Beijing RC2 documentation

Change-Id: Ic8b75e4cb33d6c4562cef2f2b9342974bfae03a3
Signed-off-by: fsandoval <frank.sandoval@oamtechnologies.com>
Issue-ID: OPTFRA-41

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+.. This work is licensed under a Creative Commons Attribution 4.0 International License.
+
+Architecture
+=============================================
+
+Introduction
+------------------
+OOF-HAS is an policy-driven placement optimizing service (or homing service) that allows ONAP to deploy services 
+automatically across multiple sites and multiple clouds. It enables placement based on a wide variety of policy 
+constraints including capacity, location, platform capabilities, and other service specific constraints. 
+
+HAS is a distributed resource broker that enables automated policy-driven optimized placement of services on a 
+global heterogeneous platform using ONAP. Given a set of service components (based on SO decomposition flows) 
+and requirements for placing these components (driven by policies), HAS finds optimal resources (cloud regions 
+or existing service instances) to home these service components such that it meets all the service requirements. 
+HAS is architected as an extensible homing service that can accommodate a growing set of homing objectives, policy 
+constraints, data sources and placement algorithms. It is also service-agnostic by design and can easily onboard 
+new services with minimal effort. Therefore, HAS naturally extends to a general policy-driven optimizing placement 
+platform for wider range of services, e.g., DCAE micro-services, ECOMP control loops, server capacity, etc. 
+Finally, HAS provides an traceable mechanism for what-if analysis which is critical for ease of understanding a 
+homing recommendation and resolving infeasibility scenarios.
+
+HAS in Service Instantiation workflows
+--------------------------------------------
+Below is an illustration of HAS interactions with other ONAP components to enable Policy driven homing. The homing 
+policy constraints have been expanded (and categorized) to highlight the range of constraints that could be provided
+to HAS for determining the homing solution. The figure also shows how HAS uses a plugin-based approach to allow an 
+extensible set of constraints and data models. 
+
+.. image:: ./diagrams/HAS_PolicyDrivenHoming.png
+
+More information on how homing constraints are specified can be found at OOF-HAS Homing Specification Guide, and a 
+sample homing template has been drawn up for residential vCPE Homing Use Case.  
+
+HAS Architecture (R2)
+----------------------
+
+.. image:: ./diagrams/HAS_SeedCode_Architecture_R2.jpg
+
+Lifecycle of a Homing request in HAS
+--------------------------------------------
+
+.. image:: ./diagrams/PlanLifecycle.jpg
+
+Use cases
+----------------------
+Residential vCPE: https://wiki.onap.org/display/DW/vCPE+Homing+Use+Case
+
+5G RAN: https://wiki.onap.org/display/DW/5G+RAN+use+case
+
+
+A sample heuristic greedy algorithm of HAS (using a vCPE as example)
+------------------------------------------------------------------------
+
+.. image:: ./diagrams/HASHeuristicGreedyAlgorithm.jpg