Edge Computing is one of the most widely used technologies in the industry of automation nowadays. It transforms the way in which data is generated by IoT and other electronic devices is stored, processed, analyzed, and transferred. It is a form of computing that is done on-site or near a particular data source, by minimizing the need for data to be processed in a remote data center. It is already used in devices that we use on daily basis like the wearable on our wrist, safety monitoring of oil rigs, streaming video optimization, crop management by drones, smart utility grid analysis, and many more places. In this article we will answer the question of edge computing is an extension of which technology? and we will also be discussing more about edge computing and its uses and benefits.
What exactly is edge computing?
Edge Computing is an extension of cloud computing, which answers the question “edge computing is an extension of which technology?” but do not confuse it as an alternative to cloud computing. The infrastructure of edge computing can integrate with central cloud data centers to deliver a performance level that would not be possible using cloud computing alone.
It is basically a part of a distributed computing topology in which information processing is located close to where people produce or consume that information. Rather than relying on a central location that may be located thousands of miles away from the devices, it brings computation and data storage closer to the devices. One of the early goals of edge computing was to reduce the bandwidth costs that were associated with the moving of raw data from where it was created to either a cloud or a data center.
Recently, due to the rise of real-time apps that require minimal latency are making the use of edge computing and driving the concept to improve further. Edge computing also helps companies to save money by having the processing done locally, which significantly reduces the amount of data that is needed to be sent to a centralized or cloud-based location.
The Working of Edge Computing
The motto of Edge computing is if you can’t get the data closer to the data center, get the data center closer to the data. Edge computing helps by offering a local alternative in which machine data is collected, stored, and analyzed at the source. This helps in making the data available in real time and available for immediate use. These features of Edge Computing help in making the apps have more responsive processing of data and make the operations smoother. Due to these features IT architecture can be decentralized with mobile computing and the IoT, businesses can gain approximately real-time insights with less latency and lower cloud server bandwidth demands.
Benefits of Edge Computing
Edge computing helps in finding the solution to various issues such as bandwidth limitations, excess latency, and network congestion. One of the main benefits of edge computing is the ability to process and store data faster, which in terms increases the efficiency of real-time applications. It provides advantages in security systems, health monitoring and wearable devices.
It helps in the areas where connectivity is unreliable or bandwidth is restricted. In these areas, it can help by doing the computing work on the site itself or on the edge device itself, by doing the processing locally the amount of data that is needed to be sent can be vastly reduced, which in terms reduces the amount of bandwidth or connectivity time that might otherwise be necessary.
Edge computing helps in ensuring data security by encrypting the data traversing the network back to the cloud or data center and the deployment itself can be hardened against hackers and other malicious activities.
Uses of Edge Computing
Since Edge Computing provides money conservation and low latency, the number of uses of Edge Computing keeps on increasing day by day. Entertainment, business, content delivery systems, and smart technology, 5G, or predictive maintenance all of these incorporate some form of edge computing technology. There are platforms that let their users to stream music and videos and use cache information to lower the latency which can help in offering more network flexibility to control user traffic demands.
Since Edge Computing enables to closely monitor equipment, production lines, and operations, that is why it is used by companies and manufacturers to detect any failures and help them in reducing the chances of having costly delays due to downtime. It is also used in health care to look for patients so that doctors can get a more real-time insight into their patient’s health without the use of any third-party database.
Some more use cases of Edge Computing are listed below:
- Farming: Indoor farming can use sensors which can help them track water, nutrient density, and determine optimal harvest.
- Optimization of Network: By measuring performance for users across the internet through which it can determine the most-reliable and low-latency path for a user’s traffic.
- Safety: It can analyze data from CCTV, and various other sensors which can help monitor the safety of any place.
- Transportation: Autonomous Vehicles require and produce a very large amount of data and process it, this can be simplified using edge computing rather than a centralized computing.
- Retail Businesses: Surveillance. Stock trading, sales data, and many other real-time business details can produce very large amounts of data. Edge Computing can help analyze and process this data effectively. It can also help in local processing in local stores.
Difficulties faced by Edge Computing
There is no technology that doesn’t have flaws. Even though edge computing has a great amount of uses and benefits, it still has some flaws. First, the main problem would be network limitation, even though edge computing overcome typical network limitations, it still needs some minimum level of connectivity to work. Therefore, it is essential to consider poor and unreliable connectivity when designing an Edge Computing concept.
Edge Computing can also be accused of security and privacy concerns. Since the data is being used by edge and being handled by different devices it might not be as secure as a centralized or cloud-based system. The users of IoT are growing day by day so the IT industry will have to consider the security risks and use techniques to secure the user’s data such as encrypting data, employing access-control methods, VPN tunnelling, software patching, and updates.
The problem with very large amounts of data is also a problem for edge computing. Consider health care devices they only need data that is critical and there’s very little point in keeping the data of normal days of a normal patient. The data that is collected during the real-time analysis is short-term data and is not needed to be kept over the long term unless it is necessary (in cases of research).
This article gave the answer to “edge computing is an extension of which technology?” We also discussed what is edge computing and what are the benefits that it provides in day-to-day life as well as to Businesses. We have also discussed the limitations of Edge Computing. Hope you liked the article.
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