Edge computing is a distributed, open IT architecture that features decentralised processing power, enabling mobile computing and Internet of Things (IoT) technologies. In edge computing, data is processed by the device itself or by a local computer or server, rather than being transmitted to a data centre.
For edge devices to be smart, they need to process the data they collect, share timely insights and if applicable, take appropriate action. Edge computing is the science of having the edge devices do this without the need for the data to be transported to another server environment, to Put in another way, edge computing brings the data and the compute closest to the point of interaction.”
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.
Why Edge Computing is better than Chrome
The new Edge has a few features that set it apart from Chrome, like better privacy settings. It also uses less of my computer’s resources, which Chrome is notorious for hogging. Perhaps most importantly, the browser extensions you’d find in Chrome are also available in the new Edge too, making it way more useful.
Why edge computing is important?
Edge computing is important because it creates new and improved ways for industrial and enterprise-level businesses to maximize operational efficiency, improve performance and safety, automate all core business processes, and ensure “always on” availability.
What is Edge Computing used for?
Edge computing optimizes internet devices and web applications by bringing computing closer to the source of the data. This minimizes the need for long distance communications between client and server, which reduces latency and bandwidth usage.
Why edge computing is a game changer in this decade?
Edge compute is the data processing that takes place at the network edge to decrease latency and reduce demands on cloud compute and data center resources. The primary reason for the growth of edge compute is efficiency. … All of that collected data needs to be processed somewhere
Who Invented Edge computing?
The origin of edge computing can be traced back to the 1990s, when Akamai launched its content delivery network (CDN). The idea back then was to introduce nodes at locations geographically closer to the end user for the delivery of cached content such as images and videos.
Where is Edge Computing used?
Edge computing allows internet consumers to use more connected applications and devices without bogging down the network. It avoids network congestion by using the network’s edge to bring services closer to the user. The network’s edge may be located in base stations, hot spots, and in data centers
Why do we need Edge Computing.
The most important benefit of edge computing is its ability to increase network performance by reducing latency. … By processing data closer to the source and reducing the physical distance it must travel, edge computing can greatly reduce latency.
The 5 Best Benefits of Edge Computing
For many companies, speed is absolutely vital to their core business. The financial sector’s reliance upon high-frequency trading algorithms, for instance, means that a slowdown of mere milliseconds can have expensive consequences. In the healthcare industry, losing a fraction of a second can even be a matter of life or death. And for businesses that provide data-driven services to customers, lagging speeds can frustrate customers and cause long term damage to a brand. Speed is no longer just a competitive advantage—it is a best practice.
The most important benefit of edge computing is its ability to increase network performance by reducing latency. Since IoT edge computing devices process data locally or in nearby edge data centres, the information they collect doesn’t have to travel nearly as far as it would under a traditional cloud architecture.
It’s easy to forget that data doesn’t travel instantaneously; it’s bound by the same laws of physics as everything else in the known universe. Current commercial fibre-optic technology allows data to travel as fast as 2/3 the speed of light, moving from New York to San Francisco in about 21 milliseconds. While that sounds fast, it fails to consider the sheer amount of data being transmitted. With the world expected to generate up to 44 zettabytes (one zettabyte equals a trillion gigabytes) of data in 2020, digital traffic jams are almost guaranteed.
There’s also the problem of the “last mile” bottleneck, in which data must be routed through local network connections before reaching its final destination. Depending upon the quality of these connections, the “last mile” can add anywhere between 10 to 65 milliseconds of latency.
By processing data closer to the source and reducing the physical distance it must travel, edge computing can greatly reduce latency. The end result is higher speeds for end users, with latency measured in microseconds rather than milliseconds. Considering that even a single moment of latency or downtime can cost companies thousands of dollars, the speed advantages of edge computing cannot be overlooked.
While the proliferation of IoT edge computing devices does increase the overall attack surface for networks, it also provides some important security advantages. Traditional cloud computing architecture is inherently centralized, which makes it especially vulnerable to distributed denial of service (DDoS) attacks and power outages. Edge computing distributes processing, storage, and applications across a wide range of devices and data centres, which makes it difficult for any single disruption to take down the network.
