Easily Designing and Deploying AI enabled Network and Telecom services

Link to our paper: https://ieeexplore.ieee.org/abstract/document/10420625

Abstract: Currently, there do not exist any open-source systems that offer streamlined and easy development and productionalization of AI/ML enabled Intelligent Network and Telecom services. This is a big problem the Network operators/Service providers face today even though Network Function Virtualization (NFV) and Software Defined Networking (SDN) have become ubiquitous and the Next Generation networks aim to be more softwarized and AI-driven. This paper aims to show how to quickly and easily design Network, Telecom and Network Security services and deploy them into a containerized cloud environment. This paper also shows how to make the Network/Telecom services AI/ML enabled and deploy them in the same way into the containerized cloud environment. We will show using ONAP (an open-source whitebox Network Operating System and management platform) and Acumos (open-source AI platform for creation, sharing and management of AI models and solutions), and specifically using their DCAEMOD and Acumos Adapter components, that this is very easy to do. To serve as an example, we will create a Network service to analyze and classify malicious network traffic. Using the same framework and tools, we will deploy the created service as a set of communicating, containerized microservices into a Network Operating system and Management platform like ONAP which is cloud-agnostic and can be run on any cloud. The same created service can also be deployed directly into any other OSS or on any other cloud platform.

Citation:

D. Panchal, I. Baran, D. Musgrove and D. Lu, "Easily Designing and Deploying AI enabled Network and Telecom services," 2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT), Malang, Indonesia, 2023, pp. 689-695, doi: 10.1109/COMNETSAT59769.2023.10420625. keywords: {Cloud computing;Microservice architectures;Network function virtualization;Software defined networking;Artificial intelligence;Telecommunication services;Network operating systems;Acumos;AI4EU;Artificial Intelligence;Machine Learning;Network;Network Operators;Open Network Automation Platform (ONAP);Open Source;Operations support systems (OSS);Service Design;Telecom},

Author Bio:

Deven Panchal is an AI Leader currently with AT&T Labs Research, USA. He also serves as the Chief Innovation and IP/Patents Officer of the AT&T Innovation Network and is a Senior Member of the IEEE.

He has led the launch of 4 products into Open Source, being used worldwide today. He has delivered products and platforms projected to save ~1 billion$, enable Network Services creation, Network Management, Service Management and Orchestration and to Improve Customer service. He has helped build the world’s first AI/ML marketplace, was involved with AT&T’s first 5G VRAN/CRAN trial and delivered solutions that today power AT&T’s network as well as other telco networks. His work has benefited millions of people around the world, received multiple awards and has been featured on Forbes, TechCrunch, Light Reading, TelecomTV etc.

In the past, he has served as a Research Scientist at SAMEER, IIT Bombay building India's first indigenous LINAC and MLC for Cancer Radiotherapy.

Deven Panchal has been the Owner for several subprojects within Acumos, and has led global teams in the Design and Development of these components. He has written several papers on Acumos, and has contributed heavily to the official Acumos documentation. Additionally, he has been a Top Code Contributor and Peer reviewer for Acumos.

Feel free to reach out to him or use/cite his work.