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- Most optimization problems can be solved in a declarative manner using a high-level modeling language.
- Recent advances in open source optimization platforms allow the solution process to be mostly solver-independent.
- By leveraging the library of standard/global constraints, optimization models can be rapidly developed.
- By developing a focused set of platform components, we can realize a policy-driven, declarative system that allows ONAP optimization applications be composed rapidly and managed easily
- Policy and data adapters
- Execution and management environment
- Curated "knowledge base" and recipes to provide information on typical optimization examples and how to use the OOF
- More importantly, by providing a way to support both "traditional" optimization applications and model-driven applications, we can provide a choice for users to adapt the platform based on their business needs and skills/expertise.
The highly modular architecture of OOF to cater to different kinds of optimization problem requirements of various use cases is depicted in the following figure.
The architectural updates done in Frankfurt release provides a lot of benefits from a platform capability perspective. This is described in the followed illustration. It enables easy extension of the platform to be able to support new use cases more easily.
Project Landing Page:
Optimization Framework Project
Project Meeting Minutes:
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Role | Name | Linux Foundation Login (LFID) | Email Address |
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PTL | krishnaa96 | krishna.moorthy6@wipro.com | |
Committers | snarayanan | snarayanan@research.att.com | |
vrvarma | vv8305@att.com | ||
amartell | arthur.martella.1@att.com | ||
dhebeha | dhebeha.mj71@wipro.com | ||
Sarat Puthenpura | sarat | sarat@research.att.com |
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Release name and time frame | Commits | Authors | Companies |
Beijing ( 11/17/2017 to 6/7/2018 ) | 118 | 18 | 7 |
Casablanca ( 6/8/2018 to 11/30/2018 ) | 142 | 18 | 7 |
219 | 12 | 6 | |
42 | 9 | 5 | |
184 | 21 | 9 |
Bitergia statistics for the last 2 years (since July 1, 2018):
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- Use Cases: The Key uses cases that OOF Project has contributed so far are:
- 5G OOF SON use case
- 5G E2E Network Slicing use case
- CCVPN use caseFine-Grained Placement Service (F-GPS)
- Change Management (CM)
- HPA
- Homing and Placement use cases
- Homing vCPE
- Homing 5G RAN VNFsService/VNF instantiation (e.g., vCPE)
- Multi-cloud
- VNF Scale out
- MDONS use case (from Guilin release)
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- Last Architecture review was done on Jan 7, 2020 as part of the Frankfurt release: OOF Frankfurt (R6) Architecture Review.
Artifact Information:
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Artifact | Repo | Docs link | Line Coverage | Test suites | Description |
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optf/osdf | https://gerrit.onap.org/r/admin/repos/optf/osdf | https:// |
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/projects/onap-optf-osdf/en/latest/index.html | osdf-csit | ONAP Optimization Service Design Framework (OSDF) is a model- and policy-driven optimization framework that makes it easier to build, deploy, and manage optimization applications for different use cases. | |
optf/has | https://gerrit.onap.org/r/admin/repos/optf/ |
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html#master-index | has-csit | OOF-HAS is a policy-driven placement optimizing service (or homing service) that allows ONAP to deploy services automatically across multiple sites and multiple clouds. | |
optf/cmso | https:// |
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html#master-index | cmso-csit | OOF-CMSO is an optimizing service that allows for the scheduling of VNF change management workflows to be executed at a time in the future. It enables a 3rd party client to provide SO workflow requests for multiple VNFs to be executed within a provided change window. |
- To our knowledge, OOF has been deployed and used in AT&T production, and it is also used internally in companies such as Wipro.