in a distributed multi-tiered computing environment

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes identifying, by a local controller associated with an DMC domain, a domain scheduling event associated with a scheduling job; and in response to identifying the domain scheduling event: identifying a candidate list of devices of the DMC domain to schedule tasks associated with the scheduling job based on a location and service level objectives; refining the candidate list of devices based on device configuration requirements, device management requirements, and security requirements to generate a final candidate list; scheduling tasks to devices using the final candidate list; generating scheduling assignments and provisioning command packages based on the scheduled tasks; providing the scheduling assignments and the provision command packages to the devices; and updating a graph based on the scheduling assignments.

Method and system for performing domain level scheduling of an application in a distributed multi-tiered computing environment

Techniques for management of virtual representations (e.g., digital twins) of infrastructure are disclosed. For example, a method comprises obtaining at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state. The method further comprises applying at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state. The method further comprises obtaining results representing the infrastructure in the second state, responsive to applying the at least one dataset to the virtual representation, wherein at least a portion of the results are indicative of an issue with the infrastructure, and then initiating one or more debugging actions with respect to the infrastructure to address the issue.

Artificial aging of digital twin to debug infrastructure

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a global controller, a DMC environment management request from a user, whereas the DMC environment management request is associated with scheduling an application in the DMC environment; and in response to obtaining the request: identifying target domains for tasks associated with the application based on the request; selecting scheduling policies for each target domain; obtaining fingerprints of previously provisioned applications associated with the request; performing case based reasoning using the fingerprints to generate scheduling packages for the target domains; sending the scheduling packages to local controllers associated with the target domains; obtaining application information from the local controllers; and providing the application information to the user.

Method and system for provisioning an application in a distributed multi-tiered computing environment using case based reasoning

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes decomposing, by a local controller associated with an DMC domain, a service dependency graph associated with a scheduling job; assigning normalized compute units and normalized network units to tasks included in the service dependency graph; generating a Q-table using the service dependency graph and reinforcement Q-learning; calculating a critical path and a max learned path using the Q-table and the service dependency graph; calculating the earliest start time and the latest start time for each task using the service dependency graph and the max learned path to obtain a plurality of earliest start time and latest start time pairs for each task; and generating scheduling assignments using the plurality of earliest start time and latest start time pairs for each task.

Method and system for performing domain level scheduling of an application in a distributed multi-tiered computing environment using reinforcement learning

Data characterization techniques in an information processing system environment are disclosed. In one example, at least one processing device is configured to obtain data associated with execution of at least one of a plurality of applications in an information processing system. The processing device extracts features from the obtained data, and then selects a reduced subset of features from the extracted features for use in a machine learning classification process configured to determine an intent of the obtained data.

Feature extraction and selection in information processing system environment

Techniques for management of virtual representations (e.g., digital twins) of infrastructure are disclosed. For example, a method comprises obtaining at least one virtual representation of an infrastructure, wherein the virtual representation represents the infrastructure in a first state. The method further comprises applying at least one dataset to the virtual representation to artificially advance the virtual representation to represent the infrastructure in a second state.

Artificial aging of digital twin representing infrastructure

Techniques described herein relate to a method for distributed data management. The method may include making a first determination that data is written to a data structure of storage of a data host; obtaining, based on the first determination, data information associated with the data; making a second determination of intent corresponding to the data; generating a global name and metadata corresponding to the data, wherein the metadata comprises the intent; and publishing the global name and the metadata to a global name repository.

Data management techniques using distributed policy agent

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a local controller associated with a DMC domain, a set of correlated services associated with an anomaly; obtaining a service dependency graph associated with the set of correlated services; generating a causal variance for each service using the correlated services and the service dependency graph; generating a weighted rank order of causal services based on the causal variance associated with each service, and the weighted rank order of causal services includes a portion of the services associated with an application associated with the anomaly; and performing remediation based on the weighted rank order of the causal services.

Method and system for performing root cause analysis associated with service impairments in a distributed multi-tiered computing environment

Techniques described herein relate to a method for managing a distributed multi-tiered computing (DMC) environment. The method includes obtaining, by a local controller associated with a DMC domain, a weighted rank order of causal services associated with a service impairment; obtaining contextual information associated with the weighted rank order of causal services; identifying top causal services based on the weighted rank order of causal services; generating, using a causal symbolic engine, a ranked order of top root causes based on the top causal services and the contextual information; selecting remediation profiles associated with the top root causes; executing remediation profiles in ranked order of the top root causes; making a determination that the remediation profiles were successful; and in response to the determination: logging the service impairment and notifying a user associated with the service impairment.

Method and system for performing service remediation in a distributed multi-tiered computing environment

Techniques are provided for secure data management in a network computing environment. A security management system receives data from a device which operates in a device network that is managed by the security management system. The security management system performs a data classification process to determine a data sensitivity level of the received data. The security management system determines a type of encryption to apply to the received data based on the determined data sensitivity level. The type of encryption is determined from a plurality of different types of encryption that are supported by a cloud system. The security management system sends the received data to the cloud system to at least one of store the data and perform secured data analytic processing of the data, in a format according to the determined type of encryption.

Secure data management in a network computing environment

Embodiments of systems and methods for enhanced drift remediation with causal methods and online model modification are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: detect drift in an Artificial Intelligence (AI) or Machine Learning (ML) model configured to make a prediction or a causal reasoning graphical or structural inference based upon input data, identify a root cause of the drift, and tag the input data with an indication of the root cause.

Enhanced drift remediation with causal methods and online model modification

One example method includes correlating trust scoring with authentication levels. Trust scores are protected in a computing system such that devices can be validated. Authentication levels are based on the verified trust scores.

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Natick, MA, United States of America

Said Tabet