== Logistic

== Attendees

Presenter: Anki Patel (AT&T)
Content: https://lf-onap.atlassian.net/wiki/pages/viewpage.action?pageId=16224067
SNIRO is now: ONAP Optimization Framework
Main aspect for today: interaction between policy framework and how application is build
details the HAS - policy driven homing and resource application

explains the flow (policy specification -> OF engine -> Graph algorithms/ILPs)
- policies are read from the policy sub-system
Q:: is the policy provided by optimization or policy framework?
A: provided by policy framework but constraint by optimization framework
Q:: policy is currently for closed loop, how would that support an optimization policy?
A: policy framework provides several policy engines and languages (for domain), optimization policies are configuration policies and XACML is perfetly suitable for that
D: right now YAML is used a policy language (only operatinal policies at the moment), for optimization we need configuration which is different
D: configuration policies are freeform based on XACML with various payload, e.g. JSON
D: optimization might also introduce other solvers (FOSS) in its evolution, e.g. to use Drools as a language
D: Drools can also easily be translated into YAML

Q:: The PDP is XACML?
A: XACML is used to store the policies, the optmization uses XACML to carry payload for optimization problems
D: intend is to convert (XACML) policy to an optimization problem definition

Q:: How does the optimization function work with policy?
Q: Which site is closer to the policy engine (framework) and which is closer to controllers
D: this project is not associated with policy framework, but requires it - but at the same time the optimization function can be used in a closed control loop as well
D: policy provides the input for what needs to be optimized
D:: would be good to provide some use cases to see how it works and flows
A: use cases
- UC1: service instantiation (details discussed)
- UC2: change management scheduling (details discussed)

Q: can this also be used for closed control loop use cases?
A: yes, e.g. optimize radio access network (maximize throughput using various control parameters)

Q:: can you do the distance calculation (from demo) also in Drools
A: can be used OpenPlaner for optimization, it is using Drools, then we can integrate everything, so yes
A: but we haven't done that yet

Q:: can it be considered a contraint that is input to the optimization?
A: the contraints we have are modelled into policies, when policy is retrieved, the engine can translate that into contraints
A: by exposing contraint into policy 3rd party can define them, also everything is stored in policy repo and we can leverage other policy characteristics (e.g. prioritization, conflict)

Q:: how to plugin data?
A: policy requires data, so the framework provides the libraries to interface with data providers (runtime information)

Q:: can we put some sequence diagrams into the Wiki to understand the flow?
A: outside the scope of this presentation, but YES we should do that and provide more information on documentation
A: plan is to include more and more information, e.g. sequence diagrams

AP1:: (all): provide commitment to project to Pam and in confluence
AP2:: (Jorge, Pam): explain documentation plan and diagrams that are planned for Wiki