Orchestrator reporting of probability of downtime from machine learning process
Disclosed embodiments relate to reporting Electronic Control Unit (ECU) errors or faults to a remote monitoring server. Operations may include receiving operational data from a plurality of ECUs in the vehicle, the operational data being indicative of a plurality of runtime attributes of the plurality of ECUs; generating, through a machine learning process, a statistical model of the operational data; receiving live, runtime updates from the plurality of ECUs in the communications network of the vehicle; identifying an ECU error associated with an ECU in the communications network of the vehicle, the ECU error being determined by a comparison of the live, runtime updates with the statistical model of the operational data to identify at least one deviation from the operational data; and wirelessly sending a report to the remote monitoring server based on the live, runtime updates, the report identifying the ECU and the identified ECU error.
1. A non-transitory computer-readable medium including instructions that, when executed by at least one processor, cause the at least one processor to perform error-monitoring operations for remediating controller errors, comprising:
receiving operational data from a plurality of controllers, the operational data being indicative of a plurality of runtime attributes associated with the plurality of controllers, the plurality of runtime attributes comprising at least one of a memory activity or a processing activity;
generating a model of the operational data received from the plurality of controllers based on a predetermined set of controller functionalities, wherein the model is based on time-based analysis of controller attributes associated with one or more of the plurality of controllers, the controller attributes associated with the plurality of controllers comprising at least one of a central processing unit operation, information stored in a memory component, or information accessed from a memory component;
receiving live, runtime updates from the plurality of controllers; and
identifying, based on a comparison of the live, runtime updates to the model, an error of a monitored controller.
2. The non-transitory computer-readable medium of claim 1 , wherein the operational data is received from the plurality of controllers in response to a poll.
3. The non-transitory computer-readable medium of claim 1 , wherein the controller attributes comprise at least one of central processing unit usage, memory usage, a memory sequence accessed, cache content, access history, or a page fault.
4. The non-transitory computer-readable medium of claim 1 , wherein the model is based on a frequency or execution path of software associated with at least one of the plurality of controllers.
5. The non-transitory computer-readable medium of claim 1 , wherein the model is based on a frequency or execution path of software associated with the plurality of controllers.
6. The non-transitory computer-readable medium of claim 1 , wherein the runtime updates comprise at least one of an identification of a delta file of at least one of the controllers, a software version of at least one of the controllers, or contents of a memory of at least one of the controllers.
7. The non-transitory computer-readable medium of claim 1 , wherein the error-monitoring operations further comprise implementing a control action for the monitored controller based on the identified error.
8. The non-transitory computer-readable medium of claim 7 , wherein the control action comprises causing the monitored controller to adjust from being configured to execute a first version of controller software to a second version of controller software in response to the identified error.
9. The non-transitory computer-readable medium of claim 7 , wherein the control action comprises causing the monitored controller to be placed in a safe mode.
10. The non-transitory computer-readable medium of claim 1 , wherein the error-monitoring operations further comprise comparing the live, runtime updates to the model.
11. The non-transitory computer-readable medium of claim 1 , wherein the identified error comprises at least one of a runtime error, a stack overflow error, or drifting of an application execution profile.
12. The non-transitory computer-readable medium of claim 1 , wherein the model is configured to account for on-board diagnostic error messages.
13. The non-transitory computer-readable medium of claim 1 , wherein the controllers are distributed across a wide area communications network.
14. The non-transitory computer-readable medium of claim 1 , wherein the model is configured to apply a machine learning function to determine if at least one of the plurality of controllers is operating within a predetermined envelope of operational attributes.
15. The non-transitory computer-readable medium of claim 1 , wherein the controllers are of a common controller type.
16. A computer-implemented method for remediating controller errors, comprising:
receiving operational data from a plurality of controllers, the operational data being indicative of a plurality of runtime attributes associated with the plurality of controllers, the plurality of runtime attributes comprising at least one of a memory activity or a processing activity;
generating a model of the operational data received from the plurality of controllers based on a predetermined set of controller functionalities, wherein the model is based on time-based analysis of controller attributes associated with one or more of the plurality of controllers, the controller attributes associated with the plurality of controllers comprising at least one of a central processing unit operation, information stored in a memory component, or information accessed from a memory component;
receiving live, runtime updates from the plurality of controllers; and
identifying, based on a comparison of the live, runtime updates to the model, an error of a monitored controller.
17. The computer-implemented method of claim 16 , wherein the runtime updates comprise at least one of an identification of a delta file of at least one of the controllers, a software version of at least one of the controllers, or contents of a memory of at least one of the controllers.
18. The computer-implemented method of claim 16 , further comprising implementing a control action for the monitored controller based on the identified error, wherein the control action comprises at least one of:
causing the monitored controller to adjust from being configured to execute a first version of controller software to a second version of controller software in response to the identified error; or
causing the monitored controller to be placed in a safe mode.
19. The computer-implemented method of claim 16 , wherein the identified error comprises at least one of a runtime error, a stack overflow error, or drifting of an application execution profile.
20. The computer-implemented method of claim 16 , wherein the controllers are of a common controller type.