One major concern about IoT edge computing devices is that they could be used as a point of entry for cyberattacks, allowing malware or other intrusions to infect a network from a single weak point. While this is a genuine risk, the distributed nature of edge computing architecture makes it easier to implement security protocols that can seal off compromised portions without shutting down the entire network.
Since more data is being processed on local devices rather than transmitting it back to a central data centre, edge computing also reduces the amount of data actually at risk at any one time. There’s less data to be intercepted during transit, and even if a device is compromised, it will only contain the data it has collected locally rather than the trove of data that could be exposed by a compromised server.
Even if an edge computing architecture incorporates specialized edge data centres, these often provide additional security measures to guard against crippling DDoS attacks and other cyberthreats. A quality edge data centre should offer a variety of tools clients can use to secure and monitor their networks in real time.
As companies grow, they cannot always anticipate their IT infrastructure needs, and building a dedicated data centre is an expensive proposition. In addition to the substantial up-front construction costs and ongoing maintenance, there’s also the question of tomorrow’s needs. Traditional private facilities place an artificial constraint on growth, locking companies into forecasts of their future computing needs. If business growth exceeds expectations, they may not be able to capitalize on opportunities due to insufficient computing resources.
Fortunately, the development of cloud-based technology and edge computing have made it easier than ever for businesses to scale their operations. Increasingly, computing, storage, and analytics capabilities are being bundled into devices with smaller footprints that can be situated nearer to end users. Edge systems allow companies to leverage these devices to expand their edge network’s reach and capabilities.
Expanding data collection and analysis no longer requires companies to establish centralized, private data centres, which can be expensive to build, maintain, and replace when it’s time to grow again. By combining colocation services with regional edge computing data centres, organizations can expand their edge network reach quickly and cost-effectively. The flexibility of not having to rely upon a centralized infrastructure allows them to adapt quickly to evolving markets and scale their data and computing needs more efficiently.
Edge computing offers a far less expensive route to scalability, allowing companies to expand their computing capacity through a combination of IoT devices and edge data centres. The use of processing-capable edge computing devices also eases growth costs because each new device added doesn’t impose substantial bandwidth demands on the core of a network.
The scalability of edge computing also makes it incredibly versatile. By partnering with local edge data centres, companies can easily target desirable markets without having to invest in expensive infrastructure expansion. Edge data centres allow them to service end users efficiently with little physical distance or latency. This is especially valuable for content providers looking to deliver uninterrupted streaming services. They also do not constrain companies with a heavy footprint, allowing them to nimbly shift to other markets should economic conditions change.
Edge computing also empowers IoT devices to gather unprecedented amounts of actionable data. Rather than waiting for people to log in with devices and interact with centralized cloud servers, edge computing devices are always on, always connected, and always generating data for future analysis. The unstructured information gathered by edge networks can either be processed locally to deliver quick services or delivered back to the core of the network where powerful analytics and machine learning programs will dissect it to identify trends and notable data points. Armed with this information, companies can make better decisions and meet the true needs of the market more efficiently.
By incorporating new IoT devices into their edge network architecture, companies can offer new and better services to their customers without completely overhauling their IT infrastructure. Purpose-designed devices provide an exciting range of possibilities to organizations that value innovation as a means of driving growth. It’s a huge benefit for industries looking to expand network reach into regions with limited connectivity (such as the healthcare, agricultural, and manufacturing sector).
Given the security advantages provided by edge computing, it should not come as a surprise that it offers better reliability as well. With IoT edge computing devices and edge data centres positioned closer to end users, there is less chance of a network problem in a distant location affecting local customers. Even in the event of a nearby data centre outage, IoT edge computing devices will continue to operate effectively on their own because they handle vital processing functions natively.
By processing data closer to the source and prioritizing traffic, edge computing reduces the amount of data flowing to and from the primary network, leading to lower latency and faster overall speed. Physical distance is critical to performance as well. By locating edge systems in data centres geographically closer to end users and distributing processing accordingly, companies can greatly reduce the distance data must travel before services can be delivered. These edge networks ensure a faster, seamless experience for their customers, who expect to have access to their content and applications on demand anywhere at any time.
