Distributed software-defined industrial systems

Patent metadata

Field	Value
Publication number	US-11330087-B2
Application number	US-201816650454-A
Country	US
Kind code	B2
Filing date	Sep 28, 2018
Priority date	Nov 16, 2017
Publication date	May 10, 2022
Grant date	May 10, 2022

Abstract

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.

First claim

What is claimed is:

1. A method for operation of a software defined industrial system, comprising:
establishing respective functional definitions of a software defined industrial system, the software defined industrial system to interface with a plurality of devices, wherein the plurality of devices include respective sensors and respective actuators; and
establishing a dynamic data model to define properties of a plurality of components of the software defined industrial system;
operating the software defined industrial system using the respective functional definitions;
monitoring data from the plurality of components, to identify operational metadata;
detecting one or more patterns from the operational metadata;
identifying changes to the dynamic data model based on the detected one or more patterns; and
updating the dynamic data model based on the identified changes.

2. The method of claim 1 , wherein the plurality of components includes respective applications, devices, sensors, or architecture definitions.

3. The method of claim 1 , wherein plurality of components includes a device, wherein the device represents an ensemble of sensors.

4. The method of claim 1 , wherein the dynamic data model is updated to indicate changes to the dynamic data model in a subset of components of the plurality of components, and wherein the dynamic data model is updated based on a resource availability change or an error condition occurring with the subset of components.

5. The method of claim 1 , wherein establishing the dynamic data model includes defining mandatory fields and restrictions for changes to the dynamic data model.

6. The method of claim 1 , wherein the operational metadata represents a probabilistic estimate of a value associated with a component of the plurality of components.

7. The method of claim 1 , further comprising:
querying a component of the plurality of components for metadata expansion rules;
receiving a response from the component in response to the querying;
wherein the updating of the dynamic data model is further based on the metadata expansion rules, and a confidence or relevancy score associated with updating respective data fields.

8. The method of claim 1 , further comprising:
performing system operations in an edge, fog, or cloud network, based on the updated dynamic data model.

9. The method of claim 1 , comprising:
defining at least one condition in the software defined industrial system for data model evaluation;
obtaining data from a plurality of sensors in the software defined industrial system;
identifying at least one pattern, rule, or threshold, for data model modification;
evaluating data from the plurality of sensors using at least one identified pattern, rule, or identified threshold;
defining a modification to the data model, based on the at least one identified pattern, rule, or identified threshold; and
incorporating the modification to the data model for the plurality of sensors and a data flow associated with the plurality of sensors.

10. The method of claim 9 , further comprising:
requesting approval for the data model modification from a data model administrator; and
receiving approval for the data model modification from the data model administrator;
wherein the incorporating of the modification to the data model is performed in response to receiving the approval for the data model modification.

11. The method of claim 9 , further comprising:
implementing changes to data processing operations in the software defined industrial system based on the data model modification.

12. At least one non-transitory machine-readable storage medium including instructions, wherein the instructions, when executed by a processing circuitry of a device, cause the processing circuitry to perform operations comprising:
establishing respective functional definitions of a software defined industrial system, the software defined industrial system to interface with a plurality of devices, wherein the plurality of devices include respective sensors and respective actuators; and
establishing a dynamic data model to define properties of a plurality of components of the software defined industrial system;
operating the software defined industrial system using the respective functional definitions;
monitoring data from the plurality of components, to identify operational metadata;
detecting one or more patterns from the operational metadata;
identifying changes to the dynamic data model based on the detected one or more patterns; and
updating the dynamic data model based on the identified changes.

13. The machine-readable storage medium of claim 12 , wherein the plurality of components includes respective applications, devices, sensors, or architecture definitions.

14. The machine-readable storage medium of claim 12 , wherein plurality of components includes a device, wherein the device represents an ensemble of sensors.

15. The machine-readable storage medium of claim 12 , wherein the dynamic data model is updated to indicate changes to the dynamic data model in a subset of components of the plurality of components, and wherein the dynamic data model is updated based on a resource availability change or an error condition occurring with the subset of components.

16. The machine-readable storage medium of claim 12 , wherein establishing the dynamic data model includes defining mandatory fields and restrictions for changes to the dynamic data model.

17. The machine-readable storage medium of claim 12 , wherein the operational metadata represents a probabilistic estimate of a value associated with a component of the plurality of components.

18. The machine-readable storage medium of claim 12 , the operations further comprising:
querying a component of the plurality of components for metadata expansion rules;
receiving a response from the component in response to the querying;
wherein the updating of the dynamic data model is further based on the metadata expansion rules, and a confidence or relevancy score associated with updating respective data fields.

19. The machine-readable storage medium of claim 12 , the operations further comprising:
performing system operations in an edge, fog, or cloud network, based on the updated dynamic data model.

20. The machine-readable storage medium of claim 12 , the operations further comprising:
defining at least one condition in the software defined industrial system for data model evaluation;
obtaining data from a plurality of sensors in the software defined industrial system;
identifying at least one pattern, rule, or threshold, for data model modification;
evaluating data from the plurality of sensors using at least one identified pattern, rule, or identified threshold;
defining a modification to the data model, based on the at least one identified pattern, rule, or identified threshold; and
incorporating the modification to the data model for the plurality of sensors and a data flow associated with the plurality of sensors.

21. The machine-readable storage medium of claim 20 , the operations further comprising:
requesting approval for the data model modification from a data model administrator; and
receiving approval for the data model modification from the data model administrator;
wherein the incorporating of the modification to the data model is performed in response to receiving the approval for the data model modification.

22. The machine-readable storage m

Assignees

• Intel Corp

Inventors

• Wouhaybi Rita H
• Vicente John
• Smith Kirk
• Chavez Robert
• Yarvis Mark
• Brown Steven M
• Ouillette Jeremy
• Kronschnabel Roderick E
• Schneider Matthew J
• Lucero Chris D
• Hatalkar Atul N
• Garg Sharad
• Rathbone Casey
• Berck Aaron R
• Zhang Xubo
• Thomas Ron Kuruvilla
• Shetty Mandeep
• Negi Ansuya

Classifications

• H04L67/10

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• H04L69/40 Primary

  for recovering from a failure of a protocol instance or entity, e.g. service redundancy protocols, protocol state redundancy or protocol service redirection (management of faults, events, alarms or notifications in data switching networks H04L41/06) · CPC title

• H04L67/565

  Conversion or adaptation of application format or content (adding application control or application functional data H04L67/561) · CPC title

• G05B19/41835 Primary

  characterised by program execution · CPC title

• H04L67/1048

  Departure or maintenance mechanisms · CPC title