Methods, devices and systems for coordinating and optimizing resources

• US 8,776,074 B1
• Filed: 01/12/2011
• Issued: 07/08/2014
• Est. Priority Date: 01/22/2010
• Status: Active Grant

• Current Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Original Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Inventors: DiMario, Michael J., Heisler, Jeffrey H., Barbera, Janet
• Primary Examiner(s): Bullock, Jr., Lewis A
• Assistant Examiner(s): Lu, Kevin X
• Application Number:
  US13/005,123
• Time in Patent Office: 1,273 Days
• Field of Search: 718/104
• US Class Current: 718/104
• CPC Class Codes: G06F 9/4806 Task transfer initiation or dispatching
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/5016 the resource being the memory
• CPC Class Codes: G06F 9/52 Program synchronisation; Mutual exclusion, e.g. by means of semaphores
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations

Abstract

A representative method for coordinating and optimizing resources in the completion of a set of tasks includes providing multiple task types defined for a scenario and task priorities; combining multiple solutions of the respective multiple task types into multiple candidate decisions; determining candidate scores for the respective multiple candidate decisions based on the combined multiple solutions of the respective multiple task types; determining an optimal candidate score based on the candidate scores from the respective multiple candidate decisions and task priorities; and selecting an optimal response to a given scenario based on the candidate decision based on having the determined optimal candidate score.

Claims

1. A method for coordinating and optimizing resources in real time for the completion of a set of tasks comprising:

providing multiple task types defined for a scenario and task priorities each task type representing a high level request used as a structure for a specific request to complete a task in the set of tasks;

determining a current operating condition;

defining a plurality of solutions for each task in the set of tasks based on the task type of each task;

combining a respective solution associated with each task in the set of tasks, to define a candidate decision for the set of tasks;

determining a plurality of candidate decisions based on all possible combinations of the plurality of solutions for each task of the set of tasks;

determining candidate scores for each of the plurality of candidate decisions, the candidate score being the sum of the scores of the plurality of solutions in the corresponding candidate decision, comprising;

determining the score for each solution in the respective candidate decision using a set of one to n criteria based on the task type of the task that the solution performs and applying weights to each criterion of each solution, wherein weights are based on a task priority assigned to the task associated with each solution and the current operating condition;

determining an optimal candidate decision as the candidate decision of the plurality of candidate decision with the overall highest candidate score, and

selecting and executing the determined optimal candidate decision for the current operating condition,

wherein the method is implemented by a computing device comprising a processing device and memory which has instructions that are executed by the processing device.

2. The method as defined in claim 1, further comprising penalizing a candidate score when negative conflicts are detected between the plurality of solutions and other conflicting tasks.

3. The method as defined in claim 1, further comprising rewarding a candidate score when positive interferences are detected between the plurality of solutions and other complementary tasks.

4. The method as defined in claim 1, wherein determining the optimal candidate score is achieved by determining a highest candidate score from the respective multiple candidate decisions.

5. A computing device comprising:

a processing device; and

memory including a resource coordination module which has instructions that are executed by the processing device, the instructions including the following logics;

receiving multiple task types defined for a scenario and task priorities each task type representing a high level request used as a structure for a specific request to complete a task in the set of tasks,

determining a current operating condition;

defining a plurality of solutions for each task in the set of tasks based on the task type of each task;

combining a respective solution associated with each task in the set of tasks to define a candidate decision for the set of tasks,

determining a plurality of candidate decisions based on all possible combinations of the plurality of solutions for each task of the set of tasks;

determining candidate scores for each of the plurality of candidate decisions, the candidate score being the sum of the scores of the plurality of solutions in the corresponding candidate decision comprising;

determining the score for each solution in the respective candidate decision using a set of one to n criteria based on the task type of the task that the solution performs and applying weights to each criterion of each solution, wherein weights are based on a task priority assigned to the task associated with each solution and the current operating condition;

determining an optimal candidate decision being the candidate decision of the plurality of candidate decisions with the overall highest score, and

selecting and executing the determined optimal candidate decision for the current operating condition.

6. The computing device as defined in claim 5, wherein the resource coordination module further comprises penalizing a candidate score when negative conflicts are detected between the plurality of solutions and other conflicting tasks.

7. The computing device as defined in claim 5, wherein the resource coordination module further comprises rewarding a candidate score when positive interferences are detected between the plurality of solutions and other complementary tasks.

8. The computing device as defined in claim 5, wherein determining the optimal candidate score is achieved by determining a highest candidate score from the respective multiple candidate decisions.

9. The computing device as defined in claim 5, wherein the resource coordination module further comprises issuing the combined multiple solutions for the optimal candidate decision to a user.

10. A system having multiple computing devices, each of the computing devices comprising a processing device and memory including instructions that are executed by the processing device, the system comprising:

a task repository module configured to receive multiple task types defined for a scenario and task priorities each task type representing a high level request used as a structure for a specific request to complete a task in a set of tasks based on a current operating condition;

a resource bid engine configured to store multiple solutions associated with each task in the set of tasks; and

a resource coordination optimization administrator configured to;

combine a respective solution associated with each task of the set of tasks to define a candidate decision for the set of tasks,

determine a plurality of candidate decisions based on all possible combinations of the plurality of solutions for each task of the set of tasks;

determine candidate scores for each of the plurality of candidate decisions, the candidate score being the sum of the scores of the plurality of solutions in the corresponding candidate decision comprising;

determining the score for each solution in the respective candidate decision using a set of 1 to n criteria based on the task type of the task that the solution performs and applying weights to each criterion of each solution, wherein weights are based on a task priority assigned to the task associated with each solution and the current operating condition;

determine an optimal candidate decision being the candidate decision of the plurality of candidate decisions with the overall highest score, and

select and execute the determined optimal candidate for the current operating condition.

11. The system as defined in claim 10, wherein the resource coordination optimization administrator further comprises penalizing a candidate score when negative conflicts are detected between the plurality of solutions and other conflicting tasks.

12. The system as defined in claim 10, wherein determining the optimal candidate score is achieved by determining a highest candidate score from the respective multiple candidate decisions.