The need to improve upon cloud computing, in trying to manage large chunks of data in real-time saw the emergence of fog computing.
As per one of the market analysis reports, fog computing’s market will see a huge expansion of up to $700 million.
This is a clear indication of the fact that fog computing has been extremely beneficial. And its advantages range across verticals like automotive, healthcare, retail, and energy.
Let’s Look at Various Advantages of Fog Computing Across Different Sectors:
IoT is fast changing the way the retail stores are operating. Here in fog computing has been particularly helpful in managing the ever-expanding virtual data.
The earlier database was mostly taken care of by on-site technology but now with a lot of handy devices like mobiles and tablets in use, retailers see cloud as the best option to manage their data.
A lot of these edge devices will require connectivity good between them. And this shall be taken care of by the scalability and flexibility aspects of fog computing.
Fog computing can really amp the computation efforts that are needed for a self-driving car.
What fog computing does, is that it reduces the computational load on central servers instead uses nearby servers or smart devices.
Self-driving vehicles communicate via two modes; vehicle-to-vehicle or with another network.
When the roads are jammed up with vehicles then these self-driving vehicles can easily communicate the data (road-driving related metric) with one another.
In case there are largely empty roads, then a nearby network center would be the ideal way to go about communicating.
Fog computing would be helpful in reaping all this computational ability from different vehicles. More vehicles would mean more computational power.
A lot of patient-general health data gets accumulated from IoT devices like wearables, glucose, and blood pressure monitors, and more such devices.
The problem lies in the integrity of this vast data. All this data is then stored in the cloud, which can be time-taking to obtain on some urgent occasions, in particular.
Now with the help of fog computing, all the critical analyses can be done directly at the device itself. So, removing one intermediate layer will improve the speed of operations.
With edge computing, all the complexities of healthcare data can be taken care of. Be it, attaining smart data in quick time, ability to operate over a large geography, and privacy of patient data.
Ensuring that various operational data is monitored in different plants over large distances can be a headache with a simple cloud solution alone.
It is estimated that with every 60 miles of distance from a cloud server, latency will increase by one millisecond.
This is of major concern for plants operating at a great distance. So how fog computing will bring down this time, is by sharing the load of data with IoT devices instead of a centralized cloud server.
Anything that needs immediate attention in regards to the smooth operation of the plant, will be easily communicated via such devices making the use of fog computing.
An organization could surely cut down on the risk when a sensor is alerting with some hazardous situation.
Improved decision making, faster deliverance of data, and maintaining consistency in relayed data, you name it and fog computing has got your back.
I’m pretty sure that organizations across so many more verticals (other than the above ones) will be using fog computing and taking all the advantages of it.
I just chose to focus on these many sectors since the intention was to highlight how it operates and proves beneficial.