Nabil Damouny is the chief strategist for Autonomous Edge, where he focuses on edge computing in the era of artificial intelligence (AI) with applications in IoT and self-driving cars.

Nabil was the co-founder of Basis Communications, acquired by Intel. Basis products and technologies powered DSL high-speed Internet access devices for more than 5 million homes and small businesses, in USA, Japan and China.

Most recently, Nabil was the Liaison Officer between ONF, focusing on Software-Defined Networking (SDN), and ETSI NFV, focusing on Network Functions Virtualization. Both SDN & NFV are the architectural foundations of next generation telecommunications networks infrastructure.

Nabil grew up in Egypt and has worked in Silicon Valley since the 80s. He earned a BSEE degree from Illinois Institute of Technology (IIT) in Chicago, and a MSECE from the University of California, Santa Barbara (UCSB). He is a life member of IEEE and holds 3 US patents in computer architecture and remote networking.

The Role of the Autonomous Edge TM in Data Analytics

Abstract

As massive amounts of structured and unstructured data are being generated by billions of devices today, with this trend expecting to rise dramatically, it can bring data processing in the cloud to a crawl. However, with the advent of Autonomous Edge TM Computing, hope is on the way!

Currently there is a tendency to think that all data processing happens in the cloud, however the Edge (defined as anything outside the cloud) is expected to play a key role, especially for those use cases requiring real-time, low-latency processing.

Specifically, with Autonomous Edge TM, compute processing will shift from centralized, back to distributed architecture. The result is that a compute node at the end device, the gateway or the Fog node, is intelligent, processing-capable, offloading real-time data processing from the cloud. New evolving technologies in compute, storage and the underlying networks will enable such capabilities. The result will affect where data analytics need to be optimally handled.

This presentation will discuss the emergence of the Autonomous Edge TM, and its role and application in IoT, where sensors spread across almost every industry are going to trigger a massive influx of big data. It will also touch upon its application in autonomous, self-driving cars. It will conclude by examining some start-ups strategy and offerings, and present ideas for future innovation.

 Outline

- The world of Big Data
    - AI, deep learning and predictive analysis

- Dependence on the Cloud
    - Keeping up with IoT and Autonomous Cars

- The Autonomous Edge
    - Moving technology out of the DC – Evolution to distributed computing
    - Edge supplanting the cloud
    - The 5 flavors of Autonomous Edge

- Edge processing for IoT and Autonomous driving

- Technology trends
    - Compute; Storage; Networks (SDN, NFV, 5G, SDS)
    - Neural networks, AI-deep learning chips

- Established Companies strategies
    - IBM, Microsoft, Cisco, Amazon (Organic, partnerships, acquisitions)

- Start-ups strategies
    - Nebbiolo, FogHorn, Interactor, Deep learning chips.