Arbeitslasteinsatz in einer Inhaltsgeführten und Dienstebenenvereinbarungsbewussten Edge-Cloud-Architektur

Details

Veröffentlichungs-Nr.

EP4715594

Anmeldetag

15. September 2025

Veröffentlichung

25. März 2026

Rechtsraum

EP

IPC

G06F9/50

Abstract

Proliferation of edge devices has significantly advanced technologies in sectors such as autonomous driving and surveillance. However, deploying machine learning models on these resource-constrained devices presents challenges including scalability and managing unpredictable workloads thereby affecting real-time performance in edge-only environments. The present disclosure discloses a method and system for workload deployment in a content guided and service level agreement (SLA) aware edge-cloud architecture. In the present disclosure, a camera feed content-guided load balancing technique is provided that dynamically manages workloads between edge and cloud. Features are extracted from an incoming camera feed to perform load-balancing process efficiently. The load balancer determines a maximum number of concurrent feeds for processing at the edge, with the remaining feeds handled by the cloud based on content of the incoming camera feed. Additionally, a cost model to estimate expenses of deploying the edge-cloud architecture in real-world scenarios with dynamic workloads is provided.

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien