Network Digital Twins

Check out our newest blog, where we discuss the network #digitaltwin and how it is intended to accurately reproduce the behavior of your live physical network.

Since our founding in 1999, the team at SCALABLE Networks has been focused on developing simulation technology and products to replicate live networks using high fidelity software models. Our goal has always been to ensure that any meaningful interactions between live software, hardware, or humans and the physical network can be accomplished via a model of the network, such that the resulting behavior from the “digital twin” accurately reproduces the behavior of the live physical network.    

Our first network simulation product, QualNet, launched in 2001 and EXata, launched several years later, asked, “Is it Live or is it QualNet (EXata)?”  (riffing off a popular advertising campaign for Memorex tapes). It is gratifying to see that almost two decades later, this concept of network digital twins is gaining widespread acceptance for a range of applications; from performance and interoperability debugging, system test & evaluation, operations & maintenance, to perhaps most importantly - cyber resilience!

A network digital twin refers to a computer simulation model of the communication network, along with its operating environment and the application traffic that it carries. The digital twin can be used to study the behavior of its physical counterpart under a diverse set of operating conditions, including cyber attacks, in a low-cost and zero-risk environment. However, in order to do so effectively, the digital twin must have sufficient fidelity so as to accurately reflect the network dynamics that can cause networks to behave unpredictably. The network dynamics are typically created by the interplay among the communication protocol, device configurations, network topology, application traffic, the physical environment, and any cyber threats. Thus the digital twin must reflect each of the preceding components.

Over the last two decades, SCALABLE has invested substantially in advanced R&D, partially sponsored by DARPA and other DoD agencies, to develop patented discrete-event simulation kernels. The simulation kernels leverage parallel and multi-core computing technology to realize real-time and faster than real-time execution for network digital twins. The faster than real-time digital twins can be used for efficient ‘what if’ analyses such as monitoring the behavior of the system under different network configuration settings, varying traffic distributions, and diverse cyber threats using stochastically generated traffic profiles. In addition, live hardware and software applications can be seamlessly interfaced with, or integrated into, a network digital twin that executes in real-time. These real-time network digital twins can then be used to improve management, performance and cyber resilience of networks in all domains, from commercial enterprise IoT to military networked systems operating from seabed to space.  Additionally, SCALABLE continues to expand its network digital twin technology and applications into artificial intelligence, machine learning, and autonomous systems – it’s an exciting time in the business of digital twins!

Written by Dr. Rajive Bagrodia, CEO of SCALABLE Networks. Dr. Bagrodia is a thought leader in the field of modeling and simulation, test and analysis, and cyber resilience of large scale networks. You can follow Dr. Rajive Bagrodia on LinkedIn.  

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Network Digital Twin - Network Simulation

About the Author

About The Author: 
Dr. Rajive Bagrodia is the Founder and CEO of Scalable Network Technologies, Inc. and an Emeritus Professor of Computer Science at UCLA. Previously, Dr. Bagrodia served as a Professor of Computer Science at UCLA, where he led a research group in mobile computing and parallel and distributed programming that produced simulation systems such as Maisie, Parsec, and GloMoSim. His research was supported by large, multi-investigator grants from federal agencies including DARPA and NSF. Dr. Bagrodia founded SCALABLE Network Technologies in the wake of significant innovations his research group achieved in the theory and practice of performance prediction for complex, large-scale computer and communication systems. Today, SCALABLE is recognized as a global leader in the development of advanced simulation technology and in its application to enhance cyber resilience of commercial and military systems. Dr. Bagrodia received a Bachelor of Technology in Electrical Engineering from the Indian Institute of Technology, Bombay and a PhD degree in computer science from the University of Texas at Austin. He has published over 175 research papers in Computer Science journals and at international conferences on high performance computing, wireless networking, and parallel simulation.