IP Library Granted Patent US 11,558,253
Granted Patent B2
US 11,558,253 · App. 17/198,367 · Granted Jan 17, 2023

Data processing method and apparatus, and computing node for updating container images

Inventor: Xihan Peng (Hangzhou, CN)
Assignee: HUAWEI TECHNOLOGIES CO., LTD.
H04L41/0846H04L41/0826H04L41/0893H04L41/14H04L41/5003G06F8/65H04L41/20
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,558,253
App. No.
17/198,367
Granted
Jan 17, 2023
Kind
B2
Abstract

A data processing method and apparatus are disclosed. The data processing method includes: receiving, by a first edge computing node in an edge computing cluster, a container image update instruction; obtaining, by the first edge computing node, a to-be-updated container image; and sending, by the first edge computing node, the to-be-updated container image to another edge computing node in the edge computing cluster. The first edge computing node is an edge computing node in the edge computing cluster, the edge computing cluster includes at least two edge computing nodes, and the container image update instruction is used to instruct the at least two edge computing nodes in the edge computing cluster to update a container image. In this way, the time required for downloading the container image is reduced.

Claims (48)

1. A data processing method performed by a plurality of edge computing clusters including a first edge computing cluster and a second edge computing cluster, the first edge computing cluster and the second edge computing cluster each including a plurality of edge computing nodes connected by a local area network, comprising:

receiving, by a first edge computing node and a second edge computing node, a container image update instruction from a remote data center via a public network, wherein the first edge computing node is one of the plurality of edge computing nodes in the first edge computing cluster, the second edge computing node is one of the plurality of edge computing nodes in the second edge computing cluster, the container image update instruction instructs each of the plurality of edge computing nodes in the first edge computing cluster and each of the plurality of edge computing nodes in the second edge computing cluster to update a container image, and the container image is software deployed on each of the plurality of edge computing nodes in the first edge computing cluster and each of the plurality of edge computing nodes in the second edge computing cluster for processing data obtained by the respective edge computing node;

in response to the container image update instruction received from the remote data center, selecting, by each of the first edge computing node and the second edge computing node, an edge computing node from the plurality of edge computing nodes in the respective edge computing cluster as an agent node for the respective edge computing cluster;

obtaining, by the agent node for the first edge computing cluster, a to-be-updated container image from the remote data center via the public network; and

sending, by the agent node for the first edge computing cluster, the obtained to-be-updated container image to another edge computing node in the first edge computing cluster via the local area network,

wherein the agent node for the first edge computing cluster can be any edge computing node within the first edge computing cluster, and said another edge computing node can be any edge computing node within the first edge computing cluster that is not the agent node for the first edge computing cluster.

2. The method of claim 1 , wherein selecting, by the first edge computing node, the edge computing node from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster comprises:

obtaining, by the first edge computing node, a performance parameter of each edge computing node in the first edge computing cluster, wherein the performance parameter indicates resource usage of the respective edge computing node;

determining, by the first edge computing node, a load of each edge computing node in the first edge computing cluster based on the performance parameter of the respective edge computing node; and

sorting, by the first edge computing node, the plurality of edge computing nodes in the first edge computing cluster based on the loads of these edge computing nodes, and selecting one edge computing node with the lowest load from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster.

3. The method of claim 2 , wherein the first edge computing node is the edge computing node with the lowest load among the plurality of edge computing nodes in the first edge computing cluster and is selected as the agent node for the first edge computing cluster.

4. The method of claim 1 , wherein selecting, by the first edge computing node, the edge computing node from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster comprises:

randomly selecting, by the first edge computing node, the edge computing node from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster.

5. The method of claim 1 , wherein selecting, by the first edge computing node, the edge computing node from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster comprises:

selecting, by the first edge computing node, the edge computing node from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster based on an identifier of the edge computing node.

6. The method of claim 1 , wherein the edge computing node is not the first edge computing node and obtaining the to-be-updated container image comprises:

obtaining, by the first edge computing node, the to-be-updated container image from the agent node for the first edge computing cluster, the to-be-updated container image being obtained by the agent node from the remote data center.

7. The data processing method according to claim 1 , wherein the plurality of edge computing nodes are connected to one or more sensors, and each of the plurality of computing nodes is configured to process data collected by the one or more sensors to generate one or more processing results and send the one or more processing results to the remote data center via the public network.

8. The data processing method according to claim 1 , wherein the container image update instruction is simultaneously sent from the remote data center to each of the plurality of edge computing clusters.

9. The data processing method according to claim 1 , wherein the container image update instruction is sent from the remote data center to the plurality of edge computing clusters in batches at different times respectively.

10. The data processing method according to claim 1 , wherein the container image update instruction is sent from the remote data center to the plurality of edge computing clusters respectively in a sequence determined based on loads of the plurality of edge computing clusters.

