How to deploy edge computing and fog computing in

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How the industrial IOT deploys edge computing and fog computing

the industrial IOT (iiot) application usually needs scalability and flexibility. It may not need to choose between fog computing and edge computing, because both enterprises may need it

with the rise of industrial Internet of things (iiot), people are introducing new technologies to process a large amount of data being generated every day. Identifying these new technologies is a challenge for enterprises and industrial companies. For example, the terms edge computing and fog computing are often used interchangeably because they both involve pushing intelligence and processing power closer to their origins. Although there are clear differences between how and why to deploy which type of infrastructure, both are critical to a successful industrial IOT strategy

in order to cope with the future of the industrial IOT, it is very necessary to adopt next-generation solutions, including computing when the edge needs to be restarted or reset parameters and fog computing, in order to expand future connectivity devices, networks and applications. Here are the details of how enterprises can better distinguish between edge computing and fog computing, and how to deploy them

difference between edge computing and fog computing

in short, edge computing is an infrastructure that can collect, analyze and store data on site in production facilities (equipment), thus saving time and helping maintain operations, rather than relying on slower systems that store all data in the cloud. Edge computing has had a significant impact on maintaining normal operation and providing near real-time data and analysis to optimize the performance of industrial IOT and the future of industrial automation. Although some departments are still adapting and adjusting to the edge, the next wave of data communication between devices and networks is coming: fog computing

fog computing is a form of cloud computing closer to the edge, so it can process a large amount of data without pushing the data to the cloud. By processing the real-time IOT requests between the edge and the data center cloud, fog computing will improve the edge capability. Although these expected benefits make fog computing seem wise for companies that want to use industrial IOT to expand their networks, it is important to consider whether fog computing is required at all levels of operation. When should you implement fog calculation? In addition to the current industrial automation and edge network, fog computing will become an integral part of large-scale connected systems and share data among thousands or millions of connected devices

for companies with more isolated and personalized infrastructure, atomization deployment may not be necessary. This level of integration may take several years, but understanding and implementing edge computing and fog computing is very important for a successful industrial IOT strategy

deployment for the industrial IOT: where to start

understanding the different applications and expandability of edge computing and fog computing, and matching different fixtures can test different test performance, making it easier to determine which is most suitable for your environment. This is especially true because both options are equipped with the next generation industrial IOT (iiot) function and are an important step in preparing for future large-scale integration. In the industrial environment, edge computing plays an important role in the selection of the horizontal tensile testing machine of Jinan new era Testing Instrument Co., Ltd., including 7 items: experiment, display, protection, storage, accounting, host computer and special machine, so as to meet the data and analysis needs of multiple facilities in the system. However, for the industry preparing for large-scale expansion, fog computing may be a better choice to achieve long-term growth and success

applying edge computing can be the next step towards industrial IOT integration, which will prepare for the future of automation. The need to optimize efficiency, productivity and quality if not cleaned up in time has prompted manufacturers to move their intelligence to the edge of the network to process data faster and cope with competitive pressures. This system is valuable for facilities with many outposts, such as hundreds of oil drilling platforms, which are connected to a central data center. Installing edge servers on oil drilling platforms enables them to share data faster and process data closer to the network edge, rather than sending data to the cloud for processing, because if the data is sent to the cloud for processing, it may delay system performance or abnormal alarms

beyond closed networks and systems, we will begin to see that fog computing can realize more future connected devices and embrace the potential of industrial IOT. Fog computing is closer to the edge, which means that it can process real-time IOT processing requests faster and reduce the delay of sharing data between networks. Beyond the industrial network, fog computing can help different industries and departments expand to connect thousands or millions of edge devices

an example is the development of driverless cars. Fog computing along the intelligent network will allow driverless cars to communicate instantly on the highway, and deal with computing needs in real time to improve speed, efficiency and safety when crossing busy intersections. With the development of driverless automobile industry and the emergence of mainstream applications, fog computing is very important for sharing data among thousands of vehicles

next generation edge architecture

what will the network composed of millions of edge computing and fog computing supported devices look like? Although the future city is still unimaginable, now laying the foundation is the best way to prepare for further automation and expansion of networks. These networks will cover longer distances, but the communication speed is faster. Fog will fill the gap between the edges and realize instant communication between device networks in the ecosystem. This new level of coordination will be necessary for future infrastructure, which will connect intelligent devices such as traffic lights, pedestrian crossings and driverless cars

smart cities cover more than equipment. They will connect utilities such as power and water to save energy use and manage water distribution, and control energy demand during peak hours of the day. Fog is the connection between all these systems to communicate their needs and coordinate these unrelated devices and networks to analyze appropriate operations. By now preparing for the next generation of edge architectures, industries and cities can analyze and accept the potential of fog computing. With the enhancement of industrial IOT functions, more networks will be connected and expanded to meet our daily needs, so as to create more intelligent homes, buildings and urban networks

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