Safeguard and recovery of internet of things (IoT) devices from power anomalies
View Patent ↗Systems and methods for safeguarding and recovering Internet-of-Things (IoT) devices from power anomalies. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory including program instructions stored thereon that, upon execution by the processor, cause the IHS to: detect an electrical power anomaly in an IoT network based, at least in part, upon a comparison between a current volatility of a data field and a volatility baseline for that data field, wherein the data field is part of a packet communicated between an IoT device and the IHS; and in response to the detection, manage the IoT network.
1. An Information Handling System (IHS), comprising:
one or more processors; and
a memory coupled to the one or more processors, the memory including program instructions stored thereon that, upon execution by the one or more processors, cause the IHS to:
detect an electrical power anomaly in an Internet-of-Things (IoT) network based, at least in part, upon a comparison between a current volatility of a data field and a volatility baseline for the data field, wherein the data field is part of a packet communicated between an IoT device and the IHS;
identify: (i) a sensitivity value of the IoT device with respect to the detected electrical power anomaly, wherein the sensitivity value is a binary value that indicates whether the detected electrical power anomaly is expected to affect the IoT device, and (ii) a priority value of the IoT device in the IoT network;
calculate a safeguard and recovery indicator as a weighted sum of the sensitivity value and the priority value; and
in response to the detection, manage the IoT network, at least in part, using the safeguard and recovery indicator of the IoT device.
2. The IHS of claim 1 , wherein the electrical power anomaly is selected from the group consisting of: power failure, power sag, power surge, under-voltage, over-voltage, electrical line noise, electromagnetic interference, frequency variation, switching transient, and harmonic distortion.
3. The IHS of claim 1 , wherein detecting the power anomaly includes forecasting the power anomaly in anticipation of the anomaly taking place.
4. The IHS of claim 1 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to shut down one or more IoT devices based upon a priority value associated with the one or more IoT devices.
5. The IHS of claim 4 , wherein the priority value is based, at least in part, upon at least one of: a physical location of the IoT device, or a role of the IoT device within the IoT network.
6. The IHS of claim 1 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to instruct each of the one or more IoT devices to boot up in an order corresponding to the priority value.
7. The IHS of claim 1 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to stop processing data received from one or more IoT devices.
8. The IHS of claim 1 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to instruct the one or more IoT devices to reduce a data collection rate of one or more sensors.
9. The IHS of claim 8 , wherein the one or more IoT devices include the IoT device, and wherein the IoT device includes a sensor that produces data included in the data field.
10. A hardware memory device having program instructions stored thereon that, upon execution by an Information Handling System (IHS), cause the IHS to:
detect an electrical power anomaly in an Internet-of-Things (IoT) network based, at least in part, upon a comparison between a current volatility of a data field and a volatility baseline for the data field, wherein the data field is part of a packet communicated between an IoT device and the IHS;
identify: (i) a sensitivity value of the IoT device with respect to the detected electrical power anomaly, wherein the sensitivity value is a scalar value that indicates a degree to which the detected electrical power anomaly is expected to affect the IoT device, and (ii) a priority value of the IoT device in the IoT network;
calculate a safeguard and recovery indicator as a weighted sum of the sensitivity value and the priority value; and
in response to the detection, manage the IoT network, at least in part, using the safeguard and recovery indicator of the IoT device.
11. The hardware memory device of claim 10 , wherein the electrical power anomaly is selected from the group consisting of: power failure, power sag, power surge, under-voltage, over-voltage, electrical line noise, electromagnetic interference, frequency variation, switching transient, and harmonic distortion.
12. The hardware memory device of claim 10 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to shut down one or more IoT devices based upon a priority value associated with the one or more IoT devices.
13. The hardware memory device of claim 12 , wherein the priority value is based, at least in part, upon at least one of: a physical location of the IoT device, or a role of the IoT device within the IoT network.
14. The hardware memory device of claim 12 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to instruct each of the one or more IoT devices to boot up in an order corresponding to the priority value.
15. The hardware memory device of claim 10 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to stop processing data received from one or more IoT devices or to instruct the one or more IoT devices to reduce a data collection rate of one or more sensors.
16. A method, comprising:
detecting an electrical power anomaly in an Internet-of-Things (IoT) network based, at least in part, upon a comparison between a current volatility of a data field and a volatility baseline for the data field, wherein the data field is part of a packet communicated between an IoT device and the IHS;
identifying: (i) a sensitivity value of the IoT device with respect to the detected electrical power anomaly, wherein the sensitivity value is binary or a scalar value that indicates how much the detected electrical power anomaly is expected to affect the IoT device, and (ii) a priority value of the IoT device in the IoT network;
calculating a safeguard and recovery indicator as a weighted sum of the sensitivity value and the priority value; and
in response to the detection, managing the IoT network, at least in part, using the safeguard and recovery indicator of the IoT device.
17. The method of claim 16 , wherein the electrical power anomaly is selected from the group consisting of: power failure, power sag, power surge, under-voltage, over-voltage, electrical line noise, electromagnetic interference, frequency variation, switching transient, and harmonic distortion.
18. The method of claim 16 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to shut down one or more IoT devices based upon a priority value associated with the one or more IoT devices.
19. The method of claim 18 , wherein the priority value is based, at least in part, upon at least one of: a physical location of the IoT device, or a role of the IoT device within the IoT network.
20. The method of claim 16 , wherein to manage the IoT network, the program instructions, upon execution, further cause the IHS to stop processing data received from one or more IoT devices or to instruct the one or more IoT devices to reduce a data collection rate of one or more sensors.