1. Casablanca Platform Enhancements to Support 5G Use Case (Network Deployment, Slicing, Network Optimization and Automation Framework)
5G Use Case Team

2. Contributors:
Supporting Companies

3. High Level Objectives for Casablanca:
Deployment of the hybrid 5G Radio Network (PNFs & VNFs)
Complete PNF Support
Platform Enhancements to Deploy Edge Virtual Radio Network Functions (e.g. CU)
Creation & Management of Radio Network Slice Subnet within the deployed network
Lifecycle management of Radio Network Slice Subnet Instances
Optimization of the deployed 5G network and the slices
Near-real Time Data Collection (e.g. streaming)
Edge Analytics to Support 5G Network Optimization
OOF enhancements for optimal placement of edge resources

4. A: 5G Radio Network – Architecture & Casablanca Focus
ONAP
Management - Design
ONAP
Management - Runtime 5G
Application
Ecosystem
RAN Network Elements
Core Network Elements
Macro Radio
& Small Cell
Antennas
CU-CP RU DU
CU-UP
Centralized
Cloud
Internet
UE/CPE
Back Haul
External Content
Front Haul
Front Haul II
Edge
Cloud
RU – Remote Radio Unit
DU – Distributed Unit
CU-UP – Centralized Unit - User Plane
CU-CP – Centralized Control Plane

5. A: 5G Radio Network Deployment Requirements
Description
Disaggregated 5G RAN may include PNFs and VNFs, in which case cloud infrastructure deployment at the edge is required. Beijing implemented the first phase of PNF discovery and instantiation. Our goal for Casablanca is expand on that work, include VNF deployment at the edge, and fully integrated lifecycle management. Key enhancements needed are:
Support full Application level Configuration (+Ansible), allow various mobile network elements to be controlled from same controller persona created from CC-SDK
Add Lifecycle management functions to controller persona
Support an integrated configuration design tool in SDC that can be used with any controller persona (next gen CDT)
Add support for PNF Software Management and Change management
Edge Cloud Support
Add needed support for deploying Mobility Virtual Network Elements (e.g. CU) at the Edge locations
Further automation of PnP Discovery for PNF
Rationale
Support for deploying and managing 5G mobility network is critically important for most ONAP members.
Impacted ONAP components
SDC, SO, CC-SDK (SDN-C, APP-C), AAI, DCAE, Multi-Cloud, OOF, (V/P)NF-SDK
Participating Companies
AT&T Amdocs China Mobile Ciena Cisco Ericsson Huawei Intel Nokia VMWare Others
For details regarding the requirements, please see

6. B: Casablanca Scope – Radio Network Slice Management
ONAP
Management - Design
ONAP
Management - Runtime
Mobile Slice Services (e.g. eMBB, Massive IoT, Mission-critical IoT)
Network Slice Instances (NSIs)
Radio Network Slice Subnet Instances (NSSIs)
Transport Network Slice Subnet Instances (NSSIs)
Core Network Slice Subnet Instances (NSSIs) 5G
Application
Ecosystem
RAN Abstraction Model
Transport Abstraction Model
Core Abstraction Model
Radio
Antennas
Core Network Elements
CU-CP
CU-UP
Centralized
Cloud
Internet RU DU
Back Haul
Front Haul
Front Haul II
External Content
Edge
Cloud
UE/CPE
RU – Remote Radio Unit DU – Distributed Unit (5G Base Unit)
CU-UP – Centralized Unit, User Plane CU-CP – Centralized Unit, Control Plane

