EFFICIENT MESH NETWORK DATA GATHERING

• US 20190036801A1
• Filed: 12/28/2017
• Published: 01/31/2019
• Est. Priority Date: 12/28/2017
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Natarajan, Venkat, Ranganathan, Kumar, Sydir, Jaroslaw J., Vyas, Apoorv
• Granted Patent: US 10,778,556 B2
• Time in Patent Office: Days
• CPC Class Codes: H03M 7/3062 Compressive sampling or sensing
• CPC Class Codes: H04L 12/66 Arrangements for connecting between networks having differing types of switching systems, e.g. gateways
• CPC Class Codes: H04L 43/022 by sampling
• CPC Class Codes: H04L 43/0888 Throughput
• CPC Class Codes: H04L 45/12 Shortest path evaluation
• CPC Class Codes: H04L 45/48 Routing tree calculation
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks

Abstract

Systems and methods may be used to map and collect data from a mesh network at a gateway device connecting a plurality of devices (e.g., edge devices, IoT devices, sensors, or the like) to a network. A method may include determining a shortest path tree (SPT) map of the plurality of devices, the shortest path tree map may define the mesh network for the plurality of devices connected to the gateway. The method may include sampling data throughout the mesh network based on a compressive sensing (CS) sampling schedule. The sampled data may be output, such as to a remote device via the network. The sampled data may be saved at the gateway.

Claims

1. A gateway device for mapping and collecting data from a mesh network, the gateway device connecting a plurality of devices to a network and comprising:

a processor connected to memory, the memory including instructions, which when executed by the processor cause the processor to;

determine a shortest path tree (SPT) map of the plurality of devices, the shortest path tree map defining the mesh network for the plurality of devices connected to the gateway;

sample data throughout the mesh network based on a compressive sensing (CS) sampling schedule; and

output the sampled data to a remote device via the network.

2. The gateway device of claim 1, wherein to sample data throughout the mesh network, the processor is further to receive an encoded reading from a parent node connected to the gateway in the mesh network.

3. The gateway device of claim 2, wherein the encoded reading includes a linearly combined reading from each child node connected within the SPT map to the parent node.

4. The gateway device of claim 1, wherein connections among the plurality of devices are unknown before determining the SPT map.

5. The gateway device of claim 1, wherein connections between the gateway and all of the plurality of devices are unknown before determining the SPT map.

6. The gateway device of claim 1, wherein to sample data, the processor is further to increase a number of routes sampled in response to detecting an anomaly at a node within the SPT map.

7. The gateway device of claim 6, wherein the processor is further to dynamically change signal recovery parameters based on the detected anomaly.

8. The gateway device of claim 1, wherein to sample data, the processor is further to cycle through routes connected to the gateway starting at each leaf node, and producing a single transmission per route.

9. The gateway device of claim 1, wherein the SPT map is determined using Dijkstra'"'"'s algorithm using network constraints including a total number of nodes and radio ranges of nodes.

10. The gateway device of claim 1, wherein the processor is further to recover an entire sensor field of the mesh network using a minimization algorithm with a discrete cosine transform (DCT) coefficient at the gateway.

11. A method for mapping and collecting data from a mesh network at a gateway device connecting a plurality of devices to a network:

determining a shortest path tree (SPT) map of the plurality of devices, the shortest path tree map defining the mesh network for the plurality of devices connected to the gateway;

sampling data throughout the mesh network based on a compressive sensing (CS) sampling schedule; and

outputting the sampled data to a remote device via the network.

12. The method of claim 11, wherein sampling data throughout the mesh network includes receiving an encoded reading from a parent node connected to the gateway in the mesh network.

13. The method of claim 12, wherein the encoded reading includes a linearly combined reading from each child node connected within the SPT map to the parent node.

14. The method of claim 11, wherein sampling data includes increasing a number of routes sampled in response to detecting an anomaly at a node within the SPT map.

15. The method of claim 14, further comprising dynamically changing signal recovery parameters based on the detected anomaly.

16. The method of claim 11, wherein sampling data includes cycling through routes connected to the gateway starting at each leaf node, and producing a single transmission per route.

17. The method of claim 11, wherein the SPT map is determined using Dijkstra'"'"'s algorithm using network constraints including a total number of nodes and radio ranges of nodes.

18. The method of claim 11, further comprising recovering an entire sensor field of the mesh network using a minimization algorithm with a discrete cosine transform (DCT) coefficient at the gateway.

19. At least one non-transitory machine-readable medium including instructions for mapping and collecting data from a mesh network, which when executed by a processor of a gateway device connecting a plurality of devices to a network, cause the processor to:

determine a shortest path tree (SPT) map of the plurality of devices, the shortest path tree map defining the mesh network for the plurality of devices connected to the gateway;

sample data throughout be mesh network based on a compressive sensing (CS) sampling schedule; and

output the sampled data to a remote device via the network.

20. The at least one machine-readable medium of claim 19, wherein sample data throughout the mesh network, the instructions further cause the processor to receive an encoded reading from a parent node connected to the gateway in the mesh network.

21. The at least one machine-readable medium of claim 20, wherein the encoded reading includes a linearly combined reading from each child node connected within the SPT map to the parent node.

22. The at least one machine-readable medium of claim 19, wherein connections among the plurality of devices are unknown before determining the SPT map.

23. The at least one machine-readable medium of claim 19, wherein connections between the gateway and all of the plurality of devices are unknown before determining the SPT map.

24. The at least one machine-readable medium of claim 19, wherein to sample data, the instructions further cause the processor to increase a number of routes sampled in response to detecting an anomaly at a node within the SPT map.

25. The at least one machine-readable medium of claim 24, wherein the instructions further cause the processor to dynamically change signal recovery parameters based on the detected anomaly.