By Jeff Harris, Vice President, Keysight Technologies
The term ‘metaverse’ brings to mind images of someone wearing virtual reality (VR) or augmented reality (AR) glasses and avatars exploring a cartoonish world. As you think more, you might associate terms like simulation, digital twins, or even emulation as part of the definition. This raises the question of the interrelation, and differences, between the terms and despite variations, there are distinguishing characteristics that give rise to consistent attributes.
⦁ A simulation models and predicts system-level environments based on a broad set of assumptions. It can include several subsystems with potential for interactive behaviors and, as a result, not necessarily accurate, complete, or real-time.
⦁ An emulation is a subset of simulation replicating a single closed-loop behavior or set of behaviors, including those behaviors’ expected responses. Emulations are more accurate, complete, interactive, and real-time.
⦁ A digital twin is an interactive model capable of replicating the interactions and behaviors of a specific system with fidelity. They have a physical counterpart, which could be as distinct as a car and as abstract as the data flow over a car’s network.
In general, simulations predict, and emulations replicate and digital twins can deliver either. In the product development world, they are used as a known good reference and for identifying performance anomalies in system-level behaviors.
Beyond the Consumer Metaverse
The visual realism associated with physical replicas hosted in a metaverse environment gives the impression that models of environments, objects, and interactions are precise.
More advanced emulations and digital twins focus less on visual representation in favor of heavier precision on behaviors such as methods of communication, expectations of interaction protocols and conventions, and stimulus responsivity that enable the model to behave as expected. These more advanced versions open a world beyond consumer applications such as product development.
The Metaverse and Product Development
A product development metaverse can be viewed as a continuum of connected interaction models, each capable of replicating some aspect of how a product would behave in response to a real-life environment, communication protocol, operating condition, or usage load. These models accurately replicate either a single or a set of interactions, becoming known good references. When combined with intelligent feedback loops, connecting or cascading multiple emulation systems can create a digital twin of a single interaction up to an entire ecosystem.
As the product metaverse expands, it will continue integrating innovative technologies, such as power consumption profiling based on typical and atypical usage models, traffic loading and advanced channel usage, and network disruption techniques. When combined with machine learning and powered by scalable computing resources, these digital twins could replicate anything from an IoT device to a worldwide data center network.
Product development digital twins provide the ability to design, build, and deploy a new solution at scale before it’s manufactured. Interactive models of this power are already in use and will continue growing in complexity and sophistication as deeper machine learning, AI prediction and more emulation models extend the reach.
Taking the Metaverse to the Enterprise, and Space
The enterprise version of the metaverse follows the same formula, modeling data interactions across networks, IT systems, and people interactions. It’s possible to create a digital twin of a user’s interaction with an application as the system has a replica from the buttons on an application screen to the operating system to the type of device they hold and its orientation.
Entire multisite networks can be modeled offline, including the wide range of applications running on those networks, the latest protocols employed, and the malware attacks it might see. The entire operating envelope can be predicted before deployment, including latency modeling from traffic congestion, network backup failover likelihood, software-defined networking deployment issues, and attack vulnerability.
If you are building a network for a 5G service about to be launched as part of a low Earth orbiting satellite (LEOSAT) network having a digital twin capable of emulating the trajectory, 5G signaling, including permutations from a range of weather conditions, and power modeling is transformative. With these insights, developers can optimize link margins, which impact; antenna size, space/weight/power, solar array size, launch costs, and even expected maintenance cycles.
Product Development hits the Metaverse Fast Lane
1. Super Charging Product Development
Thanks to integrating powerful emulation engines, digital twins dramatically accelerate product development and lower development costs as the performance envelope can be predicted before producing a unit. Whether the environment needed is for a device, an application, a network or large volumes of all three, new capabilities allow developers to rapidly explore what’s possible, troubleshoot potential issues, and optimize efficiencies at scale. This will usher in a transformative era of agile development.
2. Accelerating Iterative Innovation
Once built, developers can improve the quality and speed of a design using the digital twin to evaluate new features and because they are designed with extended reach in mind, as new features call for extending emulation features, a product development metaverse can expand. This could include more ways to infuse interference and disruptions or the ability to comply with additional standards. This continuous evolution will accelerate the worldwide applicability across multiple environments, ensuring the successful delivery of innovative products faster, safer, and more cost-effectively.
3. Collaboration
As innovation has become a global competition, access to a common virtual development environment allows teams to engage their best and brightest from any lab. This is critical as single designs often need to meet multiple interface and operation standards, and this expertise is not centralized. Collaborating in this manner dramatically accelerates troubleshooting and innovation breakthroughs and none of this would be possible without emulation-powered digital twins creating common tools every team could access. The metaverse allows teams to easily refine and improve products in real-time making remote work more productive.
The metaverse is much more than a virtual world of avatars; instead, it’s a door to transformative development environments that will herald the era of accelerated innovation. What started as emulations aimed at providing known good references is rapidly evolving and the development metaverse will forever change how engineers create, build, and refine products.
