Eden brings you embedded AI on a cloudless platform
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Ola Brising

Lead Editor at IoE Corp
Published - 04/11/2023|Reading time - 5 min 43 sec

For the 21st century, data is what oil was for the 20th century, but just as with raw oil, turning raw data into something valuable is a complex process. Eden is a private online sustainable Edge Cluster that allows you to refine your data close to the source.

No single company or public administration can survive without data, but raw data needs to be processed to make it insightful. The Economist stated in an article more than five years ago that data is "the oil of the digital era" and that it is for the 21st century what oil was for the 20th century, an enabler of new technologies, new products, and new businesses. Data will be a focal point around which the economy, society, and politics will organize. It is the future resource, especially regarding the rapid expansion of embedded AI and IoT (Internet of Things) systems.

But turning oil into something valuable has always been a complex process. Oil is crude when it comes out of the ground and needs to be cracked at a refinery to turn it into something useful, and data is similar. In its raw form, it's usually too big, too messy, and lacks structure. Therefore the refinement of data to information is crucial.

The importance of data to information refinement

Data refinement, also known as data processing or "data cleaning," transforms raw data into meaningful information. The process involves cleaning, filtering, transforming, and aggregating data to produce a more structured and organized form that can be easily analyzed. The importance of data refinement cannot be overstated in the data-driven world we live in today.

Refining data ensures that these errors are corrected, and the data is consistent and accurate. This is especially important in business settings where decisions are made based on the data. An error in the data can lead to incorrect conclusions and lost opportunities.

Once the data gets refined, it provides better insights and a more complete picture of the situation being analyzed. By removing irrelevant data and focusing only on the relevant data, analysts can gain a deeper understanding of the problem they are trying to solve, make better decisions and develop more effective strategies.

It also improves efficiency. By removing unnecessary data, the size of the data set is reduced, making it easier and faster to analyze, saving time and resources. By analyzing refined data, decision-makers can identify trends, patterns, and relationships that would be difficult to spot in raw data.

As the amount of data generated continues to increase, refining data will become even more critical in ensuring that we can derive meaningful information from it. So, ensuring that data refinement is given the attention it deserves is essential.

Escaping the Cloud with Eden

At IoE Corp, we have created Eden, a decentralized, autonomous, portable, secure virtual infrastructure for managing clustered workloads over Depos (decentralized pods) and services facilitating declarative configuration and automation. Eden is a private online Edge Cluster developed around a sustainable computing core and can be used for any informed infrastructure installation with embedded AI.

We understand that it's essential that the data refinement to information happens close to the source. Moving raw, unrefined data across the Internet makes no sense, as 99% of data in any system will look the same as the second before. Therefore, refining data to information at the Edge source is the way to go.

When we looked at the Internet's development, we noticed one destructive factor for future deployments; you always move the data to a centralized point; this works great for web and cloud services that are inherently centralized.

For IoT, it makes little sense to move all data in-processed from the IoT devices to a central point for processing and then move the data back out to devices again for actuation. This is bad for real-time responses and makes achieving sustainable computing nearly impossible. Also, the cost of running an embedded service becomes increasingly more prominent with each device added. The more data your service produces, the more transport, processing, and storage you will need and the more you will pay, making a Cloud approach far from sustainable.

A decentralized sustainable Edge Cluster

Instead, Eden is a decentralized model based on scalable device clustering where data is processed to information locally in the Eden Edge Cluster so that raw data is never needed to be pushed to the public cloud. It is a compute-efficient and cost-effective model that saves on bandwidth and external resources.

It is easy to add new devices as nodes and make it possible for any device to contribute computing resources over an intelligent mesh network so that computing can happen where needed and close to where the results will get used.

We have developed quantum-safe tunnels using polymorphic encryption keys and a consensus blockchain to verify the data moved between the nodes over the tunnels, thus creating trusted data private gardens and achieving data trust in Zero-Trust environments. The orchestration of computing and storage is done via service manifests that describe service rules, policies, and logic. An autonomous knowledge-based AI manages the underlying orchestration mechanics using network consensus over the blockchain as a deciding mechanism.

The orchestration dynamically updates the cluster topography to fit the current workload. Eden Depo services are generated and deployed similarly to container images; the exception lies in that Eden is Messaging Passing Interface (MPI), and the AI cluster is enabled as a default.

Eden reduces network traffic and data center usage. With Eden, the amount of data traversing the network can be significantly reduced, freeing up bandwidth. Bandwidth measures the quantity/size of data a network can transfer in a given time frame. Bandwidth is shared among users. Accordingly, the more data is supposed to be sent via the network at a given moment, the slower the network speed. Data on the edge is more likely to be helpful in the context of its environment. Instead of constantly sending data streams to the cloud, it makes sense to work with the data on the edge and make information available to services that can request it.

Optimized for efficiency with the possibility of using existing hardware

Clustered computing on Eden is typically more efficient than cloud data centers. Resources on edge devices are restricted. Therefore, edge devices do not scale horizontally as opposed to cloud infrastructure. Every piece of the edge tech stack is, typically and ideally, highly optimized for resource efficiency, and any computing done more efficiently helps reduce energy consumption. Eden is a safe place to harvest the data to information and begin making changes toward reducing carbon emissions.

There is also a realm of edge devices already deployed that is currently underused. Many existing devices can have data persistence, and some even for reasonably complex computing. When these devices send all their data to the cloud, an opportunity is lost. Eden enables companies to use existing hardware and infrastructure (retrofitting), utilizing the available computing power.

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