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Orchestrator design, service programming and machine learning models ((D4.1)

Khalili, Hazmeh; Papageorgiou; Siddiqui, Shuaib; Barrera, Julio; Huici, Felipe; Yasukata, Kenichi; Ciulli, Nicola; Cruschelli, Paolo; Kraja, Elian; Francesconi, Elio; Preto, Ricardo; Albanese, Antonino; Costa, Viscardo; Colman, Carlos; Baldoni, Gabrielle; Sechkova, Teodora; Paolino, Michele

This document describes the components of the 5GCity architecture related to orchestration, service programming, and machine learning as main outcomes of tasks T4.1, T4.2, and T4.3. The overall 5GCity architecture is described in Deliverable D2.2 [1] and based on pilot requirements introduced in Deliverable D2.1 [2]. Our orchestration, service programming, and machine learning components are vital for addressing challenges of state-of-the-art 5G orchestrators and platforms, such as multi-tenancy support and efficient configuration and resource placement.

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