This is our second - out of three - article about the vision of EdgeLab.ai and the three fundamental pillars of the EdgeLab Platform: we have discussed EdgeLab Automotive a few weeks ago, and now we move on to EdgeLab Cloud.
These are the building blocks of the Immersive Mixed Reality Platform that offers a near real-time, versatile, realistic and repeatable environment for building the automotive products that perform well in the stochastic and diverse real world.
If you are an automotive SoC company, EdgeLab.ai will help you take steps to mitigate design risks, shorten development cycles and deliver products that meet or exceed industry safety standards.
An end-to-end, close-loop, mixed-reality platform to let you explore, design, build and train / validate compute solutions, critical to the future of the connected and autonomous cars.
The ability to see a design from the immersive experience of vehicles, occupants, pedestrians, motorbikes, and other objects on the road offers new and valuable insight and understanding that can minimize risks, improve development time, and increase safety.
From test and development to validation and AI/ML training, EdgeLab comprehensive Digital Twins will be crucial to accelerating development, improving safety, and enhancing the user experience.
With EdgeLab Cloud, automakers and operators can choose from commercial or OSS orchestrators, and private or public clouds hosting options, or select from blueprints to configure a managed core infrastructure to host virtualized and containerized edge Virtual Network Functions (VNFs).
Deploy applications from our diverse portfolio of real-world or synthetic VNFs to test, validate, and characterize infrastructure ingredients to explore the best options for your designs and use-cases.
Cloud computing made it possible for Software, Platform, and Infrastructure to be delivered as Services.
EdgeLab.ai cloud provides the ODMs with a unified approach to integrate and test their products on a diverse ecosystem of public cloud services (AWS, Azure, GCP) or private cloud built on common OSS frameworks (OpenStack, Kubernetes, Mesos) utilizing virtualization and containerization.
A diverse collection of Virtual Network Functions (VNFs), benchmarks, and test framework enables the architects to create a service chain of complex, real-world scenarios for development and deployment.
CORE - vIMS / Session Border Controller, vFirewall, vDPI, vIP-sec, Cable Modem Termination System (vCMTS), vRouter, SD-WAN, Network Address Translation, Network Slicing
EDGE - vEPC, g/eNB, vUE, MEC (OpenNESS), Video Analytics
SYNTHETIC - NFVi-marks (packet forwarding, single/multiflow L3, MPLS tagging, Access Control List, LB / S-tuple lookup, buffering).
Edge virtualization extends the software-define concept of the cloud universally. This approach enables the remote provisioning, management and monitoring of edge devices across large geographical footprints, providing a more secure and cost-effective alternative.