INTEGRATED AND SCALABLE ARCHITECTURE FOR ACCESSING AND DELIVERING DATA

• US 20130124465A1
• Filed: 10/30/2012
• Published: 05/16/2013
• 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: Pantaleano, Michael John, Hessmer, Rainer, Pingel, Jan, Shah, Chirayu, Smith, Todd M., Giordano, Matthew C., Peters, Kermit George, van der Merwe, Neville Patrick
• Granted Patent: US 9,143,563 B2
• Time in Patent Office: Days
• US Class Current: 707/610
• 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 non-transitory computer readable medium;

a data model component that maintains a data model relating to a set of historians and historian data stored on the set of historians;

an interface component that receives a request for access to a subset of the historian data, identifies one or more locations of the subset of the historian data across the set of historians by using the data model, and retrieves and presents the subset of the historian data.

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

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 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 of 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 interface component retrieves the subsets of the historian data from the hierarchical layers and presents 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, wherein the data model models the set of historians and historian data in terms of multiple hierarchical levels of an enterprise.

9. The system of claim 1, further comprising an access component that determines, based on the data model, that a requested data item of the historian data is available from multiple historians, and identifies a selected historian, of the multiple historians, from which to retrieve the requested data item based on at least one of respective locations of the multiple historians relative to a location of origination of a data request or respective processing capabilities of the multiple historians.

10. 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.

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

12. The system of claim 1, wherein the interface component renders a tag cloud representation of the subset of the historian data, wherein the tag cloud representation comprises a set of operating state indicators, and wherein 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.

13. 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:

modeling a plurality of historians distributed across one or more levels of an industrial enterprise to yield a data model;

receiving a request for a subset of historian data stored on at least one of the plurality of historians;

determining, based on the data model, one or more locations of the subset of historian data; and

retrieving the subset of historian data from the one or more locations.

14. The method of claim 13, the operations further comprising:

determining that a volume of access requests for a portion of the historian data stored on a first subset of the plurality of historians exceeds a defined setpoint; and

migrating the portion of the historian data from the first historian to a second historian of the plurality of historians.

15. The method of claim 14, the operations further comprising selecting the second historian based on a location the second historian relative to a location of origination of the access requests.

16. The method of claim 13, 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.

17. The method of claim 16, 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.

18. The method of claim 13, wherein the modeling comprises modeling locations of the plurality of historians within multiple hierarchical levels of an industrial enterprise.

19. The method of claim 13, further comprising:

determining, based on the data model, that a historian data value is replicated on multiple historians of the plurality of historians;

determining locations of the multiple historians relative to a location from which a request for the historian data value is received; and

selecting a historian, of the multiple historians, from which to retrieve the historian data value in response to the request for the historian data value.

20. The method of claim 13, the operations further comprising generating a virtual representation of the plurality of historians on a cloud platform.

21. A 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 including:

generating a data model representing multiple historians and their associated historian data;

receiving a request to retrieve a portion of the historian data stored on a subset of the multiple historians;

identifying one or more locations of the subset of the multiple historians based on the data model; and

retrieving the portion of the historian data from the one or more locations.

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

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

identifying an available historian, of the multiple historians, capable of servicing the access requests more quickly than the subset of the multiple historians; and

relocating the portion of the historian data from the subset of the multiple historians to the available historian in response to the determining.