It is estimated that by 2025, almost 42 billion IoT devices will be connected to the Web around the world. They will produce nearly 80 ZB of data. In this way, IoT infrastructures will be responsible for generating 50% of global data.
The Entry of Edge
Previously, cloud computing was used to store and process IoT-based data. Soon, there was a growing consensus that data should be computed near the data generation sources. Edge computing was thrown in the mix to adhere to this new approach. It outpaced the traditional cloud computing model in numerous aspects.
So far, it is apparent that edge computing has what it takes to handle several IoT-related challenges. For instance, when a cloud is used with an IoT environment, it can cause latency problems. However, with edge computing, all the data processing is local, which takes out latency issues from the equation.
Perhaps the most significant benefit of edge computing is the speed it brings to the table. Most IoT environments require the real-time, quick output to help with data processing, such as in autonomous cars. To make sure that self-driving cars stay out of danger while driving on the roads, they must record and compute voluminous amounts of data. This can include determining the rules of lanes, identifying pedestrians, and making a stop at a red light. In all of these circumstances, the car must compute massive amounts of data in just milliseconds. Thus, speed is not merely an option; it is a necessity on which the whole working of the car relies on.
It is not feasible to go for cloud servers to compute this data in a brief period. In the cloud, the data must be uploaded on the server so that it can be calculated. Subsequently, after a waiting period, results are provided. While the cloud itself is speedy, it is not blazingly fast enough like edge computing to handle real-time dangers where you have an extremely narrow margin of error.
In industrial IoT, you have to deal with cases in which it is essential to control devices without depending on proper network bandwidth. This negates the likelihood of adding a cloud to the mix. Hence, edge computing is the only viable solution for such scenarios.
Another reason why the edge is gaining importance is reduced costs. Enterprises are looking to transfer critical computing aspects like processing and storage nearer to the application. This can boost up the reliability of collected data and makes sure that information which switches between firewall, servers, and routers do not get lost like before.
Final Thoughts
Edge computing has replaced cloud in various use cases and improved the capabilities of IoT devices. However, the cloud is still a crucial part of the system. Businesses can use both edge and cloud and come up with the perfect balance to decide how they will split up their processing operations.