학술논문

Mobility-Aware Routing and Caching: A Federated Learning Assisted Approach
Document Type
Conference
Source
ICC 2021 - IEEE International Conference on Communications Communications , ICC 2021 - IEEE International Conference on. :1-6 Jun, 2021
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Greedy algorithms
Base stations
Numerical analysis
Conferences
Routing
Minimization
Collaborative work
caching
dense small-cell networks
one-stop-shop
federated learning
Language
ISSN
1938-1883
Abstract
We develop mobility-aware routing and caching strategies to solve the network cost minimization problem for dense small-cell networks. The challenge mainly stems from the insufficient backhaul capacity of small-cell networks and the limited storing capacity of small-cell base stations (SBSs). The optimization problem is NP-hard since both the mobility patterns of the mobilized users (MUs), as well as the MUs’ preference for contents, are unknown. To tackle this problem, we start by dividing the entire geographical area into small sections, each of which containing one SBS and several MUs. Based on the concept of one-stop-shop (OSS), we propose a federated routing and popularity learning (FRPL) approach in which the SBSs cooperatively learn the routing and preference of their respective MUs, and make caching decision. Notably, FRPL enables the completion of the multi-tasks in one shot, thereby reducing the average processing time per global aggregation. 1 Theoretical and numerical analyses show the effectiveness of our proposed approach.