Fog Computing ,is making Distributed Processing and analysis of data in Edge Devices rapid and with bandwidth conservation. Read to know more
Fog computing is growing at an exponential rate in the current times. A recent report from Valuates Reports states that the global Fog Computing market size is projected to reach USD 539.8 Million by 2026, from USD 40 Million in 2019, at a CAGR of 44.3% during the forecast period 2021-2026. With such extended heights in the growth statistics, fog computing is soaring high in the tech and specifically, IoT arena for filling in the increasing demand for low latency and high throughput applications. As the applications of IoT increase, so does the market size of fog computing. Being able to process the data at a great speed at low latency and high throughput is something that fog computing is great at, and products like self-driving cars and vehicles only boost the demand of this arena with their expansion and adoption.
The Internet of Things is generating a high volume of data with every passing minute, and the data generated varies in nature too. This data needs to be processed quickly so that it can be acted upon when there is a need.It is important to process the data and traffic from multiple devices without outstripping the bandwidth capacity and following a traditional approach with cloud computing only adds latency. Hence, fog computing is the go-to solution for industry players that are looking for a robust, decentralized computing infrastructure.
But what exactly is fog computing?
Well, in simple terms, fog computing is a computing infrastructure that is located between the devices that produce the data and the cloud, making it a decentralized infrastructure that is flexible enough to segment bandwidth traffic to analyze data at the edge.
Many times people think of fog computing as a replacement for cloud computing, but in reality, fog computing only brings the power of the cloud closer to the source of data, which helps in processing it rather rapidly.
What is fog?
Fog is generally something that resembles cloud, but closer to the ground. Similarly, in fog computing, there is concentration on the edge of the network, enabling analytics at the edge and allowing the cloud to take care of resource-intensive analytics that are rather useful in the longer term.
Benefits of fog computing
- Conserving Network Bandwidth – As known, data processing can take time and resources, which means often there is transportation of data from edge devices to cloud and back again. This is not really necessary, because not all analysis require cloud-intensive processing. And fog computing can help with conserving the bandwidth and analysing data at the edge without having to transport it to the cloud.
- Reduction in Latency – Now that the data doesn’t need to be transported to the cloud for processing, computing can be performed at a place that is closer to the source of the data generated, leading to reduction in latency.
- Improvements in Security – In fog computing, the data is processed locally, only specific parts of the data are moved to the cloud, and since there is no movement of data around, sensitive data is more secure and protected.
- Enhanced agility in business processes – As the customers are provided with the resources that they need whenever there is a demand, businesses can offer customer-centric solutions and services by acting upon the immediate needs.
Fog computing vs edge computing
Often fog computing and edge computing are used interchangeably because both these technologies are aimed at processing data quickly and closer to the data source with intelligence. But the main differentiating point between fog computing and edge computing is the place of compute power and the standard of the process.
Fog computing performs the process of analysis within a fog node – the LAN hardware and edge computing happens at the place where the sensors are attached to the devices.
Fog computing shows great potential in the present as well as the near future. The specific and effective characteristics of fog computing are ideal for IoT applications and other arenas as well. The ultimate goal of fog computing is to be able to analyse data within milliseconds and deliver it to the users, so that it can be acted upon, making it one of the most desirable technologies in the modern world!
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