Compact schedules for resource-constrained devices

• US 10,223,160 B2
• Filed: 08/29/2016
• Issued: 03/05/2019
• Est. Priority Date: 08/31/2015
• Status: Active Grant

• Current Assignee: Ayla Networks, Inc.
• Original Assignee: Ayla Networks, Inc.
• Inventors: Vora, Jigar, Eykholt, Joseph R., Sundaresan, Sudha, Rivera, Pablo Sebastian, Friedman, David Russell, Caceres, Adrian
• Primary Examiner(s): Dascomb, Jacob D
• Application Number:
  US15/250,652
• Publication Number:
  US 20170060629A1
• Time in Patent Office: 918 Days
• CPC Class Codes: G06F 11/07 Responding to the occurrence of a fault, e.g. fault tolerance
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
• CPC Class Codes: G06F 9/542 Event management; Broadcasting; Multicasting; Notifications
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems

Abstract

A processing device executing a scheduler receives, by a device, a schedule from a remote server computing device, the schedule having a compact format that is understood by the device. The device stores the schedule and the processing device parses the schedule to identify a scheduled event. The processing device executes the scheduled event at a specified time in accordance with the schedule even in the absence of a network connection between the device and the remote server computing device.

Claims

1. A method comprising:

receiving, by a processing device, an instruction to schedule an event associated with a remote target device, wherein the remote target device is installed at a location;

generating a schedule for the remote target device based on the instruction;

translating, by the processing device, the schedule into a compact format;

transmitting the translated schedule to the remote target device, wherein the transmitting causes the remote target device to store the translated schedule;

receiving usage information from the remote target device and additional usage information generated by one or more additional remote devices also installed at the location;

applying a machine learning algorithm to the usage information and the additional usage information to determine an update to the schedule;

updating the schedule;

translating the updated schedule into the compact format; and

transmitting the translated updated schedule to the remote target device, wherein the transmitting of the translated updated schedule causes the remote target device to store the translated updated schedule and execute the event at a specified time in accordance with the translated updated schedule, wherein the event is executable by the remote target device even in the absence of a connection between processing device and the remote target device.

2. The method of claim 1, wherein the compact format comprises a binary format, and wherein translating the schedule into the compact format comprises encoding the schedule into the binary format, the binary format comprising encodings for at least one of a start time, an end time, a device property, or a frequency.

3. The method of claim 1, wherein the target device is a gateway device or network-connected device comprising an embedded system.

4. The method of claim 1, wherein receiving the instruction comprises receiving the instruction via an Application Programming Interface (API) from at least one of a third-party service or an application executing in a mobile device.

5. The method of claim 1, wherein the additional usage information is received from a third-party system that manages the one or more additional remote devices.

6. The method of claim 1, wherein execution of the event comprises activation of at least one of a rule associated with the remote target device or an additional schedule associated with the remote target device.

7. The method of claim 1, wherein the remote target device is installed at a household, the method further comprising:

receiving an indication from an additional remote device also installed at the household that the household is unoccupied; and

sending a message to the remote target device to cause the remote target device to disable execution of the event or translated schedule.

8. A method, comprising:

receiving, by a device installed at a location, a schedule from a remote server computing device, the schedule having a compact format;

storing the schedule by the device;

parsing the schedule to identify a scheduled event;

executing, by the device, the scheduled event at a specified time in accordance with the schedule, wherein the scheduled event is executed even in the absence of a network connection between the device and the remote server computing device;

sending usage information to the remote server computing device, wherein the remote server computing device applies a machine learning algorithm to the usage information and additional usage information from an additional device also installed at the location to determine an update to the schedule;

receiving the updated schedule from the remote server computing device, the updated schedule also having the compact format;

parsing the updated schedule to identify a new scheduled event; and

executing, by the device, the new scheduled event at a new specified time in accordance with the updated schedule.

9. The method of claim 8, wherein the compact format comprises a binary format, the binary format comprising encodings for at least one of a start time, an end time, a device property, or a frequency.

10. The method of claim 8, further comprising:

receiving a timing signal from the server computing device;

assigning a first count of a counter to a first time based on the timing signal; and

determining a second count of the counter that corresponds to the specified time, wherein the scheduled event is executed when the counter reaches the second count.

