SYSTEMS AND METHODS FOR ADAPTIVE COMPUTER CODE PROCESSING BY COMPUTING RESOURCE STATE-AWARE FIRMWARE

• US 20190034246A1
• Filed: 07/28/2017
• Published: 01/31/2019
• Est. Priority Date: 07/28/2017
• Status: Abandoned Application

• Current Assignee: Swfl Inc.
• Original Assignee: Swfl Inc.
• Inventors: Miller, Jeremie, Muldowney, Thomas, Clift-Jennings, Allison
• Application Number:
  US15/662,591
• Publication Number:
  US 20190034246A1
• Time in Patent Office: Days
• CPC Class Codes: G06F 2009/45583 Memory management, e.g. access or allocation
• CPC Class Codes: G06F 9/45529 Embedded in an application, e.g. JavaScript in a Web browser
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06F 9/5094 where the allocation takes into account power or heat criteria power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The systems and methods for operating an autonomous device with a constraint-aware firmware includes: identifying a request to execute a script; identifying one or more computing resource costs associated with executing the script by one or more computing resources of the autonomous device; detecting a state of each of the one or more computing resources of the autonomous device; in response to (i) identifying the one or more computing resource costs and (ii) detecting the state each of the one or more computing resources of the autonomous device, executing or not executing the scripts.

Claims

1. A system of operating an autonomous device using an energy-aware firmware, the system comprising:

an autonomous device having;

an energy source that powers one or more operations of the autonomous device;

a virtual machine that receives a script processing request, wherein the script processing request identifies a computer-executable script;

a firmware that is in operable command communication with the virtual machine;

prior to executing the script, the virtual machine analyzes the script and reveals to the firmware each of one or more control functions of the script and/or one or more logic functions of the script;

wherein, in response to the revealed information, the firmware determines;

(i) an energy state of the energy source, the energy state indicating an amount of power available to perform the one or more operations of the autonomous device;

(ii) an energy cost for executing the script, wherein the energy cost indicates an amount of power required by the autonomous device to execute the script;

(iii) generating execution instructions based on the energy state of the energy source and the energy cost for executing the script, wherein the execution instructions indicate whether or not to execute the script by the virtual machine; and

(iv) transmitting the execution instructions to the virtual machine.

2. The system of claim 1, further comprising:

at the virtual machine;

receiving the execution instructions indicating whether or not to execute the script;

wherein if the execution instructions include instructions to execute the script, identifying which of the one or more control functions of the script and/or the one or more logic functions of the script to execute; and

selectively executing less than an entirety of the script based on the execution instructions.

3. The system of claim 1,

at the firmware:

wherein the one or more control functions of the script comprises a plurality of control functions and wherein the one or more logic functions comprises a plurality of logic functions;

selectively identifying which of the plurality of control functions and/or which of the plurality of the logic functions to execute based on the energy state of the energy source and the energy cost for executing the script;

wherein the execution instructions comprise instructions to execute only a portion and not all of the plurality of control functions and/or a portion and not all of the plurality of logic functions of the script.

4. The system of claim 1, wherein the scripts comprise lambda functions that are dynamically loaded to a dynamic memory of the autonomous device based on an occurrence of a triggering event,

upon occurrence of the triggering event, the lambda function is only loadable to the dynamic memory if one or more control functions and/or one or more logic functions of the lambda function are validated against a digital smart contract, wherein the digital smart contract comprises machine-enforceable contract terms.

5. A method of operating an autonomous device with a computing resource state-aware firmware, the method comprising:

at an autonomous device;

identifying a request to execute a script;

identifying one or more computing resource costs associated with executing the script by one or more computing resources of the autonomous device;

detecting a state of each of the one or more computing resources of the autonomous device;

in response to (i) identifying the one or more computing resource costs and (ii) detecting the state of each of the one or more computing resources of the autonomous device, executing or not executing the scripts.

6. The method of claim 5, wherein the request comprises an indication of one or more control operations and/or one or more logic operations of the script, wherein the wherein identifying the one or more computing resource costs is based on determining a computing cost for each of the one or more control operations and/or the one or more logic operations of the script.

7. The method of claim 5, wherein the script comprises a lambda function, wherein the lambda function comprises a single-purpose script that is dynamically loaded to a dynamic memory of the autonomous device at time of execution.

8. The method of claim 6, wherein identifying the one or more computing resource costs associated with executing the script includes identifying for each of the one or more control operations and/or for each of the one or more logic operations of the script a respective computing cost.

