Dynamic SLA-aware Network Slice Monitoring

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 4× more accurately compared to static baselines, while showing that change-triggered INT outperforms alternative primitives for realizing the telemetry primitive contract.

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Publication Details

Journal
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Published
2026-03-26
DOI
https://doi.org/10.1145/3788090
Primary Topic
Software-Defined Networks and 5G
Type
article
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article

Dynamic SLA-aware Network Slice Monitoring

Nashid Shahriar, Mina Tahmasbi Arashloo, Niloy Saha, R. Boutaba
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Software-Defined Networks and 5G
article

Dynamic SLA-aware Network Slice Monitoring

Nashid Shahriar, Mina Tahmasbi Arashloo, Niloy Saha, R. Boutaba
article en

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 4× more accurately compared to static baselines, while showing that change-triggered INT outperforms alternative primitives for realizing the telemetry primitive contract.

Proceedings of the ACM on Measurement and Analysis of Computing SystemsVol. 10(1)
University of Waterloo (CA), University of Regina (CA)
Partnerships for the goals
Openalex Percentile: Top 7%
Software-Defined Networks and 5G
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Dynamic SLA-aware Network Slice Monitoring — Nashid Shahriar, Mina Tahmasbi Arashloo, et al. · Proceedings of the ACM on Measurement and Analysis of Computing Systems (2026) | TGRS Research Map | TGRS