Requirements for the Second Wave

The 4th SD-WAN Summit will take place from 24th to 26th September 2019.

As each year, the programme will benefit from many operators and enterprises testimonies. They will address their development focal points and the future evolution of their services.

Renowned experts will underline the maturity challenge of SD-WAN and what are the pain points.

With more than 500 participants (+25%) from 38 countries (+35%) and a 25% growth of exhibitors number, the 3rd SD-WAN Summit has confirmed its place as the leading event for stakeholders in this new technology.

The 21st Edition of the MPLS+SDN+NFV World Congress will be held 9/12 April 2019 in Paris.

The Congress will once again gather major actors of service providers and enterprises networks evolution.

Over the years, the MPLS SDN NFV World Congress attendance has grown. The 2018 edition surpassed the record number with 1,600 participants.

The 20th Edition of the MPLS+SDN+NFV World Congress remained one of the most well-attended event with delegates representing service providers and large enterprises from across the globe delivering thought leadership driving service provider and cloud scale networking.

Presentations lead by renowned experts on orchestration, automation, and service delivery along with panel discussions ranging on a diversity of topics from SDN, NFV, 5G, SD-WAN and Blockchain provided ample opportunity for attendees to learn about new technologies, ask questions, and then dive deep with on the exhibition floor.

Today’s networks have scaled to a size and complexity that is beyond human ability to manage, maintain availability, and achieve optimality. Artificial Intelligence and Machine Learning are seen as the only way out to continue growing.

Indeed, SDN and NFV are bringing about programmability by decoupling control plane from the network devices and running softwarized network function on commodity hardware. The SDN-NFV controller is expected to play a key role for service provider network management by programming their customized network management policy. This controller requires computational intelligence.

During the past several years there have been remarkable advancement in academic research for applying machine learning to network management. Machine learning is applied to diversified data including traffic flow, performance, quality, syslog, configuration file, trouble tickets, SNS. In fact, AI can be practically used in many networking areas, such as fault isolation, intrusion detection, event correlation, log analysis, capacity planning, and design optimization, just to name a few.