Thanks for attending today and the excellent discussion. The meeting minutes 
and materials are uploaded at -- 
https://datatracker.ietf.org/meeting/interim-2018-nfvrg-01/session/nfvrg.

Request to continue the discussion on several interesting topics around IoT use 
cases, ATIS work etc. which came up in the meeting.
--
Thanks,
Ramki

-----Original Appointment-----
From: Ramki Krishnan
Sent: Wednesday, April 11, 2018 10:20 PM
To: Ramki Krishnan; nfvrg@irtf.org; di...@ieee.org; ISUKAPALLI, SASTRY S 
(SASTRY) (sas...@research.att.com); Nina Narodytska; Siamak Layeghy; Radhika 
Niranjan; Ranganathan, Raghu; PUZHAVAKATH NARAYANAN, SHANKARANARAYANAN 
(SHANKARANARAYANAN) (snaraya...@research.att.com); PUTHENPURA, SARAT (SARAT); 
onap-...@lists.onap.org; onap-usecase...@lists.onap.org; Giridhar Jayavelu; T. 
Sridhar
Cc: Susan Hares; paparao.palacha...@us.fujitsu.com; Hesham ElBakoury; Zebetian, 
Mohammad; Carlos Pignataro (cpignata); Hariharan Ananthakrishnan; Tim Chown; 
Diego R. Lopez; g_cha...@dell.com; Bernier, Daniel; Oberle, Karsten (Nokia - 
DE/Stuttgart); Michael Van Norman; Giovane Moura; Skutt, Timothy (Tim); 
Mahmoudi, Charif (IntlAssoc); Sumandra Majee; pierre.ly...@keysight.com; 
Natale, Bob; MAY, JOHN; SOMASUNDARAM, PRABHURAM; Sana Tariq; Arash Hekmat; 
Parviz Yegani; Xinhui Li; Margaret Chiosi (A); vincent.sch...@telekom.de; Jorge 
Salazar; Kedalagudde, Meghashree Dattatri; BARTOLI, PAUL D; Demers, Sebastien; 
Bainbridge, David; steve.s.kni...@verizon.com; BEGWANI, VIMAL; BRAGG, DEAN L; 
Lando,Michael; Josef Reisinger
Subject: NFVRG interim meeting -- Model-driven & AI-Enabled Inter-Cloud 
Optimization
When: Tuesday, April 24, 2018 10:00 AM-12:15 PM (UTC-08:00) Pacific Time (US & 
Canada).
Where: In person (VMware campus) + Remote (Zoom)

Dear All,

Please find details on the NFVRG interim meeting on "Model-driven & AI-Enabled 
Inter-Cloud Optimization". Looking forward to your participation.

More on Network Functions Virtualization Research Group (NFVRG): 
https://irtf.org/nfvrg

--
Thanks,
NFVRG Co-Chairs (Ramki & Diego)

Zoom:                                vmware.zoom.us/j/3055973130
VMware address:            Promontory A, Hemlock, 3401 Hillview Ave, Palo Alto, 
CA 94304
VMware campus map:   
https://www.vmware.com/files/pdf/vmw-directions-to-vmware.pdf


Title: Model-driven & AI-Enabled Inter-Cloud Optimization

  *   Introduction
     *   "Use Cases (5G/Edge Computing)"                                        
                                          - Dilip Krishnaswamy (Reliance Jio, 
India)                           - 20 min.

"Architecture & Benefits"                                                       
                                          - Sastry Isukapalli (AT&T, New 
Jersey, USA)                       - 20 min.

  *   Research Challenges & Solution Direction
     *   "Recent Trends in Constraint Optimization and Satisfaction"            
                      - Nina Narodytska (VMware, California, USA)               
     - 40 min.
     *   "SCOR: Software-defined Constraint Optimal Routing platform for SDN"   
          - Siamak Layeghy (Univ. of Queensland, Australia)           - 40 min.


Agenda Details:
"Use Cases (5G/Edge Computing)" - Dilip Krishnaswamy (Reliance Jio, India)
Abstract: Emerging 5G network architecture will consist of a large number of 
distributed "clouds" with dynamically varying resource availability in terms of 
compute, or storage, or network bandwidth, or energy, and with support for edge 
computing/services. The ability to serve users with dynamic requirements across 
geographies using such distributed resources will require learning  and 
prediction of distributed models across users and infrastructure to dynamically 
and efficiently allocate resources. This talk will cover different use-cases 
that drive the need for such distributed architecture, and motivate the need 
for building distributed models of users and infrastructure, and the need for 
dynamic resource optimization across these distributed and edge clouds.

