The European Space Agency wanted to derive insights from previously discarded data from the Global Navigation Satellite Systems and expose the scientific community to the benefits of deploying AI modules at the edge.
The requirements –
- Handle massive amounts of data infusion
- Expose the cloud on a smaller scale at the edge
- Build hardware that’s able to survive harsh conditions
The team worked with SixSq and HPE to provide an edge-to-cloud solution to deliver a hybrid, highly scalable solution easily deployed by research scientists on the ground and in space. This was 2019-20.
Around Feb 2021, NASA and HPE launched a supercomputer aboard the SpaceX CRS-12 rocket for the International Space Station (the literal edge) to study the technology’s ability to operate in the harsh conditions of space. This was possibly the first field test of in-space commercial Edge Computing and AI Capabilities. The edge supercomputer had to draw less than 500W and survive the vibrations of lift-off, plus radiation levels 10 to 100 times the levels on earth.
Welcome to the Final Edge Frontier – Space
What is all the fuss about data?
As per repeated studies, data-driven companies are 58% more likely to beat revenue goals than non-data-driven companies and 162% more likely to outperform laggards significantly. Data is becoming critical in almost every industry, whether it’s helping farms increase crop yields or fundamentally changing the game of basketball. The problem is it’s not always easy to put data to work. The Seagate Rethink Data report found that just 32% of the data available to enterprises is used, and the remaining 68% goes unleveraged.
Why talk about it now?
The convergence of 5G cellular, IoT, and Advanced Analytics is why. The combined effect of these technologies generates the data and the impetus to create tools that provide insights leading to new business models, operational efficiency and true technology-driven innovation. 5G enables intelligent network and app services connectivity to remote sensors coupled with low latency data transmissions of IoT data. Advanced Analytics can no longer be an afterthought; it will play a significant role in evolving 5G, IoT, and edge-enabling intelligence across networks, applications, and business.
IoT has been a hitherto unfulfilled promise in tech. The main roadblock has been accessing, transmitting, and handling vast amounts of data and associated IoT and 5 G-based systems analytics. Enter Next-Gen Cloud Computing. The market interest in IoT increased because of the strides made by 5G and cloud technologies. The game plan is for the cloud to help handle the information volumes generated by IoT, as 5G boosts the network capacity. Combining these techs will be a boon to industries such as automotive and mobility, media and content, government/smart city, healthcare, manufacturing, energy, utilities and more.
The EDGE changes the game
The edge is where the data is first collected – an IP camera, an intelligent sensor, a POS machine, or a Formula 1 car.
Organisations that have realised the benefits of cloud-native application design and can scale up and down in response to demand want those same characteristics in their edge solutions. As a result, the edge should feel like an extension of their existing cloud environment and not a bolted-on appendage.
As if on cue, the multi-access edge computes (MEC) market is expected to grow exponentially within the next few years. 5G, IoT, MEC, and real-time AI will unlock scenarios to help businesses derive a significant competitive edge.
Where it all started
The origins of edge computing were in the 1990s when content delivery networks (CDNs) put data collecting nodes closer to end-users. But it was limited to images and videos, not large data workloads. In the 2000s, the shift to mobile and early smart devices increased the strain on existing IT infrastructure.
It wasn’t until cloud computing that true IT decentralisation began, giving end-users enterprise-level processing power with increased flexibility, on-demand scalability, and collaboration from anywhere in the world. As a result, analysts predict that by 2022, 75% of enterprise data will be created and processed outside traditional central data centres or cloud providers.
Working on the edge
In an oft-quoted example, Formula 1 and AWS transformed the fan experience before, during, and after each race. Every F1 car contains 300 sensors which generate 1.1 million telemetry data points per second transmitted from the vehicles to the pits. This real-time data, combined with over 70 years of historical race data, extracts insights that inform, educate, and enrich the fan experience while pushing the boundaries on split-second change of race strategy that creates winning performances on the track.
When people visit Disney parks, they love the immersive nature of their experiences. They are less likely to know the degree to which technology plays a role in that experience. Attractions like Millennium Falcon: Smugglers Run and the most recent Star Wars: Rise of the Resistance are original designs using edge computing, powerful hardware, advanced robotics and control systems, advanced analytics, and much more.
Michael Tschanz, Director of Engineering Technology and Analysis at Disney Parks, Experiences and Products, emphasises how no application is all cloud or all edge – it has to be a healthy hybrid.
The Future Challenge
There is no clear one choice that will work for all. A single approach might not even work for one enterprise. It is the world of hybrid. Experience so far suggests that companies are not comfortable taking an all-cloud, all-edge, no on-prem strategy. At the same time, they realise the value of cloud/edge flexibility. Providers like HPE (with their experience from European Space Agency and Disney Parks) who can leverage this dichotomy to provide the most palatable offering will be the leaders of tomorrow.