11. A computing node, comprising at least one processor and a memory, wherein the memory is configured to store computer readable instructions that, when executed by the at least one processor, cause the computing node to perform operations comprising:

receiving a container image update instruction from a remote data center via a public network, wherein the container image update instruction is sent from a remote data center to a plurality of edge computing clusters including a first edge computing cluster and a second edge computing cluster, the first edge computing cluster and the second edge computing cluster each includes a plurality of edge computing nodes connected by a local area network, the computing node is one of the plurality of edge computing nodes in the first edge computing cluster, the container image update instruction instructs each of the plurality of edge computing nodes in the first edge computing cluster and each of the plurality of edge computing nodes in the second edge computing cluster to update a container image, and the container image is software deployed on each of the plurality of edge computing nodes in the first edge computing cluster and each of the plurality of edge computing nodes in the second edge computing cluster for processing data obtained by the respective edge computing node; and

in response to the container image update instruction received from the remote data center, selecting an edge computing node from the plurality of edge computing nodes in the first edge computing cluster as an agent node for the first edge computing cluster, wherein another agent node is selected by one of the plurality of edge computing nodes in the second edge computing cluster for the second edge computing cluster,

wherein the agent node for the first edge computing cluster is configured to obtain a to-be-updated container image from the remote data center via the public network, and send the obtained to-be-updated container image to another edge computing node in the first edge computing cluster via the local area network,

wherein the agent node for the first edge computing cluster can be any edge computing node within the first edge computing cluster, and said another edge computing node can be any edge computing node within the first edge computing cluster that is not the agent node for the first edge computing cluster.

12. The computing node of claim 11 , wherein, when executed by the at least one processor, the computer readable instructions further cause the computing node to perform operations comprising:

obtaining a performance parameter of each edge computing node in the first edge computing cluster, wherein the performance parameter indicates resource usage of the respective edge computing node;

determining a load of each edge computing node in the first edge computing cluster based on the performance parameter of the respective edge computing node; and

sorting the plurality of edge computing nodes in the first edge computing cluster based on the loads of these edge computing nodes, and selecting one edge computing node with the lowest load from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster.

13. The computing node of claim 12 , wherein the computing node is the edge computing node with the lowest load among the plurality of edge computing nodes in the first edge computing cluster and is selected as the agent node for the first edge computing cluster.

14. The computing node of claim 11 , wherein the edge computing node is randomly selected from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster.

15. The computing node of claim 11 , wherein the agent node is selected from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster based on an identifier of the agent node.

16. The computing node of claim 11 , wherein the agent node is not the computing node, and the to-be-updated container image is obtained by the computing node from the agent node, after the agent node obtains the to-be-updated container image from the remote data center via the public network.

17. A non-transitory computer-readable storage medium comprising instructions that, when executed by a computing node, cause the computing node to perform operations comprising:

receiving a container image update instruction from a remote data center via a public network, wherein the container image update instruction is sent from a remote data center to a plurality of edge computing clusters including a first edge computing cluster and a second edge computing cluster, the first edge computing cluster and the second edge computing cluster each includes plurality of edge computing nodes connected by a local area network, the computing node is one of the plurality of edge computing nodes in the first edge computing cluster, the container image update instruction instructs each of the plurality of edge computing nodes in the first edge computing cluster and each of the plurality of edge computing nodes in the second edge computing cluster to update a container image, and the container image is software deployed on each of the plurality of edge computing nodes in the first edge computing cluster and each of the plurality of edge computing nodes in the second edge computing cluster for processing data obtained by the respective edge computing node; and

in response to the container image update instruction received from the remote data center, selecting an edge computing node from the plurality of edge computing nodes in the first edge computing cluster as an agent node for the first edge computing cluster, wherein another agent node is selected by one of the plurality of edge computing nodes in the second edge computing cluster for the second edge computing cluster,

wherein the agent node for the first edge computing cluster is configured to obtain a to-be-updated container image from the remote data center via the public network, and send the obtained to-be-updated container image to another edge computing node in the first edge computing cluster via the local area network,

wherein the agent node for the first edge computing cluster can be any edge computing node within the first edge computing cluster, and said another edge computing node can be any edge computing node within the first edge computing cluster that is not the agent node for the first edge computing cluster.

18. The non-transitory computer-readable storage medium of claim 17 , wherein the instructions, when executed by the computing node, further cause the computing node to perform operations comprising:

obtaining a performance parameter of each edge computing node in the first edge computing cluster, wherein the performance parameter indicates resource usage of the respective edge computing node;

determining a load of each edge computing node in the first edge computing cluster based on the performance parameter of the respective edge computing node; and

sorting the plurality of edge computing nodes in the first edge computing cluster based on the loads of these edge computing nodes in the first edge computing cluster, and selecting one edge computing node with the lowest load from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster.

19. The non-transitory computer-readable storage medium of claim 18 , wherein

the computing node is the edge computing node with the lowest load among the plurality of edge computing nodes in the first edge computing cluster and is selected as the agent node for the first edge computing cluster.

20. The non-transitory computer-readable storage medium of claim 17 , wherein the agent node for the first edge computing cluster is randomly selected from the plurality of edge computing nodes in the first edge computing cluster as the agent node.

21. The non-transitory computer-readable storage medium of claim 17 , wherein

the agent node is selected from the plurality of edge computing nodes in the first edge computing cluster as the agent node for the first edge computing cluster based on an identifier of the agent node.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 1, 2021
From: PENG, XIHAN
To: HUAWEI TECHNOLOGIES CO., LTD.
Reel/Frame 055792/0614 →
Priority Claims (1)
CN 201811061918.1 · Sep 12, 2018 · national
Continuity (2)
Continuation PCTCN2019094143 · Jul 1, 2019
Related Publication 20210203554A1 · Jul 1, 2021
Cited By (1)
US 12,229,414