PREDICTIVE DECONSTRUCTION OF DYNAMIC COMPLEXITY

• US 20120197686A1
• Filed: 01/31/2012
• Published: 08/02/2012
• Est. Priority Date: 01/31/2011
• Status: Active Grant

• Current Assignee: X-Act Science Inc.
• Original Assignee: Accretive Technologies, Inc.
• Inventors: Abu El Ata, Nabil A.
• Granted Patent: US 10,726,362 B2
• Time in Patent Office: Days
• US Class Current: 705/7.39
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis

Abstract

The dynamic complexity and the operational risk inherent in a system are defined and incorporated into a mathematical model of the system. The mathematical model is emulated to predict the states of instability that can occur within the operation of the system. Dynamic complexity of a service is demonstrated where there is an observed effect where the cause can be multiple and seemingly inter-related effects of a many-to-one or many-to-many relationship. Having assessed the dynamic complexity efficiency and the operational risk index of a service (e.g., a business, process or information technology), these indexes can be employed to emulate all attributes of a service, thereby determining how a service responds in multiple states of operation, the states where the dynamic complexity of a service can occur, optimal dynamic complexity efficiency of a service, and the singularities wherein a service becomes unstable.

Claims

1. A computer implemented method for evaluating operation of an information system architecture, comprising:

obtaining a multi-layer mathematical model of architecture of an information system of the enterprise, the information system architecture supporting the business process design, layers of the multi-layer model comprising a business layer, an application layer, and a technology layer;

modeling performance metrics of the multi-layer model under a first set of operational parameters, said modeling including dimensions of cost, quality of service and throughput;

generating a second set of operational parameters, the second set being distinct from the first set of operational parameters by one set of variables, the one set of variables include at least one of;

failure of a component of the system architecture, a delay of an operation, a change in a sequence of operations, and an alternative mode of operation;

modeling performance metrics of the multi-layer model under the second set of operational parameters, said modeling including dimensions of cost, quality of service and throughput;

comparing the performance metrics of the second set of operational parameters against at least one of the performance metrics of the first set of operational parameters and a set of predetermined thresholds; and

reporting, based on the comparison, characteristics of the information system architecture under the second set of operational parameters.

2. The method of claim 1, wherein reporting the characteristics of the information system architecture includes reporting the performance metrics under the second set of operational parameters relative to the set of predetermined thresholds.

3. The method of claim 2, wherein the set of predetermined thresholds include dimensions of cost, quality of service and throughput.

4. The method of claim 1, wherein reporting the characteristics of the information system architecture includes reporting a difference in performance metrics resulting from the first set of operational parameters and the second set of operational parameters.

5. The method of claim 4, further comprising comparing the difference in performance metrics against a threshold.

6. The method of claim 1, wherein generating the second set includes:

analyzing a record of operation of the information system architecture; and

selecting the one set of variables as a function of at least one of a historical trend, a pattern and a fault as indicated in the record.

7. The method of claim 1, wherein the mathematical model includes characteristics corresponding to changes in components of the system relative to an operational time of the system.

8. The method of claim 1, wherein the mathematical model includes characteristics corresponding to changes in connections between components of the system relative to an operational time of the system.

9. The method of claim 1, further comprising identifying an adverse event from the characteristics of the information system architecture under the second set of operational parameters.

10. The method of claim 9, wherein the adverse event includes a change in behavior of the system that exceeds a threshold of change over time.

11. The method of claim 10, wherein the adverse event includes a singularity.

12. The method of claim 9, further comprising identifying a component of the system that is proximate to the adverse event.

13. The method of claim 12, further comprising identifying a series of components operationally linked between the one set of variables and the component proximate to the adverse event.

14. The method of claim 13, further comprising identifying characteristics of the series of components contributing to the adverse event.

15. A computer implemented method for evaluating operation of a system architecture, comprising:

obtaining a mathematical model of architecture of a system, the model including a plurality of components, a description of the connections and functional relationships between the components, and a description of the behavior each component in response to system functions and the internal state of the component;

modeling performance metrics of the model under a first set of operational parameters, said modeling including dimensions of cost, quality of service and throughput;

generating a second set of operational parameters, the second set being distinct from the first set of operational parameters by one set of variables, the one set of variables include at least one of;

failure of a component of the system architecture, a delay of an operation, a change in a sequence of operations, and an alternative mode of operation;

modeling performance metrics of the model under the second set of operational parameters, said modeling including dimensions of cost, quality of service and throughput;

comparing the performance metrics of the second set of operational parameters against at least one of the performance metrics of the first set of operational parameters and a set of predetermined thresholds; and

reporting, based on the comparison, characteristics of the information system architecture under the second set of operational parameters.