5G Core AFLSF for Adaptive FL Aggregation Under Stragglers
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Solution Overview
Problem
Current 5G communication systems lack support for flexible engagement models in federated learning (FL) operations, particularly in scenarios where user equipment (UEs) have varying computation and connectivity resources, leading to issues like stragglers and network unreliability.
Innovation Solution
Introduce an Application Federated Learning Support Function (AFLSF) within the 5G Core network to enable flexible FL operations by allowing UEs to initiate connections, support synchronous and asynchronous model aggregation modes, and provide configuration recommendations based on network analytics and UE information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If synchronous model aggregation is used in federated learning, then model convergence accuracy is improved, but system reliability deteriorates due to stragglers and network unreliability
Solution Approach 1:
The system dynamically switches between synchronous and asynchronous model aggregation modes based on network conditions and UE capabilities. The AFLSF entity receives configuration parameters indicating the aggregation mode and adjusts operations accordingly, allowing the system to be flexible rather than static in its approach to model aggregation.
Solution Approach 2:
The invention changes the operational parameters of federated learning by introducing configurable aggregation modes (synchronous/asynchronous) and adjusting timing parameters based on network analytics. This allows optimization of both accuracy and reliability by selecting appropriate parameter settings for different operational scenarios.
2Measurement precision
If strict timing requirements are imposed on FL operations, then model aggregation accuracy is improved, but adaptability deteriorates for UEs with varying computation and connectivity resources
Solution Approach 1:
The system dynamically adapts timing requirements based on individual UE capabilities and network conditions. UEs with better computation resources and connectivity can participate in synchronous aggregation, while UEs with limited resources can use asynchronous aggregation with relaxed timing, making the system adaptable to heterogeneous UE populations.
Solution Approach 2:
The federated learning operation is segmented into different aggregation modes (synchronous and asynchronous) that can be selectively applied to different UEs or different rounds of learning. This segmentation allows the system to maintain high accuracy requirements for capable UEs while providing relaxed timing for resource-constrained UEs.
3Productivity
If centralized FL control is implemented, then coordination efficiency is improved, but device complexity increases for UEs to manage connections and sessions
Solution Approach 1:
The AFLSF entity acts as an intermediary between the application function and UEs, managing the complexity of FL operation configuration, analytics collection, and coordination. This intermediary absorbs the complexity of centralized control, leaving UEs with simpler connection management requirements while maintaining efficient coordination through the mediator.
Data Source
AI summary
The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. A method for supporting federated learning (FL) by an application federated learning support function (AFLSF) in a wireless communication system is provided. The method comprises receiving, from an application function (AF), a message for requesting assistance for an FL operation: obtaining, from a network data analytics function (NWDAF), analytics to get assistance on determination of an FL configuration recommendation; obtaining information related to at least one user equipment (UE) from a session management function (SMF) and an access and mobility management function (AMF); deriving a FL configuration recommendation based on the analytics and the obtained information related to the at least one UE; transmitting, to the AF, a response message including at least one parameter related to the FL configuration recommendation.