Design of 5G Architecture Enhancements for Supporting Edge Split Computing Service Pipeline

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초록

Split computing is one of the key service paradigms that future 6G networks are expected to support. In this paradigm, emerging 6G applications, such as Artificial Intelligence (AI) and Machine Learning (ML) inference, or Extended Reality (XR), can be deployed as sequential or parallel sub-service pipelines distributed across multiple Multi-access Edge Computing (MEC) sites. To enable the deployment of split computing, recent studies in 5G and 6G have proposed various solutions that address critical challenges, including optimal task partitioning and the placement or resource allocation of sub-services across MEC nodes. However, the current 5G network architecture requires significant enhancements to implement these split computing orchestration solutions. This article proposes new components and procedures to the 5G Control Plane and User Plane by integrating the Computing-Aware Traffic Steering (CATS) framework and the Segment Routing IPv6 (SRv6)-based Mobile User Plane (MUP). A Proof-of-Concept (PoC) implementation demonstrates that the proposed architecture enhances the capability of existing 5G systems to support split computing pipelines by significantly reducing control plane-user plane configuration overhead as well as underlay network traffic steering path setup and modification latency.

키워드

5G mobile communicationPipelinesComputational modeling6G mobile communicationArtificial intelligenceResource managementComputer architectureAdaptation modelsRouting3GPP5G6Gsplit computingedge computingtraffic steering
제목
Design of 5G Architecture Enhancements for Supporting Edge Split Computing Service Pipeline
저자
Tran, Minh-NgocTrung, Kiem NguyenKim, Younghan
DOI
10.1109/ACCESS.2025.3630182
발행일
2025-11
유형
Article
저널명
IEEE Access
13
페이지
191515 ~ 191530