Citation :

Venkata Rama Uday Kiran Bokam, Sachin Vasanthkumar, Kameswaran Arunachalam, "SCONE-AEGIS: Uncertainty-Aware AI-Driven Edge Compute Steering for Mobile Edge Applications," International Journal of Computer Trends and Technology (IJCTT), vol. 74, no. 4, pp. 52-72, 2026. Crossref, https://doi.org/10.14445/22312803/IJCTT-V74I4P105

Abstract

Mobile Edge Computing (MEC) has become increasingly critical for latency-sensitive applications, including Augmented/Extended Reality (AR/XR), Cloud Gaming, Real-Time Video Analytics, and Interactive Enterprise Services. Existing edge steering mechanisms remain largely reactive by relying on static policies, nearest-edge selection, or compute-only information that usually fail under user mobility, fluctuating radio conditions, dynamic user-plane paths, and edge resource contention rather than being more proactive. This paper presents SCONE-AEGIS framework that extends the Standard Communication with Network Elements (SCONE) paradigm beyond throughput advisories to support joint network-compute steering of MEC applications. SCONE-AEGIS introduces an Edge Steering Advice (ESA) that communicates recommendations that can be consumed by the applications, which have been derived from a combination of RAN, UPF, and MEC telemetry. The framework is a combination of a two-stage AI/ML engine, the first being a Spatio-Temporal Graph Predictor that is uncertaintyaware and models the evolving relationships among radio access network nodes, user-plane functions, edge sites, and mobile users, and the second stage is a Safe Contextual Bandit Steering Policy (SCBSP) that selects execution sites subject to SLA constraints, migration hysteresis, and prediction confidence. The proposed framework provides a standards-compatible, privacypreserving path for exposing joint network-compute intelligence to applications without breaking transport encryption.

Keywords

SCONE, MEC, Edge Computing, Service Steering, Mobile Networks, AI/Ml, Graph Neural Networks, QoE, Mobility- Aware Orchestration, 5G.

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