Dynamic SLA-aware Network Slice Monitoring

TL;DR

This paper introduces SliceScope, a novel framework for SLA-aware network slice monitoring that dynamically allocates monitoring resources and uses change-triggered INT to improve accuracy and efficiency in real-time performance tracking.

Contribution

It formalizes network slice monitoring as a control problem, defining minimal data plane requirements and implementing a dynamic, SLA-aware monitoring system called SliceScope.

Findings

SliceScope tracks critical slices up to 4x more accurately than static methods.

Change-triggered INT outperforms other primitives in providing end-to-end visibility.

The framework effectively balances monitoring accuracy and overhead in programmable networks.

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.