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METIS: A Declarative Slice Orchestrator for Application-Centric 5G/6G Networks

Jul 2026 · arXiv.org · Vol abs/2607.29282 · 0 citations · 29 references
Computer Science

TL;DR

METIS is a declarative slice orchestrator that manages the Day-0/1/2 lifecycle of network slice instances through cascaded reconciliation loops, and derives 3GPP-aligned slice profiles via hierarchical aggregation following the 5G quality-of-service model.

Abstract

Network slicing is the cornerstone of application-aware 5G and 6G networks, yet dynamic lifecycle management of network slice instances with coordinated quality-of-service enforcement across the radio access network and core network remains unresolved. Existing orchestrators rely on network-centric data models, imperative workflows, and static slice templates, while O-RAN addresses radio-side slice control independently of 3GPP core-side control, leaving slice-level quality-of-service enforcement uncoordinated across domains. This paper introduces METIS, a declarative slice orchestrator that manages the Day-0/1/2 lifecycle of network slice instances through cascaded reconciliation loops. METIS defines an application-centric data model for service profiles, enabling customers to describe the semantics and quality-of-experience requirements of their applications. From these, METIS derives 3GPP-aligned slice profiles via hierarchical aggregation following the 5G quality-of-service model, eliminating static templates, and jointly coordinates O-RAN and 3GPP slicing for slice instantiation and enforcement. Our central finding is a structural asymmetry in end-to-end slice control: downlink traffic can be shaped at the core before reaching the radio access network, but uplink leaves the user equipment unregulated, so core-only slicing cannot reliably satisfy uplink service-level agreements - radio-side enforcement is necessary, not merely complementary. Evaluated on a 5G cloud-native testbed in a campus-event scenario, METIS completes slice creation, update, upgrade, and deletion within 22.4, 5.1, 52.2, and 32.1 seconds, respectively; sustains full service-level-agreement satisfaction under concurrent multi-slice overload; scales to 63 slice instances across nine zones consuming under 0.03 processor cores total; and recovers slices from injected failures across four levels in under 19 seconds.

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