Integrated and scalable architecture for accessing and delivering data

• US 9,143,563 B2
• Filed: 10/30/2012
• Issued: 09/22/2015
• Est. Priority Date: 11/11/2011
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Pingel, Jan, Pantaleano, Michael John, Shah, Chirayu, Smith, Todd M., Giordano, Matthew C., Hessmer, Rainer, Peters, Kermit George, van der Merwe, Neville Patrick
• Primary Examiner(s): Reyes, Mariela
• Assistant Examiner(s): VU, THONG H
• Application Number:
  US13/663,928
• Publication Number:
  US 20130124465A1
• Time in Patent Office: 1,057 Days
• Field of Search: 707/200, 707/763, 707/692
• US Class Current: 1/1
• CPC Class Codes: G06F 11/3409 for performance assessment
• CPC Class Codes: G06F 11/3423 where the assessed time is active or idle time
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 3/0604 Improving or facilitating administration, e.g. storage management
• CPC Class Codes: G06F 3/0647 Migration mechanisms
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: H04L 41/069 using logs of notifications; Post-processing of notifications
• CPC Class Codes: H04L 67/1095 Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: Y02P 90/845 Inventory and reporting systems for greenhouse gases [GHG]

Abstract

A distributed and scalable data historian framework is provided that allows historian functionality to be efficiently incorporated at various levels of an industrial enterprise. The framework includes a historian data interface system that provides a single interface and common protocol for configuring, managing, and viewing historian data located throughout a network of historian distributed across the industrial enterprise. The historian data interface system leverages a data model that models the enterprise and sources of historian data to facilitate fast and efficient retrieval of desired historian data. By unifying the distributed historians under a common framework, the data model can facilitate enterprise-level management of historian data collection and storage.

Claims

1. A system, comprising:

at least one non-transitory computer-readable medium having stored therein computer-executable components; and

at least one processor that executes the following computer-executable components stored on the at least one non-transitory computer readable medium;

a data model component that maintains a data model that defines multiple hierarchical levels of an industrial enterprise and models correlations between historian data stored on a set of historian devices in terms of the multiple hierarchical levels;

an access component that

receives a request for access to a data item of the historian data,

identifies, based on the correlations defined by the data model, at least two historian devices of the set of historian devices that store duplicate instances of the data item, and

selects a historian device, of the at least two historian devices, from which to retrieve the data item based on respective locations of the at least two historian devices relative to a location of origination of the request; and

an interface component configured to display the data item retrieved from the historian device.

2. The system of claim 1, further comprising a migration component that relocates a portion of the historian data stored at a first historian device to a second historian device, wherein the first historian device and the second historian device are included in the set of historians devices.

3. The system of claim 2, wherein the migration component relocates the portion of the historian data in response to a determination that a frequency of access requests for the portion of the historian data exceeds a defined frequency.

4. The system of claim 3, wherein the migration component selects the second historian device based on a location of origination of the access requests.

5. The system of claim 1, further comprising a caching component that caches subsets of the historian data as a function of at least one of a volume of access requests, a frequency of the access requests, a location of origination of the access requests, or respective importance levels determined for the subsets of the historian data.

6. The system of claim 5, wherein the caching component ranks the subsets of the historian data, and caches the subsets of the historian data in hierarchical layers according to ranking.

7. The system of claim 6, wherein the access component retrieves the subsets of the historian data from the hierarchical layers and displays the subsets of the historian data as a graphical representation that progressively updates over time as the subsets of the historian data are retrieved from the respective hierarchical layers.

8. The system of claim 1, further comprising a cloud interface component that synchronizes at least a portion of the historian data to a virtual representation of the set of historians on a cloud platform.

9. The system of claim 1, wherein at least one of the data model, the access component, or the interface component resides on a cloud platform.

10. The system of claim 1, wherein the interface component renders a tag cloud representation of a subset of the historian data, the tag cloud representation comprises a set of operating state indicators, and an operating state indicator of the set of operating state indicators has a size that is a function of a duration of time that an operating state corresponding to the operating state indicator was in effect for a time period represented by the subset of the historian data.

11. The system of claim 1, wherein the multiple hierarchical levels comprise at least an enterprise level, a plant level, and a machine level.

12. The system of claim 1, further comprising a join component configured to discover a relationship between a first data tag on a first historian device of the set of historian devices and a second data tag on a second historian device of the set of data historian devices based on the data model, wherein the data model component is further configured to create, in the data model, a record of a data join between the first data tag and the second data tag based on the relationship.

13. The system of claim 1, wherein the data model defines an association between a real-time data value stored in a first historian device and a corresponding historical data value stored in a second historian device.

14. A method, comprising

using at least one processor executing computer-executable instructions embodied on at least one non-transitory computer-readable medium to perform operations, the operations comprising:

defining multiple hierarchical levels of an industrial enterprise;

modeling correlations between data tags associated with historian data located on a plurality of historian devices distributed across one or more levels of the industrial enterprise in terms of the multiple hierarchical levels to yield a data model;

receiving a request for a subset of the historian data associated with a data tag of the data tags;

in response to receiving the request, determining, based on correlations modeled by the data model, that the subset of historian data is replicated on at least two historian devices of the plurality of historian devices;

selecting a historian device of at least two historian devices from which to retrieve the subset of the historian data based on a comparison of locations of the at least two historian devices relative to a location from which the request for the subset of the historian data is received; and

retrieving the subset of historian data from the historian device.

15. The method of claim 14, the operations further comprising:

in response to determining that a volume of access requests for a portion of the historian data stored on a first subset of the plurality of historian devices exceeds a defined setpoint, migrating the portion of the historian data from the first historian device to a second historian device of the plurality of historian devices.

16. The method of claim 15, the operations further comprising selecting the second historian device based on a location the second historian device relative to a location of origination of the access requests.

17. The method of claim 14, the operations further comprising caching selected subsets of the historian data based on at least one of a number of access requests, a frequency of the access requests, a location from which the access requests are received, or respective importance of the subsets of the historian data.

18. The method of claim 17, the operations further comprising:

ranking the selected subsets of the historian data; and

caching the selected subsets of the historian data among caching layers according to ranking.

19. The method of claim 14, the operations further comprising generating a virtual representation of the plurality of historian devices on a cloud platform.

20. The method of claim 14, wherein the modeling the correlations comprises modeling a correlation between a real-time data value stored in a first historian device and a historical data value corresponding to the real-time data value stored in a second historian device.

21. A non-transitory computer-readable medium having stored thereon computer-executable instructions that, in response to execution by a system including a processor, cause the system to perform operations, the operations comprising:

generating a data model representing multiple historian devices and correlations between historian data stored on the multiple historian devices in terms of multiple hierarchical levels of an industrial enterprise on which the multiple historian devices reside;

receiving a request to retrieve a portion of the historian data associated with a data tag;

identifying, based on the correlations defined by the data model, that the portion of the historian data is duplicated on two or more historian devices of the multiple historian devices;

selecting a historian device, of the two or more historian devices, from which to retrieve the portion of the historian data based on respective locations of the two or more historian devices relative to a location from which the request was received; and

retrieving the portion of the historian data from historian device.

22. The computer-readable medium of claim 21, the operations further comprising:

determining that a volume of requests for the portion of the historian data exceeds a defined setpoint;

identifying an available historian device, of the multiple historian devices, capable of servicing the access requests more quickly than the two or more historian devices; and

relocating the portion of the historian data from the two or more historian devices to the available historian device in response to the determining.