Federated Trainer Pairing Using Shared Counters for Data Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In large-scale vertical federated learning scenarios, manual trainer pairing is inefficient, time-consuming, and prone to errors such as repeated or missing pairings, leading to misaligned training data and abnormal training indicators, and there is a need for efficient collaborative control of trainers in case of unexpected exits.
Innovation Solution
A method and apparatus for trainer pairing in federated learning that utilizes a counter component to automatically assign unique numbers to trainers based on a shared rule, enabling automatic pairing and collaborative control through a distributed collaborative component, ensuring consistent and efficient trainer pairing and handling unexpected trainer exits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual pairing manner is adopted, then trainer pairing can be controlled, but pairing efficiency is low and time consumption increases
Solution Approach 1:
The system enables self-service pairing where trainers automatically obtain their own trainer numbers from the counter component and query for paired trainers without manual intervention. The first trainer obtains its trainer number, queries the counter component for the second participant's trainer numbers, and automatically identifies the paired trainer based on matching numbers, eliminating the need for manual pairing table creation.
Solution Approach 2:
The patent replaces the manual mechanical pairing process with an automated system using a counter component that distributes unique trainer numbers and enables automatic pairing through number matching. This substitution of manual operations with automated number-based identification resolves the efficiency and time consumption issues.
2Reliability
If manual pairing manner is adopted, then pairing can be controlled, but errors such as repeated pairing or missing pairing occur
Solution Approach 1:
The system implements feedback mechanisms where trainers query the counter component to verify the existence of paired trainers and check for number conflicts. The first trainer queries trainer numbers of the second participant and checks whether the target number exists, providing feedback to ensure correct pairing and prevent repeated or missing pairings.
Solution Approach 2:
The automated number-based pairing system replaces manual pairing tables with a counter component that automatically assigns and tracks trainer numbers, eliminating human error in pairing while maintaining operational simplicity through standardized number matching procedures.
3Manufacturing precision
If manual pairing manner is adopted, then pairing can be controlled, but training data alignment fails
Solution Approach 1:
The patent replaces manual pairing with an automated counter component system that ensures precise data alignment through unique trainer number assignment and automatic pairing. This mechanism guarantees that trainers receive correct paired information, preventing data misalignment while maintaining efficient training progression.
Data Source
AI summary
The present disclosure relates to a trainer pairing method in federated learning model training, an electronic device, and storage medium. The method includes: obtaining, after the first trainer is started, a trainer number of the first trainer from a counter component; querying trainer numbers of a second participant in the counter component, and taking a second trainer corresponding to a target number as a pairing trainer of the first trainer when the target number being the same as the trainer number of the first trainer exists in the trainer numbers of the second participant; wherein the first trainer and the second trainer are configured to perform model training collaboratively in a federated learning process, and trainers started by the first participant and the second participant are numbered according to a same rule.