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[2602.15281] High-Fidelity Network Management for Federated AI-as-a-Service: Cross-Domain Orchestration
Summary
This paper presents a framework for high-fidelity network management in Federated AI-as-a-Service, focusing on cross-domain orchestration to enhance service reliability and performance.
Why It Matters
As AI-as-a-Service becomes increasingly integral to communication service providers, understanding the orchestration of network and compute resources is crucial for ensuring reliable AI service delivery. This research addresses key challenges in managing network impairments and optimizing performance across multiple domains, which is essential for the future of AI service deployment.
Key Takeaways
- Introduces an assurance-oriented management plane for AIaaS using Tail-Risk Envelopes.
- Addresses operational challenges in delivering reliable AI services across federated domains.
- Demonstrates improved performance compliance through Monte-Carlo simulations and tenant-level reservations.
- Provides a framework for accountability in network performance via runtime telemetry.
- Highlights the importance of managing network and inference impairments for AI service delivery.
Computer Science > Networking and Internet Architecture arXiv:2602.15281 (cs) [Submitted on 17 Feb 2026] Title:High-Fidelity Network Management for Federated AI-as-a-Service: Cross-Domain Orchestration Authors:Merve Saimler, Mohaned Chraiti, Ozgur Ercetin View a PDF of the paper titled High-Fidelity Network Management for Federated AI-as-a-Service: Cross-Domain Orchestration, by Merve Saimler and 2 other authors View PDF HTML (experimental) Abstract:To support the emergence of AI-as-a-Service (AIaaS), communication service providers (CSPs) are on the verge of a radical transformation-from pure connectivity providers to AIaaS a managed network service (control-and-orchestration plane that exposes AI models). In this model, the CSP is responsible not only for transport/communications, but also for intent-to-model resolution and joint network-compute orchestration, i.e., reliable and timely end-to-end delivery. The resulting end-to-end AIaaS service thus becomes governed by communications impairments (delay, loss) and inference impairments (latency, error). A central open problem is an operational AIaaS control-and-orchestration framework that enforces high fidelity, particularly under multi-domain federation. This paper introduces an assurance-oriented AIaaS management plane based on Tail-Risk Envelopes (TREs): signed, composable per-domain descriptors that combine deterministic guardrails with stochastic rate-latency-impairment models. Using stochastic network calculus, we ...
