Edge Node Agent for Container Image Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In edge computing networks, the process of downloading container images is prolonged due to limited network bandwidth between edge computing nodes and the data center, affecting the efficiency of upgrades across multiple nodes.
Innovation Solution
Implementing a method where one edge computing node acts as an agent node to download the container image from the data center and then distribute it to other nodes within the same local area network, optimizing bandwidth usage and reducing the time required for each node to obtain the updated image by selecting the node with the lowest load or using a randomly selected node.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple edge computing nodes download container images directly from the data center simultaneously, then each node can obtain the update independently, but the limited network bandwidth causes prolonged download time for all nodes
Solution Approach 1:
The patent introduces an agent node as an intermediary between the data center and other edge computing nodes. The agent node downloads the container image from the data center and then distributes it to other nodes within the edge computing cluster. This mediator approach allows most nodes to obtain updates quickly via the high-bandwidth local network while maintaining the ability for any node to independently update by contacting the agent node.
Solution Approach 2:
The patent segments the update distribution function by designating one specific node as the agent node responsible for external communication with the data center, while other nodes focus on local updates. This segmentation separates the bandwidth-intensive download operation from the distribution operation, allowing parallel execution and reducing overall update time.
2Reliability
If all edge computing nodes download container images from the data center at the same time, then each node ensures fresh updates, but the network bandwidth between the data center and edge cluster becomes a bottleneck
Solution Approach 1:
The agent node performs the download action in advance on behalf of the entire cluster. By downloading the container image once and storing it locally, the agent node prepares the update resource before other nodes need it. This preliminary action eliminates the need for repeated downloads from the data center, ensuring all nodes receive fresh updates while avoiding bandwidth bottlenecks.
Solution Approach 2:
The patent merges the update distribution process by having the agent node serve multiple nodes simultaneously. Instead of each node independently downloading from the data center, the agent node consolidates the download operation and then distributes the single downloaded copy to all requesting nodes, combining multiple update operations into one efficient process.
3Speed
If the system selects an agent node based on lowest load, then the agent node can perform downloads faster, but requires additional mechanisms to monitor and compare node performance parameters
Solution Approach 1:
The system implements feedback mechanisms where edge computing nodes report their performance parameters (CPU usage, memory availability, network status) to the coordinating node. Based on this feedback, the system dynamically selects the agent node with the most favorable conditions. This feedback loop ensures optimal download speed while maintaining manageable complexity through standardized monitoring and selection criteria.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
This application discloses a data processing method and apparatus. The method includes: receiving, by a first edge computing node, 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 any 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, a time required for downloading the container image is reduced.