"Architecture and Benefits" - Sastry Isukapalli (AT&T, New Jersey, USA)
Abstract: This talk focuses on the Open Network Automation Platform (ONAP) 
Optimization Framework (OOF) open source effort, which is a declarative 
framework based on a Policy- and Model-driven, architecture with AI assists. 
While the core design framework is based on MiniZinc, it also supports 
optimization applications based on generic or problem-specific custom solvers. 
The system is presented with a set of example applications, including dynamic 
resource allocation under various complex constraints.



"Recent Trends in Constraint Optimization and Satisfaction" - Nina Narodytska 
(VMware, California, USA)
Abstract: In this talk we overview several constraint optimization solvers and 
consider the main design principles behind these search procedures. First, we 
look at Boolean Satisfiability (SAT) and Integer Linear Programing( ILP) 
solvers and their extensions. These decision procedures  offer a restrictive 
modeling language based on Boolean logic and integer linear constrains, and 
powerful search procedures. Next we will talk about Constraint Programing (CP) 
solvers, whose rich modeling languages include expressive global constraints 
and a variety of decision search procedures, e.g., backtracking search, 
lazy-clause generation,  etc.



"Software-defined Constrained Optimal Routing (SCOR)" - Siamak Layeghy (Univ. 
of Queensland, Australia)
Abstract: Software-defined Constrained Optimal Routing (SCOR) is a SDN 
northbound interface which  is based on constraint programming techniques to 
provide a robust, declarative interface for stating networking problems. The 
main advantage of SCOR, is to hiding the complexity of solving the problem from 
the user.  Accordingly, users only state the constraints and utility functions 
of the routing problem and the solution is provided by a powerful generic 
solver. It is implemented in the MiniZinc constraint modelling language 
consisting of nine fundamental constraint programming predicates which cover 
different aspects of the routing problems.  This interface (set of predicates) 
is sufficiently expressive to handle all the known and relevant QoS routing 
problems. Furthermore, the practicality and scalability of the approach are 
demonstrated via some example scenarios, with use cases in real-world SDN 
controllers.


Dilip Krishnaswamy (Reliance Jio, India) Bio:
Dilip Krishnaswamy is currently serving as Vice President (New Technology 
Initiatives) at Reliance Jio Infocomm Ltd. Previously, he has worked as a 
senior scientist at IBM Research, as a platform architect at Intel, and as a 
senior staff researcher in the office of the chief scientist at Qualcomm. He 
has a PhD in electrical engineering from the University of Illinois at 
Urbana-Champaign. He is an inventor on 61 granted US patents, and has 70+ 
publications.  His research interests include distributed information 
processing, distributed function virtualization, distributed resource 
management, blockchain technology, edge services, NFV/SDN,  NB-IoT, AI/ML, and 
5G architecture & systems.



Sastry Isukapalli (AT&T, New Jersey) Bio:
Sastry Isukapalli is Principal Inventive Scientist at AT&T Labs Research. 
Previously, he was part of the Machine Learning and Data Mining groups in AT&T 
Research. Prior to the AT&T tenure, he was Assistant Professor at the RW 
Johnson Medical School. He obtained his PhD from Rutgers University for 
development of the Stochastic Response Surface Method under the direction of 
Prof. Panos Georgopulos. He is also an Alumnus of the Indian Institute of 
Technology, Madras, India. He is an alumni of Savera Systems, Virtual Gold, and 
Kirusa Inc. He is a committer for the open source ONAP Optimization Framework 
Project (onap.org).



Nina Narodytska (VMware, California, USA) Bio:
Nina Narodytska is a researcher at VMware Research. Prior to VMWare Research, 
she was a researcher at Samsung Research America, a postdoctoral researcher in 
the Carnegie Mellon University School of Computer Science and the University of 
Toronto. She received her PhD from the University of New South Wales in 2011. 
Nina works on developing efficient search algorithms for decision and 
optimization problems.  She was named one of "AI's 10 to Watch" young 
researchers in the field of AI. She also received an Outstanding Paper Award at 
AAAI 2011 and an outstanding program committee member award at the Australasian 
Joint Conference on Artificial Intelligence 2012.



Siamak Layeghy (Univ. of Queensland, Australia) Bio:
Siamak Layeghy is finishing his PhD at the School of Information Technology & 
Electrical Engineering at the University of Queensland, Brisbane, Australia. He 
received his Bachelor in Telecommunication Engineering and his Master in 
Electronics Engineering from K.N.Tousi University of Technology, Tehran, Iran.  
He has several years' experience in Network Engineering in Iran's National 
Infrastructure Company. His main research interests include Software Defined 
Networks, Routing and Traffic Engineering and Network Optimization.




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