Edge computing: Cloud-based data processing and storage that is physically located near where it is required, to increase speed and reduce bandwidth usage.

Edge computing aids network optimization by measuring and evaluating network performance for users through the entire web.
It finds minimal latency and most reliable network path for user traffic.

• For locations with subpar internet connectivity, having the ability to store and process data at the edge improves reliability once the cloud connection is disrupted.
• For example, US-based BlueDot
• This means legacy industrial equipment can be seamlessly and efficiently connected to modern IoT platforms.

Processing often involves normalizing and analyzing the info stream to search for business intelligence, and only the results of the analysis are repaid to the main data center.
In traditional enterprise computing, data is produced at a client endpoint, like a user’s computer.
That data is moved across a WAN such as the internet, through the corporate LAN, where the data is stored and worked upon by an enterprise application.
This remains a proven and time-tested approach to client-server computing for most typical business applications.
Edge and cloud computing solutions both have a multitude of individual and joint applications now and in the foreseeable future, and in conjunction, offer enterprises an exciting wealth of IT capabilities.

Although only 27% of respondents have previously implemented edge computing technologies, 54% find the idea interesting.
Edge nodes useful for game streaming are known as gamelets, which are often a couple of hops away from the client.
Per Anand and Edwin say “the edge node is mostly a couple of hops away from the mobile client to meet up the response time constraints for real-time games’ in the cloud gaming context.”
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From The Edge To The Cloud

IoT advantages from having compute power closer to in which a physical device or data source actually exists.
In order for the info made by IoT devices to react faster or mitigate issues, it needs to be analyzed at the edge, rather than traveling back to a central site before that analysis can take place.
An IoT device is really a physical object that is connected to the web and is the source of the data.

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“In the case where the edge storage is mainly focused as a data ingestion platform that then replicates or transmits the data to the cloud, a larger proportion of storage could be HDD rather than SSD to allow for more data density,” he says.
But adding storage by way of a networked PC, a small server or perhaps a NAS device only really works in office or back office environments, because they are static, environmentally stable and usually reasonably secure.
Edge computing is a better solution for supporting smart and specialized devices that perform special functions and are not the same as regular devices.
With the increased using smart devices, the risk vector of attackers compromising the devices increases.

Cloud Infrastructure Uses

These add the factory floor, with edge devices attached to manufacturing equipment and power tools, to cameras along with other sensors out in the environment, to telecoms kit and also vehicles.
While many edge gateways or servers will undoubtedly be deployed by providers looking to support an advantage network , enterprises looking to adopt an exclusive edge network will have to consider this hardware aswell.
The ongoing global deployment of the 5G wireless standard ties into edge computing because 5G enables faster processing for these cutting-edge, low-latency use cases and applications.

• Having the ability to teach machines to toggle between a computation which might be performed at the edge and something that will require the cloud can be a challenge.
• A database that’s maintained and configured for scalable business intelligence and analytics is known as a cloud data warehouse.
• One of the most cutting-edge applications of edge is frictionless store checkout in retail, allowing customers to get items off the shelves and walk out the door, getting tested without waiting in line.

Autonomous vehicles are an example of why IoT solutions and edge computing have to work together.
An autonomous vehicle driving later on needs to collect and process real-time data about traffic, pedestrians, street signs and stop lights, in addition to monitor the vehicle’s systems.

Achieving reliability in a distributed system like an edge architecture requires the network to manage node failures efficiently.
Users should always have the ability to access the service without interruption, even when a single node falls.

While the bulk of data processing for connected devices across industries now happens in the cloud, sending data backwards and forwards across a central server can take seconds too long — and also takes a ton of expensive infrastructure.
By the entire year 2024, an estimated 149 zettabytes — the equivalent of a lot more than 149T gigabytes —will be created globally each day.
While both edge and cloud computing solutions are agile, scalable, reliable, secure, and enhance productivity and performance, some vital differences exist between your two computing platforms.
As regulators make an effort to understand more concerning the operations and great things about edge and cloud computing systems, it is imperative for organizations that use these computing platforms to comply with all relevant regulations.