Generating estimated efficiency models for selecting a processing unit in a storage network

1. A method for execution by a computing device of a storage network comprises:

generating a plurality of estimated efficiency models associated with a plurality of processing units of the storage network, wherein an estimated efficiency model of the plurality of estimated efficiency models includes estimated efficiency probabilities, and wherein the estimated efficiency probabilities corresponds to data access request types for a processing unit of the plurality of processing units; and

storing the plurality of estimated efficiency models in memory of the storage network.

2. The method of claim 1 further comprises:

receiving a data access request;

selecting a processing unit from the plurality of processing units based on the plurality of estimated efficiency models; and

sending the data access request to the selected processing unit for execution.

3. The method of claim 2 further comprises:

determining, by the computing device, an actual processing efficiency of a processing of the data access request by the selected processing unit; and

updating, by the computing device, the estimated efficiency model of the selected processing unit based on the actual processing efficiency.

4. The method of claim 2 , wherein the selecting the processing unit of the processing units is based on a randomizing factor to produce the selected processing unit.

5. The method of claim 4 , wherein the selecting the processing unit of the processing units comprises:

when the randomizing factor indicates selecting an estimated most efficient processing of the data access request, selecting the one of the processing units having a highest estimated efficiency probability for a type of data access request of the data access request types.

6. The method of claim 5 , wherein the selecting the one of the processing units comprises:

when the randomizing factor indicates selecting an estimated second-most efficient processing of the data access request, selecting the one of the processing units having a second highest estimated efficiency probability for the type of data access request; and

when the randomizing factor indicates selecting an estimated third-most efficient processing of the data access request, selecting the one of the processing units having a third highest estimated efficiency probability for the type of data access request.

7. The method of claim 4 , wherein the selecting the processing unit of the processing units comprises:

when the randomizing factor indicates randomly selecting, and when the estimated efficiency processing of the data access request is above an efficiency threshold, selecting the one of the processing units at random.

8. The method of claim 1 , wherein the generating a plurality of estimated efficiency models is based on historical performance data.

9. The method of claim 1 , wherein the generating a plurality of estimated efficiency models is based on estimated performance data.

10. The method of claim 1 , wherein the generating a plurality of estimated efficiency models is based on network bandwidth.

11. The method of claim 1 , wherein the generating a plurality of estimated efficiency models is based on network reliability.

12. The method of claim 1 , wherein the generating a plurality of estimated efficiency models is based on processing resources of the plurality of processing units.

13. The method of claim 1 , wherein the generating a plurality of estimated efficiency models is based on data access request volumes.

14. The method of claim 1 , wherein an estimated efficiency probability of the estimated efficiency probabilities comprises an estimated time to complete the data access request by the processing unit.

15. The method of claim 1 , wherein an estimated efficiency probability of the estimated efficiency probabilities comprises an estimated probability that the estimated time will be met.

16. The method of claim 1 , wherein an estimated efficiency probability of the estimated efficiency probabilities comprises an estimated probability of an error occurring when executing the data access request.

17. The method of claim 1 , wherein an estimated efficiency probability of the estimated efficiency probabilities comprises an estimated probability of a connection failure prior to fulfillment of the data access request.