9. The method of claim 5, wherein identifying the one or more computing resource costs associated with executing the script includes:

identifying a memory cost for executing the script, wherein the memory cost comprises an amount of a memory resource of the autonomous device that would be used when executing the script; and

identifying an energy cost for executing the script, wherein the energy cost comprises an amount of an energy resource of the autonomous device that would be used when executing the scripts.

10. The method of claim 5, wherein detecting the state of the one or more computing resources includes one or more of:

(i) identifying an energy level of an energy supply of the autonomous device, wherein the energy level of the energy supply defines an available amount of energy at the energy supply or an amount of energy expended by the energy supply; and

(ii) identifying a memory level of a memory of the autonomous device, wherein the memory level of the memory defines an available amount of memory at the memory or an amount of memory expended by the memory.

11. The method of claim 5, wherein the one or more computing resources comprise an energy supply of the autonomous device, wherein detecting the state of the one or more computing resources includes determining an energy level of the energy supply;

and

further comprising;

determining whether or not to execute the script based on the energy level of the energy supply.

12. The method of claim 11, wherein the determining whether or not to execute the script includes:

(i) if the energy level of the energy supply satisfies an execution threshold, then generating instructions to execute the script, or

(ii) if the energy level of the energy supply does not satisfy the execution threshold, then generating instructions not to execute the script.

13. The method of claim 5, further comprising:

executing the script,

wherein executing the script includes selectively executing only a portion of the one or more control operations and/or the one or more logic operations of the script to thereby reduce an amount of the one or more computing resources expended during execution of the script.

14. The method of claim 12, wherein the execution threshold comprises a continuum including a plurality of thresholds, wherein each of the plurality of thresholds, respectively, indicates different execution parameters for different energy levels of the energy supply, the different execution parameters indicating an extent to which a script can be executed;

wherein the determining whether or not to execute the script includes;

comparing the energy level of the energy supply to the plurality of thresholds of the continuum;

identifying one threshold of the plurality of threshold satisfied by the energy level of the energy supply;

identifying execution parameters associated with the one threshold; and

generating instructions to execute a subset of the one or more control operations and/or a subset of the one or more logic operations of the script based on the execution parameters of the one threshold.

15. The method of claim 13, wherein selectively executing only a portion of the one or more control operations and/or the one or more logic operations of the script includes:

identifying a ranking for each of the one or more control operations and/or the one or more logic operations of the script, wherein the ranking includes a high ranking or a low ranking, wherein the high ranking is based on a control operation or a logic operation satisfying or exceeding a critical-to-operation threshold, wherein the low ranking is based on the control operation or the logic operation failing to satisfy the critical-to-operation threshold; and

wherein the portion that is executed includes the one or more control operations and/or the one or more logic operations identified as high in ranking.

16. The method of claim 15, further comprising:

identifying a different portion of the one or more control operations and/or the one or more logic operations of the script as low in ranking; and

redirecting the different portion to a queue based on the low ranking.

17. The method of claim 5, wherein the autonomous devices comprises one or more computer processors that implements firmware and a virtual machine,

wherein the firmware identifies the one or more computing resource costs and detects the state of each of the one or more computing resources;

and

wherein the virtual machine executes or does not execute the script based on instructions from the firmware.

18. A method of processing operations of an autonomous device in accordance with a computing resource state, the method comprising:

at an autonomous device;

detecting an occurrence of an event;

determining that the occurrence of the event triggers a potential execution of a script;

validating the event and a functionality of the script against a digital smart contract;

in response to a successful validation of the event and the functionality of the script, dynamically loading the script to a dynamic memory accessible to a virtual machine, wherein the virtual machine is configured to execute the script;

identifying each of the one or more control functions and/or the one or more logic functions of the script by decomposition of the script;

detecting a state of each of the one or more computing resources of the autonomous device;

in response to detecting the state of each of the one or more computing resources of the autonomous device, executing or not executing the scripts.

19. The method of claim 18, wherein a firmware of the autonomous device evaluates the script for execution and previews each of the one or more control operations and/or the one or more logic operations of the script to a firmware,

wherein the firmware decides which of the one or more control operations and/or the one or more logic of the script to execute based on the state of each of the one or more computing resources of the autonomous device.

20. The method of claim 19, wherein the one or more computing resources includes a limited energy source of the autonomous device, wherein the state of the energy source indicates an energy level of the energy source.