Transaction-enabled systems and methods for predicting a forward market price utilizing external data sources and resource utilization requirements

1. A transaction-enabling system, comprising:

a controller configured to:

interpret a resource utilization requirement for a compute task;

interpret a plurality of external data sources, the plurality of external data sources comprising:

at least one additional third-party data source that is external to the transaction-enabling system data; and

a social media data source;

operate an expert system to:

generate a prediction of a forward market price for an online compute resource in response to the resource utilization requirement and a social data stream received from the social media data source;

maintain a training set comprising feedback data indicating outcomes of previous predictions of the forward market price in relation to at least one of facility parameters, yield, profitability, optimization of resources, optimization of business objectives, satisfaction of goals, satisfaction of users, or satisfaction of operators; and

train the expert system to iteratively self-adjust the prediction for the forward market price of the online compute resource, based on the feedback data of the training set; and

execute a transaction on a resource market for the online compute resource in response to determining that the prediction of the forward market price for the online compute resource is greater than a current market price for the online compute resource; and

a task system configured to assign the compute task having the resource utilization requirement to the online compute resource in response to the controller executing the transaction.

2. The system of claim 1 , wherein the plurality of external data sources further comprises an internet-of-things (IoT) data source.

3. The system of claim 1 , wherein:

the controller is further configured to operate the expert system to predict a second forward market price for a network bandwidth resource; and

the task system is further configured to assign a network task to the network bandwidth resource in response to the controller executing a second transaction for the network bandwidth resource.

4. The system of claim 1 , wherein:

the controller is further configured to operate the expert system to predict a second forward market price for a spectrum resource; and

the task system is further configured to assign a network task to the spectrum resource in response to the controller executing a second transaction for the spectrum resource.

5. The system of claim 1 , wherein:

the resource utilization requirement comprises a first resource, and

the online compute resource of the forward market price comprises at least one of:

the first resource, or

a second resource that can be substituted for the first resource.

6. The system of claim 5 , wherein the controller is further configured to:

operate the expert system to determine a substitution cost of the second resource; and

execute the transaction on the resource market further in response to the substitution cost of the second resource.

7. The system of claim 6 , wherein the expert system is further configured to determine at least a portion of the substitution cost of the second resource as an operational change cost for the task system.

8. The system of claim 1 , wherein the resource utilization requirement further requires at least one of: a network bandwidth resource, a spectrum resource, a data storage resource, an energy resource, or an energy credit resource.

9. A method, comprising:

interpreting a resource utilization requirement for a task system having a compute task;

interpreting a plurality of external data sources, the plurality of external data sources comprising one or more internet-of-things (IoT) data sources that are external to the task system;

operating an expert system to:

generate a prediction for a forward market price for an online compute resource in response to the resource utilization requirement and the plurality of external data sources;

maintain a training set comprising feedback data indicating outcomes of previous predictions of the forward market price and at least one of facility parameters, yield, profitability, optimization of resources, optimization of business objectives, satisfaction of goals, satisfaction of users, or satisfaction of operators; and

train the expert system to iteratively self-adjust the prediction for the forward market price of the online compute resource, based on the feedback data of the training set;

executing a transaction on a resource market for the online compute resource in response to determining that the prediction of the forward market price for the online compute resource is greater than a current market price for the online compute resource; and

assigning, by the task system, the resource utilization requirement to the online compute resource in response to the executing the transaction.

10. A method, comprising:

interpreting a resource utilization requirement for a task system having a compute task and a networking task, the compute task requiring an online compute resource, the networking task requiring at least one of a network bandwidth requirement and a network spectrum requirement;

interpreting a plurality of external data sources that are outside of the task system;

operating an expert system to:

generate a first prediction for a compute resource forward market price for the online compute resource in response to the resource utilization requirement and the plurality of external data sources;

generate a second prediction for a network resource forward market price for a network resource, comprising at least one of the network bandwidth resource and the network spectrum resource, in response to the resource utilization requirement and the plurality of external data sources;

maintain a training set comprising feedback data indicating outcomes of previous predictions of compute resource forward market prices and at least one of facility parameters, yield, profitability, optimization of resources, optimization of business objectives, satisfaction of goals, satisfaction of users, or satisfaction of operators; and

train the expert system to iteratively self-adjust the prediction for the compute resource forward market price of the online compute resource, based on the feedback data of the training set;

executing a first transaction on a resource market for the online compute resource in response to determining that the first prediction of the compute forward market price for the online compute resource is greater than a first current market price for the online compute resource;

assigning, by the task system, the compute task of the resource utilization requirement to the online compute resource in response to the executing the first transaction,

executing a second transaction for the network resource in response to determining that the second prediction of the network resource forward market price for the network resource is greater than a second current market price for the network resource;

assigning, by the task system, the network task of the resource utilization requirement to the network resource in response to the executing the second transaction.

11. A method, comprising:

interpreting a resource utilization requirement for a task system having a compute task;

interpreting a plurality of external data sources, the plurality of external data sources comprising at least one data source outside of the task system;

operating an expert system to:

generate a prediction for a forward market price for an online compute resource in response to the resource utilization requirement and the plurality of external data sources;

maintain a training set comprising feedback data indicating outcomes of previous predictions of the forward market price and at least one of facility parameters, yield, profitability, optimization of resources, optimization of business objectives, satisfaction of goals, satisfaction of users, or satisfaction of operators; and

train the expert system to iteratively self-adjust the prediction for the forward market price of the online compute resource, based on the feedback data of the training set;

executing a transaction on a resource market for the online compute resource in response to determining that the prediction of the forward market price for the online compute resource is greater than a current market price for the online compute resource; and

assigning, with the task system, the resource utilization requirement to the online compute resource in response to the executing the transaction,

wherein:

the plurality of external data sources comprises a social media data source, and

the operating the expert system to predict the forward market price for the online compute resource is further in response to a social data of the social media data source.

12. The method of claim 11 , wherein the forward market price comprises a forward market price for a network bandwidth resource.

13. The method of claim 11 , wherein the forward market price comprises a forward market price for a spectrum resource.

14. The method of claim 9 , wherein:

the resource utilization requirement comprises a first resource, and

the online compute resource of the forward market price comprises at least one of:

the first resource; or

a second resource that can be substituted for the first resource.

15. The method of claim 14 , further comprising:

operating the expert system to determine a substitution cost of the second resource; and

executing the transaction on the resource market further in response to the substitution cost of the second resource.

16. The method of claim 15 , further comprising determining at least a portion of the substitution cost of the second resource as an operational change cost for the task system.

17. The method of claim 16 , wherein the resource utilization requirement further requires at least one of: a network bandwidth resource, a spectrum resource, a data storage resource, an energy resource, or an energy credit resource.

18. The system of claim 1 , wherein the expert system predicting the forward market price for the online compute resource includes determining a likelihood of a surge of interest in the online compute resource based on the social data stream.

19. The system of claim 1 , wherein the predicting the forward market price for the online compute resource comprises determining a plurality of forward market prices for a plurality of cloud processing devices.

20. The system of claim 1 , wherein the predicted forward market price comprises an aggregate price for the online compute resource and a network resource.