In this data-driven world, people are connected globally using millions of IoT devices. Huge amounts of data were being processed and handled by cloud computing until now. However, the explosive amount of data and interconnected devices have caused the cloud to reach its maximum potential. As a result, industries using cloud technology are facing latency and bandwidth problems.
These limitations can cost businesses a fortune, especially the ones that require fast data processing. For example, in financial services, traders need to make quick decisions in real-time and any lag in data computation can cause enormous loss of money.
Edge computing aims to address these costs of bandwidth and latency for data traveling long distances. Rapidly growing 5G wireless technology is fueling the growth of edge computing systems. According to Gartner, by 2025, 75% of enterprise-generated data will be created and processed by edge computing.
According to Gartner, edge computing is “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information”.
In simple words, edge computing allows data to be processed where it is created, that is, at the “edge”. The word “edge” literally refers to geographical distribution. The computing is done near the data source. This can be within the device or close to the device. It does not require centralization like cloud processing.
The biggest advantage of edge computing is that it prevents latency issues that can affect an application’s performance. This also allows companies to save money by having the data processed locally instead of a cloud-based centralized location.
The biggest tech giants including Amazon, Google, and Microsoft are exploring edge computing. This indicates the rise of the next big computing race.
This nascent technology already has quite a few benefits to offer:
Faster data processing and analysis in real-time: Since data is processed within or close to the device instead of traveling to an external data center, lag time is reduced.
Low costs: Companies have to spend less on local data management solutions as compared to cloud networks.
Less network traffic: The ever-increasing number of IoT devices are generating data at overwhelming rates, leading to a bottleneck of data in the cloud. Edge computing remedies this problem.
Increased application performance: The lower latency rates achieved with the help of edge computing can result in applications operating efficiently.
Despite the benefits offered and cloud problems solved by edge computing, it raises concerns for privacy and security. Data on the edge can create security problems, especially when being processed by different devices. In this respect, cloud-based computing is much more secure to the centralized location of data.
The growing number of IoT devices is alarming IT professionals about potential security risks. This necessitates data encryption and the utilization of correct access-control methods and VPN tunneling.
In addition, the varying demands of power, network connectivity, and electricity of different devices impact the reliability of edge devices.
My name is Chirag Panikar. I am a newbie blogger, here to give you guys some tips and tricks which will ease your life surrounded by tech. Two things I love are GYM and gaming. Finding new things to learn every day that’s the whole point.????