Cost-based deployment of components in smart item environments

• US 20080033785A1
• Filed: 07/31/2006
• Published: 02/07/2008
• Est. Priority Date: 07/31/2006
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP AG (SAP SE)
• Inventors: Anke, Juergen
• Granted Patent: US 8,396,788 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06F 2209/5017 Task decomposition
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals
• CPC Class Codes: G06F 9/5066 Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs mappping at compile time, see G06F8/451
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

One or more distributions, to service execution environments, of component services associated with a composite service associated with an analysis of data generated by one or more sensors, may be determined, the composite service including an ordering of execution of the associated component services for the analysis of the data, at least one of the service execution environments located at a first network node associated with a device layer and at least one other one of the service execution environments located at a second network node associated with a middleware layer. An evaluation of each of the distributions of the component services may be determined based on a metric associating weighted values with a consumption by each distribution of respective resources associated with each of the first and second network nodes. A recommendation including one or more of the distributions may be determined based on the evaluation.

Claims

1. A method comprising:

determining one or more distributions, to service execution environments, of component services associated with a composite service associated with an analysis of data generated by one or more sensors, the composite service including an ordering of execution of the associated component services for the analysis of the data, at least one of the service execution environments located at a first network node associated with a device layer and at least one other one of the service execution environments located at a second network node associated with a middleware layer that includes a request handling layer and a device handling layer;

determining an evaluation of each of the distributions of the component services based on a metric associating one or more weighted values with a consumption by the each distribution of one or more respective resources associated with each of the first and second network nodes; and

determining a recommendation including one or more of the distributions based on the evaluation.

2. The method of claim 1 wherein determining the evaluation comprises determining the evaluation based on a metric including a quality measure of distributions based on the consumption by the each distribution of the one or more respective resources associated with each of the first and second network nodes and on one or more performance measures.

3. The method of claim 1 wherein determining the evaluation comprises determining the evaluation based on a metric including a quality measure of distributions in accordance with

4. The method of claim 1 further comprising:

determining a model of the composite service including a first model node associated with a first one of the component services, a second model node associated with a second one of the component services, and a directed edge between the first and second model nodes based on the ordering of execution.

5. The method of claim 4 further comprising:

storing in a first storage device associated with the first model node a value indicating an amount of a first resource required by the first one of the component services;

storing in a second storage device associated with the second model node a value indicating an amount of a second resource required by the second one of the component services; and

storing in a third storage device associated with the directed edge a value indicating an amount of a third resource required by the composite service.

6. The method of claim 1 further comprising:

determining a model of network nodes that include the service execution environments, the model including a model node associated with each network node and a model edge associated with each network link connecting the network nodes.

7. The method of claim 6 further comprising:

storing in a storage device associated with each model node one or more values indicating amounts of one or more resources that are available for the component services; and

storing in a storage device associated with each model edge one or more values indicating amounts of one or more resources that are available for the each network link.

8. The method of claim 1 further comprising:

determining a load model based on one or more parameters associated with one or more requests for the analysis of the data.

9. The method of claim 8 wherein -the one or more requests for the analysis of the data is generated by a business application located at a backend system, and wherein one or more of the sensors is associated with a product embedded information device (PEID) located at the device layer.

10. The method of claim 9 wherein the one or more requests for the analysis of the data is received from a product lifecycle management (PLM) application and wherein one or more of the sensors is configured to generate data associated with a specified product.

11. The method of claim 9 wherein the metric specifies a first one of the weighted values associated with the first network node that is substantially different from a second one of the weighted values associated with the second network node, wherein the first and second ones of the weighted values are each associated with a substantially similar respective resource associated with each of the first and second network nodes.

12. The method of claim 1 wherein the one or more respective resources includes one or more of memory, central processing unit (CPU) power, time, or bitrate.

13. The method of claim 1 wherein the device layer includes one or more of a radio frequency identification (RFID) reader, a smart items device, a device within a sensor network, a sensor mote, or a product embedded information device.

14. The method of claim 1 wherein one or more of the component services is configured to calculate one or more results using one or more of a linear regression, a moving average, a classification, a determination of a minimum value, a determination of a maximum value, threshold monitoring, a notification, a formatting of data, or a number of occurrences of an event or item.

15. The method of claim 1 wherein one or more of the component services is configured to buffer data received from a sensor.

16. A system comprising:

a middleware layer including a request handling layer and a device handling layer, the middleware layer in communication with an application and a device layer including one or more devices, wherein the request handling layer includes;

a service repository that is configured to store at least one composite service in association with service metadata describing an ordering of execution of component services of the composite service; and

a distribution manager that is configured to;

determine one or more distributions, to service execution environments, of the component services associated with the composite service associated with an analysis of data generated by one or more sensors, the composite service including the ordering of execution of the associated component services for the analysis of the data, at least one of the service execution environments located at a first network node included in the device layer and at least one other one of the service execution environments located at a second network node included in the middleware layer,

determine an evaluation of each of the distributions of the component services based on a metric associating one or more weighted values with a consumption by the each distribution of one or more respective resources associated with each of the first and second network nodes, and

determine a recommendation including one or more of the distributions based on the evaluation.

17. The system of claim 16 wherein the device layer includes one or more of a radio frequency identification (RFID) reader, a smart items device, a device within a sensor network, a sensor mote, or a product embedded information device.

18. The system of claim 16 wherein the service repository is configured to store one or more service executables and the service metadata associated with the composite service.

19. The system of claim 16 further comprising:

a model data storage device that is configured to store a model of the composite service including a first model node associated with a first one of the component services, a second model node associated with a second one of the component services, and a directed edge between the first and second model nodes based on the ordering of execution.

20. A distribution manager configured to:

determine one or more distributions, to service execution environments, of component services associated with a composite service associated with an analysis of data generated by one or more sensors, the composite service including an ordering of execution of the associated component services for the analysis of the data, at least one of the service execution environments located at a first network node included in the device layer and at least one other one of the service execution environments located at a second network node included in the middleware layer;

determine an evaluation of each of the distributions of the component services based on a metric associating one or more weighted values with a consumption by the each distribution of one or more respective resources associated with each of the first and second network nodes; and

determine a recommendation including one or more of the distributions based on the evaluation.

21. The distribution manager of claim 20 wherein one or more of the component services is configured to calculate one or more results using one or more of a linear regression, a moving average, a classification, a determination of a minimum value, a determination of a maximum value, threshold monitoring, a notification, a formatting of data, or a number of occurrences of an event or item.

22. The distribution manager of claim 20 wherein the device layer includes one or more of a radio frequency identification (RFID) reader, a smart items device, a device within a sensor network, a sensor mote, or a product embedded information device.

23. The distribution manager of claim 20 wherein the one or more respective resources includes one or more of memory, central processing unit (CPU) power, time, or bitrate.