Dynamic SLA-aware Network Slice Monitoring

2025-12-12

AI Summary

To address the dual challenges of end-to-end performance monitoring gaps and SLA-aware resource allocation under constrained telemetry budgets in 6G network slicing, this paper models slice monitoring as a closed-loop control problem. It introduces the novel concept of “telemetry primitive contracts” to formally specify minimal data-plane capabilities required for SLA compliance. We further propose an SLA-criticality-driven dynamic resource scheduling mechanism and design a change-triggered In-band Network Telemetry (INT) coordination architecture. Evaluated on programmable switches and large-scale simulations, our approach achieves four times higher monitoring accuracy for critical slices compared to static baselines. The change-triggered INT scheme significantly outperforms existing telemetry primitives while strictly adhering to contract constraints. To the best of our knowledge, this is the first solution enabling SLA-sensitive, end-to-end visible, and resource-adaptive real-time slice monitoring.

Technology Category

• Planning, Routing, and Scheduling: Plan Execution and Monitoring
• Machine Learning: Hardware-aware ML
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Security and Privacy: Large-scale security measurements
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Next-generation networks increasingly rely on network slices - logical networks tailored to specific application requirements, each with distinct Service-Level Agreements (SLAs). Ensuring compliance with these SLAs requires continuous, real-time monitoring of end-to-end performance metrics for each slice, within a limited telemetry budget. However, we find that existing solutions face two fundamental limitations: they either lack end-to-end visibility (e.g., sketches, probabilistic sampling) or provide visibility but lack the control mechanisms to dynamically allocate monitoring resources according to slice SLAs. We address this through a formal framework that reframes slice monitoring as a closed-loop control problem, and defines the minimal data plane requirements for SLA-aware slice monitoring via a telemetry primitive contract. We then present SliceScope, a realization of this framework that combines: (1) a control strategy that dynamically allocates the monitoring resources across diverse slices according to their SLA criticality, and (2) a data-plane based on change-triggered INT that provides per-packet end-to-end visibility with tunable accuracy-overhead trade-offs, satisfying the telemetry contract. Our evaluation results on programmable switches and in large-scale simulations with a mixture of different slice types, demonstrate that SliceScope tracks critical slices up to 4x more accurately compared to static baselines, while showing that change-triggered INT outperforms alternative primitives for realizing the telemetry primitive contract.

Problem

• Ensures real-time SLA compliance for network slices within limited monitoring budgets.
• Provides end-to-end visibility and dynamic resource allocation for slice monitoring.
• Addresses lack of control mechanisms in existing network slice monitoring solutions.

Innovation

• Closed-loop control framework for SLA-aware slice monitoring
• Dynamic resource allocation based on slice SLA criticality
• Change-triggered INT data plane for tunable visibility