7. B: Radio Network Slice Management – ONAP Requirements
Description
Many providers are interested in using ONAP for slice management and extending the cloud notion of sharing network/compute/storage to sharing network functions and network slice subnet instances . 3GPP standards are still evolving and early versions are not expected to be available before June However, we would like to demonstrate these concepts in ONAP initially using a simple slice definition, creation, and management for 5G Radio Network. Radio Access Network slice subnet instances supported and demonstrated in Casablanca will be limited to simple examples such as eMBB (enhance Mobile Broad Band). Key enhancements needed are:
Enhance SDC to model & define network slice subnets for Radio network
Enhance SO Instantiate and lifecycle manage network slice subnet instances
Enhance A&AI to inventory and store state of slice segments
Enhance Multi-Cloud and A&AI to support Guarantee (hard isolation), Burstable (soft isolation) and Best Effort (no isolation) QoS classes for Edge Clouds
Integrated design (e.g. configuration and service designs)
Support Complex Service Modeling (e.g. service composition, nested allotted resources)
Define and instantiate monitoring and management of network slice subnet instances, network slice instances
Rationale
Typical carrier deployments will be complex enough to need support for nested / complex services, correlation across multiple elements - hence, these are critical functional requirements for a carrier-grade ONAP
Impacted ONAP components
SDC, SO, CC-SDK (SDN-C, APP-C), AAI, Multi-Cloud, DCAE
Participating Companies
AT&T Amdocs China Mobile Ciena Cisco Ericsson Huawei Intel Nokia

8. Impacted ONAP components Participating Companies
C: Near-Real Time Edge Analytics & Network Optimization ONAP Requirements
Description
Edge cloud infrastructure (ECI) analytics is required for near-real-time correlation between various Events (e.g. Number of VM Power On/Off); Alerts (e.g. Cloud region CPU usage exceeds threshold) and Faults (e.g. loss of redundancy from a Host NIC perspective). Edge cloud near-real-time streaming infrastructure resource (CPU, Memory, Network etc.) utilization metrics are needed by OOF for inter-cloud resource optimization
Key Enhancements needed
Enhance ONAP SDC to support new ECI Models
Enhance ONAP Policy to support new ECI Policies
Enhance ONAP Policy to synchronize ECI Policies with the ECI Analytics through ONAP Multi-Cloud
Enhance ONAP Multi-Cloud to translate from vendor-specific to vendor-agnostic ECI Policies
Enhance ONAP Multi-Cloud to translate from vendor-specific to vendor-agnostic Resource Utilization Metrics & Analytics and asynchronously communicate these over DMaaP
Rationale
Near-real time decision making is critical for proactive self-healing and inter-cloud resource optimization
Important to minimize effects of WAN latency and bandwidth for near-real time decision making -- ONAP Components are centralized whereas Edge Clouds are Distributed
Impacted ONAP components
SDC (including Policy Design), Multi-cloud, Policy, OOF
Participating Companies
AT&T Amdocs China Mobile Ciena Cisco Ericsson Huawei Intel Nokia VMware

9. C: ONAP Optimization Framework Enhancements
Description
Many services in ONAP require optimization functionality during the lifecycle of the service components.
Service design, deployment, management, scheduling, and dynamic reconfiguration
The ONAP Optimization Framework provides declarative, model- and policy- driven system to support above needs. We would like to demonstrate OOF functionality using applications such as SON (PCI assignments, balancing network load), and dynamic workload aware placement and migration of edge services for 5G.
Key enhancements needed are:
Enhance A&AI to inventory and store 5G related data
Enhance Multi-cloud to provide streaming updates (near-real time and/or feed of statistical aggregates)
Enhance OOF to provide near-real time solutions and evaluate it for large clouds
Enhance Policy to support complex service modeling (e.g. complex constraints, nested resources and related policies)
Enhance SDC to model & define constraint and optimization policies
Enhance SO to support workflows related to management of 5G related network entities
Rationale
Optimization needs for typical carrier deployments will involve large, distributed data centers, and will involve complex rules and constraints governing how multiple network elements are instantiated and managed. Hence, these are critical functional requirements for a carrier-grade ONAP. Specifically, within the 5G domain, efficient allocation of resources and dynamic, load- and cost-aware reconfigurations are valuable.
Impacts
Impacted ONAP components are: A&AI, Multi-cloud, Policy, OOF, SDC, SO
Companies
Participating companies are: AT&T, Cisco, Intel, Netcracker, VMWare

10. Thank You!