Intel Corporation

Intel Corporatioon

Mark D Yarvis

Rita H Wouhaybi

John B Vicente

Sharad K Garg

Hong C Li

James R Blakley

Kirk Smith

Robert Chavez

W Steven Conner

Aaron R Berck

Xubo Zhang

Ron Kuruvilla Thomas

Casey T Rathbone

David L Graumann

Anand P Rangarajan

Bradut Vrabete

Sangita R Sharma

Rahul C Shah

Peter S Adamson

Chieh-Yih Wan

Ansuya Negi

Mandeep Shetty

Atul N Hatalkar

Roderick E Kronschnabel

Matthew J Schneider

Chris D Lucero

Steven M Brown

Jeremy Ouillette

Francesc Guim Bernat

Kshitij Arun Doshi

John Joseph Browne

Mark Angus MacDonald

Susanne M Balle

Mats Gustav Agerstam

Marcos Emanuel Carranza

Mousumi M Hazra

Joshua Boelter

Thijs Metsch

Soethiha Soe

Nandakishore R Kushalnagar

Christopher J Lord

Mustafa Demirhan

Bin Li

Dario Oliver

Adrian C Hoban

Anantha Deepthi Uppala

Mikko Ylinen

Dominic Fulginiti

Samuel D Benn

David Cremins

Andrew G Shirtz

Sumeet Sandhu

Ahmad Khoshnevis

Lenitra M Durham

Jasmeet Chhabra

Matthew D Wood

Cesar Martinez-Spessot

Benjamin Walker

Patrick Koeberl

Philip Muse

Milind S Pandit

John Mangan

Yong Wang

Kara E Jackson

David J Cobbley

Andrew S Dickinson

Marcelino Ford-Livene

Ceara Chewning

Marcelino Ford Livene

Jens Mache

Hakirat Singh

Harkirat Singh

Xiangping Qin

Sharad A Garg

Hong Li

Various systems and methods for implementing intent-based cluster administration are described herein. An orchestrator system includes: a processor; and memory to store instructions, which when executed by the processor, cause the orchestrator system to: receive, at the orchestrator system, an administrative intent-based service level objective (SLO) for an infrastructure configuration of an infrastructure; map the administrative intent-based SLO to a set of imperative policies; deploy the set of imperative policies to the infrastructure; monitor performance of the infrastructure; detect non-compliance with the set of imperative policies; and modify the administrative intent-based SLO to generate a revised set of imperative policies that cause the performance of the infrastructure to be compliant with the revised set of imperative policies.

Intent-based cluster administration

Various systems and methods for implementing intent-based orchestration in heterogenous compute platforms are described herein. An orchestration system is configured to: receive, at the orchestration system, a workload request for a workload, the workload request including an intent-based service level objective (SLO); generate rules for resource allocation based on the workload request; generate a deployment plan using the rules for resource allocation and the intent-based SLO; deploy the workload using the deployment plan; monitor performance of the workload using real-time telemetry; and modify the rules for resource allocation and the deployment plan based on the real-time telemetry.

Intent-based orchestration in heterogenous compute platforms

Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

Distributed software-defined industrial systems

An Internet of Things (IoT) system that includes an orchestration device is provided. The orchestration device receives resource requirements and accesses a device/capability map to produce a task deployment map.

Adaptive deployment of applications

Embodiments herein relate to recognition of an appliance state based on sensor data and determination of a response based at least in part on the appliance state. In various embodiments, an apparatus to recognize an appliance state may include a sensor data module to identify sensor data in one or more signals relating to data from one or more sensors associated with an appliance, an appliance state recognition module to determine an appliance state of the appliance based at least in part on the sensor data, a response module to determine a response based at least in part on the appliance state, and a transmission module to send the response to at least one of an appliance controller for the appliance or a presentation device. Other embodiments may be described and/or claimed.

Appliance state recognition device and methods

Various systems and methods may be used to implement a software defined industrial system. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. The orchestrated system may include an orchestration server, a first node executing a first module, and a second node executing a second module. In response to the second node failing, the second module may be redeployed to a replacement node (e.g., the first node or a different node). The replacement mode may be determined by the first node or another node, for example based on connections to or from the second node.

Distributed dynamic architecture for error correction

Various systems and methods are provided for implementing a software defined industrial system. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device, configured to: identify available software modules adapted to perform functional operations in a control system environment; identify operational characteristics that identify characteristics of execution of the available software modules that are available to implement a control system application; select a software module for execution based on the operational configuration and the operational characteristics identified in the manifest; and cause the execution of the selected software module in the control system environment based on an application specification for the control system application.

Self-descriptive orchestratable modules in software-defined industrial systems

Technologies for establishing and utilizing a decentralized cloud infrastructure using a plurality of mobile computing devices include broadcasting for the formation of the decentralized cloud computing and storage infrastructure and establishing wireless communications between the plurality of mobile computing devices. The plurality of mobile computing devices self-organize and cooperate with one another to establish a structured decentralized cloud infrastructure to expose and sharing resources, services, and/or applications for ad hoc or socially-driven decentralized, cloud computing purposes.

Ad hoc decentralized cloud infrastructure

Growing community of inventors

Santa Clara, CA, United States of America

Mark D Yarvis