11. The method of claim 8, wherein the scheduled event comprises a first operation, a second operation, and a duration between the first operation and the second operation, and wherein executing the scheduled event comprises performing the first operation at the specified time, waiting the duration, and performing the second operation after the duration has elapsed.

12. The method of claim 8, wherein the device is a gateway device, wherein the schedule is for a target device having a wireless connection to the gateway device, and wherein executing the scheduled event comprises transmitting one or more commands to the target device at the specified time.

13. The method of claim 12, further comprising:

receiving an additional schedule having the compact format, wherein the additional schedule is for an additional target device that is managed by the gateway device;

storing the additional schedule;

parsing the additional schedule to identify an additional scheduled event; and

executing the additional scheduled event at an additional specified time in accordance with the additional schedule, wherein executing the additional scheduled event comprises transmitting one or more additional commands to the additional target device at the additional specified time.

14. A device comprising:

a memory;

a network interface; and

a processing device operatively coupled to the memory, wherein the processing device is to;

receive, via the network interface, a schedule from a remote server computing device, the schedule having a compact format that is understood by the device;

store the schedule in the memory;

parse the schedule to identify a scheduled event;

execute the scheduled event at a specified time in accordance with the schedule, wherein the scheduled event is executed even in the absence of a network connection between the device and the remote server computing device;

send usage information to the remote server computing device, wherein the remote server computing device applies a machine learning algorithm to the usage information and additional usage information from an additional device installed at a same location as the device to determine an update to the schedule;

receive the updated schedule from the remote server computing device, the updated schedule also having the compact format;

parse the updated schedule to identify a new scheduled event; and

execute the new scheduled event at a new specified time in accordance with the updated schedule.

15. The device of claim 14, wherein the compact format comprises a binary format, the binary format comprising encodings for at least one of a start time, an end time, a device property, or a frequency.

16. The device of claim 14, wherein the processing device is further to:

receive a timing signal from the server computing device;

assign a first count of a counter to a first time based on the timing signal; and

determine a second count of the counter that corresponds to the specified time, wherein the scheduled event is to execute when the counter reaches the second count.

17. The device of claim 14, wherein the scheduled event comprises a first operation, a second operation, and a duration between the first operation and the second operation, and wherein to execute the scheduled event the processing device is to perform the first operation at the specified time, to wait the duration, and to perform the second operation after the duration has elapsed.

18. The device of claim 14, wherein the device is a gateway device, the device having a wireless interface, wherein the schedule is for a target device having a wireless connection to the gateway device via the wireless interface, and wherein to execute the scheduled event the processing device is to transmit one or more commands to the target device at the specified time using the wireless interface.

19. The device of claim 18, the device having an additional wireless interface, wherein the processing device is further to:

receive an additional schedule having the compact format, wherein the additional schedule is for an additional target device that is managed by the gateway device;

store the additional schedule in the memory of the device;

parse the additional schedule to identify an additional scheduled event; and

execute the additional scheduled event at an additional specified time in accordance with the additional schedule, wherein to execute the additional scheduled event the processing device is to transmit one or more additional commands to the additional target device at the additional specified time, via the additional wireless interface.

20. A non-transitory computer readable storage medium comprising instructions that, when executed by a processing device, cause the processing device to:

receive an instruction to schedule an event associated with a remote target device, wherein the remote target device is installed at a location;

generate a schedule for the remote target device based on the instruction;

translate the schedule into a compact format;

transmit the translated schedule to the remote target device, wherein transmittal of the translated schedule causes the remote target device to store the translated schedule;

receive usage information from the remote target device and additional usage information generated by one or more additional devices also installed at the location;

apply a machine learning algorithm to the usage information and the additional usage information to determine an update to the schedule;

update the schedule;

translate the updated schedule into the compact format; and

transmit the translated updated schedule to the remote target device, wherein transmittal of the translated updated schedule causes the remote target device to store the translated updated schedule and execute the event at a specified time in accordance with the translated updated schedule, wherein the event is executable by the remote target device even in the absence of a connection between processing device and the remote target device.

21. The non-transitory computer readable storage medium of claim 20, wherein the compact format comprises a binary format, and wherein translating the schedule into the compact format comprises encoding the schedule into the binary format, the binary format comprising predetermined encodings for at least one of a start time, an end time, a device property, or a frequency.