Edge Node Data Pre-loading for 5G Mobile Latency
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Solution Overview
Problem
In 5G networks, traditional content delivery systems face challenges in providing low latency and adapting to mobile users' geographical changes, leading to increased transmission distances and delays, especially when users are in fast-moving vehicles, as they often rely on edge nodes that are not optimally chosen based on the user's location.
Innovation Solution
A method where a management node obtains status data from multiple work nodes to determine their utilization rates and weights, allowing for the pre-loading of content data onto edge nodes along a user's predicted path, ensuring optimal data delivery and minimizing latency by selecting the best-performing edge nodes for data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If content data is delivered from remote servers through traditional content delivery systems, then data transmission can be achieved, but communication delays increase and transmission distances lengthen
Solution Approach 1:
The system performs preliminary actions by predicting the user terminal's movement trajectory and pre-loading content data to edge nodes along the predicted path before the user actually reaches those locations. This advance preparation eliminates waiting time and reduces communication delays when the user requests data.
Solution Approach 2:
Edge nodes serve as intermediary elements between remote servers and user terminals. Instead of direct long-distance transmission, data is first transmitted to intermediate edge nodes positioned along the user's movement path, which then provide data to the user terminal with much shorter transmission distances and lower latency.
2Adaptability or versatility
If edge nodes are selected based on traditional content delivery systems, then data delivery can be achieved, but adaptability to user movement and geographical changes deteriorates
Solution Approach 1:
The system dynamically adapts edge node selection based on real-time user terminal location and predicted movement trajectory. Instead of static edge node assignment, the system continuously updates which edge nodes should receive pre-loaded data based on the user's current position and intended direction of travel, ensuring optimal adaptability to geographical changes.
Solution Approach 2:
The system uses feedback mechanisms by monitoring user terminal movement patterns and trajectory changes to continuously optimize edge node selection. The prediction of user movement provides feedback that guides which edge nodes should be prepared with content data, improving both adaptability to movement and service continuity.
3Speed
If computing workload is assigned to edge nodes closest to user terminal, then response time can be reduced, but network IO and distributed system delays may offset the advantage
Solution Approach 1:
By pre-loading content data to edge nodes along the predicted user trajectory, the system performs the data transmission action in advance during periods of lower network load. This shifts the timing of network IO operations away from peak demand periods, reducing the impact of network IO delays and distributed system complexity on actual user response time.
Data Source
AI summary
Embodiments of the disclosure provide a method, electronic device and computer program product for data transmission. The method may include enabling a management node to obtain status data of a plurality of work nodes from the plurality of work nodes managed by the management node in response to determining that a user terminal is to move from a first position to a second position different from the first position. The status data are at least associated with utilization rates of the plurality of work nodes. The method may further include determining a plurality of weights of the plurality of work nodes at least based on the status data of the plurality of work nodes. Moreover, the method may include loading content data requested by the user terminal to at least one work node in the plurality of work nodes based on the plurality of weights.