Fog Computing is exactly what helps you maintain a good, up-to-date IoT system. In this article, we are going to introduce you to the basic concept of Fog Computing. You may have heard of the term for a while and wondered what the Fog Computing are and what their Applications are. Let me draw your attention to the fact that in the world of Internet of Things every device or system produces data. Devices generate a variety of data.
In the Internet world, all information is digital, and all information is in protocols such as IP. In the path of data transfer from IoT sensors to cloud there are different switches, routers, servers and different sections that all interact with each other under the same protocol for transmitting IoT data. Many devices in the world today use the Internet of Things. Imagine this amount of information going to the cloud and having to do something special for each event that the sensors recorded. Rest assured, the capacity of data centers around the world will not be responsive to this volume of information.
What solution do you suggest. Let me help you. What do you think about the categorization of data sent to data centers? In this category we can divide the data by response time. For example, data that needs to be processed quickly and that operations are executed quickly. The next bunch of information is not very sensitive to their reaction time and can wait a while. And the third category of information that can be analyzed and processed at the appropriate time.
Suitable infrastructure for Fog computing
Investing in IoT requires a new kind of infrastructure. The designers of the model did not design the model for data volume, variety and speed. Many devices that were not previously connected to the Internet now produce more data per day. Transferring all generated data to the cloud requires a lot of bandwidth to perform the analysis process.
Some objects include devices that use industrial protocols to connect to the Controller. So we need to convert them to IP before sending the data to a cloud for analysis or storage. IoT devices are constantly generating data, and we need to respond quickly to the cloud. When the temperature in a chemical tank rapidly approaches a predetermined rate, you should take corrective action immediately. Therefore, the possibility of crashing when reading temperature and transferring data from Edge to Cloud is eliminated.
Controlling the volume, variety, and speed of IoT data requires a new computing model whose core requirements include:
Timing is important when fixing a production line or restoring some services. Analyzing data near the equipment that produced the data can prevent disaster in these systems.
Network Bandwidth Protection:
Much data is generated by the IoT in various sectors. This data is sent to the cloud for processing and storage. Transferring this amount of data requires a lot of bandwidth. So we need a system that can analyze data at the data generating site, and only send certain data to the cloud.
IoT data must be protected during the transfer process. This requires automatic monitoring and response throughout the entire attack chain, before, during, and after the attack.
We use data from the IoT to make decisions that affect the safety of citizens and important infrastructure. So we can’t ignore the infrastructure and data availability.
Collects and protects data from a wide geographic range with varying environmental conditions:
IOT usually obtain data at different distances and in different environmental conditions. Protecting this data at the time of transfer requires a great deal of cost. We cannot protect this data in environments such as railroads, roads, service stations, and vehicles. Data processing and storage is the best way to protect your data.
Cloud computing architecture or traditional cloud computing cannot meet all the above requirements. The general approach of this type of computing is to transfer all data from the edge of the network to the Data Center for processing. In addition, traffic to equipment is much more than bandwidth capacity. Industry regulations and privacy concerns prevent offsite storage for certain types of data. Cloud servers are only IP-related and not associated with many other protocols used by IoT devices.
So it’s a good place for analyzing and analyzing most IoT data near the equipment they produce and operate on, this process is called Fog Computing.
What is Fog Computing?
Any device that can perform network storage, data storage and computing is called a node. Cloud deployment is provided alongside the device and can generate and process data. These devices include controllers, switches, routers, isolated servers and CCTVs.
According to IDC estimates, the volume of data analyzed in devices that are physically close to IoT is about 40 percent. Therefore, analyzing IoT data near objects reduces latency and this is very important. The technology transfers several gigabytes of traffic from the main network and holds sensitive data inside the network.
Types of Fog Computing related applications
Fog applications are as diverse as IoT, including monitoring, analyzing real-time data on networked objects, and then starting an activity. Examples may include machine-to-machine communication or M2M and human-machine interaction or HMI. Such as locking the door, changing equipment settings, using brakes on the train, zooming in on the camera, opening the valve when pressed, drawing a bar chart or sending a technician alert for precautions.
Fogging plans are rapidly expanding in the sectors of production, oil and gas, utilities, transportation, mining and the public sector. Collects data at the edge of the network: vehicles, ships, factory level, roads, railways and more. Thousands or millions of objects produce data across vast geographic regions. The analysis as well as the data activity should take less than one second.
How Fog Computing Works
Developers write and deliver IoT applications for Fog Nodes on the edge of the network. Fog nodes located nearest to the edge of the network receive data from IoT devices. We then direct various types of data to the appropriate location for analysis.
Analyzes time-sensitive data in fog nodes near objects. For example, the most important issue in Cisco’s intelligent distribution network is ensuring that the control and protection loops are functioning properly. Therefore, fog nodes near Grid sensors can detect problematic signals and prevent problems by sending control commands to drivers.
It sends data that can wait several seconds or minutes for an Action to be analyzed and run at an Aggregation Node or Aggregation Point. In the case of the Smart Grid, each of the substations may have its own Aggregation Node that reports the operational status of each of the side or side feeders.
Sends less sensitive data to the cloud for historical analysis, mass data analysis, and long-term storage. For example, any one of the thousands or hundreds of thousands of May nodes can send periodic summaries of network data to the cloud for time analysis and storage.
Checking Fog Computing and Cloud Computing Processes:
- Receives feeds from IoT equipment using any protocol in real-time.
- Runs IoT enabled applications for real-time analysis and control with a response time of milliseconds.
- Provides temporary storage, often for 1 to 2 hours.
- Sends a periodic summary of data to the Cloud.
- Collect and retrieve data summaries from a large number of Fog Nodes.
- Performs analysis on IoT data and data from other sources.
- Based on this information, it can send new application rules to Fog Nodes.
Benefits of Fog Computing
This technology performs data processing and storage operations next to objects and, if needed, performs activities in the same environment. So it is practically useful for the following reasons:
More business agility:
Developers with the right tools can quickly develop and deploy Fog applications when needed. Car manufacturers offer MaaS to their customers. Fog applications can customize the device to suit each customer’s needs.
In the process of protecting the Fug nodes, it uses the same control methods and policies and practices used in other IT sectors, and uses similar solutions to provide physical and cyber security.
More detailed information with privacy control:
The IT team has better control over data collection, analysis, and storage equipment and sends only certain data to the cloud.
Reduce Operating Costs:
Processes data locally and does not send it to the cloud. As a result, it does not waste network bandwidth to transmit data that can be processed on site and reduces the cost of the organization.
Fog Computing manages IoT data in the cloud on a daily basis. The challenges of expanding large volumes of data solves the variety and speed of data processing near objects. Accelerates information acquisition and response to events. Reduces bandwidth cost and protects sensitive data by analyzing IoT data alongside objects. Ultimately, organizations that use Fog Computing will get faster information, increase agility in business, improve service levels, and improve security.