What is edge computing and what is the value of edge computing?

Edge computing is a distributed computing model that places compute and data storage in edge devices close to the source of the data, rather than processing them in remote data centers or cloud servers.

Edge computing aims to address the latency and bandwidth constraints found in traditional computing models, especially when real-time response or large-scale data processing is required. With local computing on edge devices, you can reduce the time and cost of data traveling through the network and improve the responsiveness and performance of your applications.

Another advantage of edge computing is that it can improve data privacy and security. Because data doesn't have to travel through cloud servers or other remote data centers, data on edge devices can better protect privacy and reduce the risk of data breaches.

Edge computing refers to an open platform that integrates the core capabilities of network, computing, storage, and application at the edge of the network near the source of things or data, and provides edge intelligence services nearby to meet the key needs of industry digitalization in terms of agile connection, real-time business, data optimization, application intelligence, security, and privacy protection.

Edge computing refers to the processing and analysis of data at the edge of the network. Here, we give the definition of an edge node, which refers to any node with computing resources and network resources between the data generation source and the cloud center.

For example, the mobile phone is the edge node between the person and the cloud center, and the gateway is the edge node between the smart home and the cloud center. In an ideal environment, edge computing refers to analyzing and processing data close to the source of data generation, without data flow, thereby reducing network traffic and response time.

Advantages of edge computing.

In the field of face recognition, the response time has been reduced from 900ms to 169ms.

After offloading some computing tasks from the cloud to the edge, the energy consumption of the entire system can be reduced by 30%-40%, and the time for data integration and migration can be reduced by 20 times.

Edge computing is a distributed computing model that brings computer data storage closer to where it is needed. Computations are performed primarily or entirely on distributed device nodes. Edge computing will facilitate applications, data, and computing power closer to users, rather than to centralized points.

Edge computing targets applications or general functions that require a source of action that is closer to the interaction of distributed system technology with the physical world.

Edge computing is a distributed computing model that moves computing and data processing from a server to an edge device closer to the data source. Edge devices can be smartphones, sensors, IoT devices, robots, etc. Edge computing can provide many values for many applications, including:

Faster response times: Edge Meter Computing moves data processing from the server to a device closer to the data source, so data can be processed and requests responded to more quickly. This is important for applications that require real-time responses, such as autonomous vehicles, industrial automation, and more.

Reduced network latency: Traditional cloud computing models require data to be sent from the device to a cloud server for processing, and then the results are returned to the device. This can lead to network latency and high data transfer costs.

The edge residual virtual bond calculation can process data locally on the device, reducing data transmission and network latency.

Better data privacy and security: Edge computing can store and process data locally on the device instead of uploading it to a server. This improves data privacy and security, and reduces the risk of data breaches and being hacked.

Higher reliability: Edge computing can process data locally on the device and continue to process data even if the network connection is interrupted. This increases the reliability of the system and ensures that there will be no failures during mission-critical tasks.

Reduce costs: Edge computing can reduce the dependence on ** servers and reduce data transmission and storage costs. In addition, it can leverage the idle resources of edge devices for computing, reducing hardware costs.

In conclusion, edge computing can provide many values to many applications, including faster response times, lower network latency, better data privacy and security, higher reliability, and lower costs.

Edge computing is an emerging field with the following advantages.

2) Lower costs: Enterprises spend less on data management solutions for on-premise devices than on cloud and crash data center networks.

3) Less network traffic: As the number of old connected devices increases, data increases at a record rate. As a result, network bandwidth has become more limited, overwhelming the cloud and creating greater data bottlenecks.

4) Higher application efficiency: As lag decreases, applications are able to run faster and more efficiently.

5) Weakening the role of the cloud also reduces the likelihood of a single point of failure.

Mobile Edge Computing (MEC) technology also changes the state of separation of network and service in the mobile Internet, sinks the service platform to the edge of the network, provides business computing and data caching capabilities for business terminals nearby, and realizes the key leap of the network from the access channel to the information service empowerment platform, which is the representative capability of the development of the new generation of mobile Internet. The core functions of MEC include application and content ingestion pipeline, dynamic service chain functions, and control plane auxiliary functions.

If you compare cloud computing to the brain of the entire computer intelligence system. Then the edge margin calculation is the eyes, ears, hands and feet of this system. The core server makes the intelligent system have a strong artificial intelligence, but if this artificial intelligence is deaf and blind, it will not play much role.

One of the pain points often faced in big data DU applications is that the appropriate data is not collected. Edge computing can provide the most accurate and timely data for the big data algorithm of the core server.

The combination of edge computing and cloud computing makes the entire intelligent system not only clear-headed, but also deaf and agile. The computer system, which relies entirely on cloud computing, is like an army that has to consult the headquarters for every thing, and when it needs to interact with the outside world a lot, it will appear rigid and slow to respond, and if there is a problem with the network, it will completely stop cooking.

I think the value of edge computing is to serve the center computing, which allows us to more accurately calculate the value of the center, without these edge edge computing, then the value of the center we get is also biased.

