Edge Computing

Updated: Dec 21, 2021

Edge computing is about bringing devices and their computing as close to the source of data as possible; essentially, on the “edge”. Edge computing will put fewer responsibilities on the cloud, which is held in large data centers that can be thousands of miles away. By moving as much data as possible to locally-based servers, there will be less latency that could affect the performance of applications. Edge computing will allow data, especially data delivered right after collection, to be computed, stored, and used faster while still being processed in a centralized manner like the cloud. This will even lead companies to save money as edge computing reduces the amount of data stored in centralized cloud centers.

Edge computing has mainly formed due to the rising of IoT devices. IoT devices need the internet to receive and deliver information, and with the number of people and devices constantly expanding, more data will generate in increasing amounts during operations. Transmitting data across one machine isn’t so complicated, but the role of edge computing becomes essential when there are many devices transmitting data simultaneously. Imagine multiple devices sending footage, images, and information to and from a centralized cloud. When this number multiplies by hundreds or thousands, latency becomes an extreme factor along with the cost of bandwidth. When you bring in edge computing, you can solve this dilemma by having local processing and storage centers.

For many reasons, edge computing will be a large part of the future. With technology expanding, we need specific data types and computations to be stored and processed at rapid rates. A great example of this is if we ever turn to self-driving cars. For this to be possible, a vehicle would need to have several sensors. These would all collect data that would need to be processed and stored at a much faster rate than would be able to be done by sending it back and forth from the cloud. Edge computing solves this problem. Another way edge computing has begun to evolve is through system modules that have AI functions integrated into them. At NVIDIA, they have engineered a module more diminutive than the size of a credit card that can be built into drones, robots, and other devices. These AI algorithms are complicated and require immense processing power that usually runs using cloud services. Switching this to edge computing would allow for significantly faster responses and instantaneous computing.

So, what are the concerns with edge computing? It saves you money by minimizing bandwidth costs and use of cloud resources, brings a significant improvement on latency, and offers new functionalities like analyzing data in real-time. However, a concerning factor is what this might mean for our privacy. With edge servers being added, there will be new ways for malicious people to compromise our devices, and edge data may not be as secure as it would be in a centralized cloud system. Also, companies will have new ways to control what we do. Through edge computing, devices in homes will be run by companies like Google, Amazon, Microsoft, and Apple. People will not be worrying about the functionalities or capabilities of the software installed. Big companies will be able to decide how much control they will have over the lives of people who use their products and will also be able to incorporate new additions continually. In the end, edge computing is a powerful tool that will shape the future of technology alongside cloud computing.

Written by Mariah

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