With so many edge computing devices and edge data centres connected to the network, it becomes much more difficult for anyone failure to shut down service entirely. Data can be rerouted through multiple pathways to ensure users retain access to the products and information they need. Effectively incorporating IoT edge computing devices and edge data centres into a comprehensive edge architecture can therefore provide unparalleled reliability.
Where do you see edge computing in five years?
The firm predicted two years ago that by 2025, a whopping 75 percent of enterprise data would be generated and processed at “the edge.” Put another way, in five years, the majority of enterprise data could bypass the cloud entirely
The future of edge computing will absolutely be open. Edge will converge with the use of data through artificial intelligence and machine learning to turn insight into actions that benefit businesses and their customers. It will eventually be viewed just like any other location where applications can be placed seamlessly with consistency and without compromise.
Many technical challenges will need to be overcome before edge computing achieves mainstream adoption. Of these, which has Nutanix identified as the most critical?
One major challenge companies must overcome is managing the volume, velocity and variety of data at an industrial scale and refining it at the edge to get actionable insights, often under tight time constraints. Over the past few years, we’ve seen devices deployed at the network edge increase almost exponentially to process more data than all the public and private clouds of the world combined, leaving teams struggling to adjust to this new volume of data.
Accompanying this data influx is a fundamental shift in the computing paradigm from “human-oriented” to predominantly “machine-oriented” processing. For example, when collecting sensor data, companies will need to use AI and analytics techniques to convert raw data into business insights. This shift will require a more distributed and interconnected approach between the core and hundreds, if not thousands, of edges to make sure they work as a whole. The alternative would be impossible to manage or secure. I expect the industry will see significant progress in this area in the coming years.
What companies use Edge computing?
German Edge Cloud Main offering: Private edge cloud infrastructure (IaaS) and platforms (PaaS) for industry-specific applications, particularly in factory environments.German Edge Cloud (GEC), part of the Friedhelm Loh Group, has developed ONCITE in partnership with IoTOS. ONCITE is an industrial edge cloud appliance aimed at midsized manufacturing companies. It will enable them to obtain new insights from their production data through real-time data availability as well as supplementary network AI capabilities. GEC aims to target companies which are less likely to opt for solutions from the hyperscale cloud service providers. German Edge Cloud leverages the various assets under the Friedhelm Loh Group: Rittal (hardware), IoTOS (software solutions), iNNOVO Cloud (managed services) and Eplan (engineering).
EdgeInfra: Main offering: Micro edge-data centres co-located on site in places such as macro cell towers and other mobile network locations, or on fixed networks.Currently in pre-launch phase, EdgeInfra is looking to provide micro edge-data centres located at the extreme edge of network and mobile infrastructure in Europe. This will enable ultra-local interconnected micro eco-systems where deployed.The core factors that underpin EdgeInfra’s solutions include creating a neutral infrastructure, open ecosystems, multi-tenancy and focus to bring specialists together through partnerships.
AlefEdge: Main offering: Enabling 5G applications through open APIs at the edge for AI, AR/VR, Smart Cities, IoT, etc. via edge gateways, the edge cloud and end-applications.A leader in the Edge Internet, AlefEdge enables 5G applications through open APIs at the Edge. This creates an ‘open edge ecosystem’ that will enable businesses, developers and networks to work in a friction-free way. AlefEdge is looking to leverage the ‘world’s first Edge applications’ in Virtual and Augmented Reality, Artificial Intelligence, Industry 4.0, Smart Cities, IoT and Gaming.AlefEdge is working with telecoms operators worldwide on edge compute solutions and recently announced a live deployment of an edge area network in Massachusetts via partnerships with Packet and Federated Wireless.
ClearBlade is an edge computing software company that provides a single platform offering the ability to leverage local compute, artificial intelligence and actionable visualizations. Operating in the cloud, on-premise, and at the edge, ClearBlade’s middleware platform is designed to seamlessly connect the various parts of IoT.ClearBlade is also using blockchain and smart contract technology to track progress and provide immutable, highly visible supply chains for industrial ecosystems.