AI & Machine Learning in NFV/SDN: Key Takeaways

Sandra O'Boyle
11/10/2017
50%
50%

At Light Reading's recent OSS in the Era of NFV/SDN event in London, I moderated a panel discussion on "Analytics, Machine Learning & AI in Next-Gen OSS/BSS" and wanted to share some key insights from the speakers:

  • Dima Alkin, VP Service Assurance, Teoco Corp.
  • Oliver Cantor, Business Network and Security Solutions, Verizon Communications Inc. (NYSE: VZ)
  • Ignacio Mas, Senior Expert in Programmable Network Architecture, Ericsson AB (Nasdaq: ERIC)
  • Mark Pendred, Control and Orchestration Lead, BT Media & Broadcast
  • Jay Perrett, Founder and CTO, Aria Networks Ltd.

Machine learning and AI can help, but set the right expectations
Machines can solve problems, learn what's happening and act on those learnings -- but they have to be programmed how to learn and they have to be taught rules and outcomes (e.g., how to route traffic through a network). However, to utilize machine learning (ML), companies first have to overcome barriers such as organizational distrust and a general resistance to ML and AI. Dima Alkin from TEOCO explained that in the case of service assurance, we are very forgiving of human error in root cause analysis and trouble-ticketing systems, but we expect machines to be absolutely right every time, even if it's unrealistic. The onus is still on us to give machines the requirements and get objectives right -- what are you trying to do?

Oliver Cantor from Verizon was cautious, and said the hardest part is applying machine learning to the multi-dimensional network layer; operators are not bad at the customer side of things. He advocated getting the data in one place and starting with machine learning to understand patterns and what the data is telling us.

Ignacio Mas from Ericsson, a network engineer at heart, discussed the issue of maturity of using machine learning and AI models in the network, stating that the models are already there and being used by operators to crunch data to predict customer behavior and prevent churn. With networks becoming programmable and software-based with SDN/NFV, operators should try these models out.

Dima Alkin also discussed why big data analytics projects have failed in the past. One issue was the amount of time and resources spent on reprocessing, normalizing and standardizing data to make it perfect and to make analytics work. He advocates consuming available data as is and moving as close as possible to live network environments to try out models, rather than wasting time in proof-of-concept trials.

AI – top down, bottom up or both?
There was debate and disagreement on this topic -- whether AI algorithms in areas such as policy and closed loop control needed to be top down -- decided by an intent or information model -- or bottom up -- through optimizing control loops at the infrastructure layers.

Jay Perrett, founder and CTO of Aria Networks, was adamant that networks should be a commodity -- an intelligent Ethernet cable that decides how to get from A to B -- and that network optimization should be handled top down based on what the service needs and what's right for the business.

Ignacio Mas from Ericsson argued we need both -- a top-down and bottom-up approach -- to create a network that will support services and make changes we want, and react to customer needs/what we need from the network.

Perrett also discussed how AI is important as it can scale, operate automatically (e.g., self-healing VNFs) and adapt to new requirements/changes in the model (e.g., to support new use cases). With an information model and plug-and-play algorithm system (e.g., topology optimization, route optimization), you can probe and change so that when a new use case comes on, it can adapt to the environment. This is important, as you cannot anticipate use cases that will be important in three years, for example.

Next page: The business value of AI

(0)  | 
Comment  | 
Print  | 
Newest First  |  Oldest First  |  Threaded View        ADD A COMMENT
More Blogs from Heavy Lifting Analyst Notes
The shift to application and network virtualization by operators and CSPs requires a new generation of multicore processors that are being introduced by many vendors.
In the wake of a damaging cyber attack in 2015, Philip Clayson was tasked with creating a cyber breach remediation plan for over 600 applications across TalkTalk's consumer and enterprise divisions and to deal with the operator's 'tech debt.'
It's still hard to say whether carrier SDN is really a success or a failure, but the needle is moving on SDN commercialization – albeit not as quickly as some might hope.
The most recent Thought Leadership Council (TLC) survey finds that although most communications service providers (CSPs) prefer to have a solid plan in place before moving on a new market trend, it's not looking to be the same for automation, as most CSPs surveyed say they are moving forward without solid plans.
Software-defined wide area network (SD-WAN) is the primary focus for cable in 2018, with fierce competition across the market.
Featured Video
From The Founder
The world of virtualization is struggling to wrench itself away from the claws of vendor lock-in, which runs counter to everything that NFV stands for.
Flash Poll
Upcoming Live Events
March 20-22, 2018, Denver Marriott Tech Center
March 22, 2018, Denver, Colorado | Denver Marriott Tech Center
March 28, 2018, Kansas City Convention Center
April 4, 2018, The Westin Dallas Downtown, Dallas
April 9, 2018, Las Vegas Convention Center
May 14-16, 2018, Austin Convention Center
May 14, 2018, Brazos Hall, Austin, Texas
September 24-26, 2018, Westin Westminster, Denver
October 9, 2018, The Westin Times Square, New York
October 23, 2018, Georgia World Congress Centre, Atlanta, GA
November 8, 2018, The Montcalm by Marble Arch, London
November 15, 2018, The Westin Times Square, New York
December 4-6, 2018, Lisbon, Portugal
All Upcoming Live Events
Hot Topics
21st Century Networking? Welcome to the Lock-In
Steve Saunders, Founder, Light Reading, 2/20/2018
How Long Before We Hit Peak MWC?
Iain Morris, News Editor, 2/23/2018
Stakes Run High for Tivo in Comcast Suit
Mari Silbey, Senior Editor, Cable/Video, 2/20/2018
Liberty Global: Not So Fast on D3.1
Alan Breznick, Cable/Video Practice Leader, Light Reading, 2/20/2018
AT&T Reveals Initial 5G Cities
Dan Jones, Mobile Editor, 2/21/2018
Animals with Phones
Live Digital Audio

A CSP's digital transformation involves so much more than technology. Crucial – and often most challenging – is the cultural transformation that goes along with it. As Sigma's Chief Technology Officer, Catherine Michel has extensive experience with technology as she leads the company's entire product portfolio and strategy. But she's also no stranger to merging technology and culture, having taken a company — Tribold — from inception to acquisition (by Sigma in 2013), and she continues to advise service providers on how to drive their own transformations. This impressive female leader and vocal advocate for other women in the industry will join Women in Comms for a live radio show to discuss all things digital transformation, including the cultural transformation that goes along with it.

Like Us on Facebook
Twitter Feed