Alleviate the pressure on network broadband and the requirements of back-end structuring on servers. Improve the landing efficiency and replication speed of intelligent scenes; Rapid AI empowerment of existing terminal equipment improves massive data processing capabilities. Effectively manage the data flow from the device to the cloud to reduce the risk of user privacy leakage. It can be widely used in smart security, smart medical care, smart transportation, and smart community.

Intelligent manufacturing, industrial IoT and other fields.

Up to 24T computing power.

Complete the AI upgrade of equipment with low investment, and with the smart city in the intelligent era.

Construction, 5G, Internet, Internet of Things, Internet of Things, and smart construction environment, do not need to rely on cloud computing.

Edge computing will usher in a new market blue ocean.

Hongqiao Technology uses IoT technology to create a comprehensive service system for the operation and management of the urban Internet of Things with the Internet of Everything, information sharing, and intelligent control and management. The system can cooperate with Hongqiao Smart Cloud Box to connect with various intelligent hardware to form a unified management specification and manage and operate IoT sensing devices within the city.

The core of edge computing is to provide computing, storage and other infrastructure close to data sources or users, and provide cloud services and IT environment services for edge applications. At the same time, it also supports the embodiment of specific network technologies such as low latency and high density of IoT technology, and has the characteristics of strong scenario customization. Compared with centralized cloud computing, edge computing not only solves the problems of long latency and excessive aggregate traffic, but also provides better support for real-time and bandwidth-intensive services.

Edge computing has many advantages, one is that it is closer to the data source, can quickly process data, and make real-time judgments; Second, it is more secure and can prevent data leakage; The third is to reduce bandwidth costs, because it supports local processing, and local offloading of large wandering services can reduce the backhaul pressure and effectively reduce costs.

Valuable real-time insights can be gained for competitive advantage, and the biggest advantage of edge computing is that it dramatically reduces the latency of analytics processing, while generating buzz about the technology.

Edge application services reduce the amount of data that must be moved, the amount of traffic that comes with it, and the amount of distance that must be traveled. This provides lower latency and reduces transmission costs. Computational offloading of real-time applications has been demonstrated in early test tests. Bi Demo.

Its advantages are to reduce the number of masks, reduce the delay, increase the number of segments and strengthen security. Reduce the strain from the network. Faster processing and analysis of data, without high operating costs and with less network traffic, are all valuable and advantageous.

The seemingly "remote" edge computing is not actually "edge", and Brother Li is of great significance. Edge computing is somewhat similar to cloud computing, both of which are computationally run ways that process big data. But the difference is that this time, the data no longer needs to be transmitted to the distant cloud to the end, and it can be solved on the edge side.

I think the main thing should be that on the one hand, it should be very secure in terms of the integrity of the Ancha Sparrow, and in terms of cost, it will also reduce the cost of cherry blossoms, and in addition, for the development of other industries, it should be able to provide support.

Edge computing refers to processing that occurs at or near the "edge" of the network where Internet of Things (IoT) data is negotiated or collected. A combination of edge computing and edge analysis, including artificial intelligence and machine learning.

Power computing refers to the side close to the source of things or data, using network computing, storing and applying the core capabilities of the overhead platform, spending the least cost, the fastest to get the required information, and improving production efficiency.

Data is often sent to the cloud, processed and calculated, and then relayed meaningful information back to the terminal.

It is necessary to pay attention to applications that are sensitive to the core performance of edge computing, which is "high efficiency and low latency". The first is the Internet of Vehicles in the field of automatic driving, the requirements of the Internet of Vehicles for data processing are more special, one is low latency, in the process of high-speed vehicle movement, to achieve the collision warning function, the communication delay should be within a few ms; The second is high reliability, due to the requirements of safe driving, compared with ordinary communication, the Internet of vehicles needs higher reliability. At the same time, since the vehicle is moving at high speed, the signal needs to be able to support high-speed movement on the basis of achieving high reliability.

In this case, edge computing scenarios are actually needed. Secondly, there are some industrial control scenarios, which require low latency. In addition, there are also ** live broadcast scenarios, such as 5G cloud VR AR, which broadcasts sports events or concerts live.

Mobile edge computing can greatly reduce latency, eliminate dizziness, and improve user experience through real-time processing of information.

Hongqiao Smart "Cloud Box" has powerful computing power, which can build the edge computing capability of smart light poles. Smart light poles with edge computing can be understood as special "robots" that can be found in all corners of the city. The smart light pole has the ability to execute the linkage strategy of the smart device, and the sensing device and the execution device can be linked by themselves to automatically execute the linkage strategy. Hongqiao smart "cloud box" also has the best recognition ability, and the smart light pole is an agile monitoring robot to solve the problem of unstructured data analysis efficiency and resource bottleneck.

Application scenarios of edge computing. 1Improve medical device performance and data management. Second, real-time data analysis of local retail.

Third, make virtual reality more vivid, fourth, accelerate data analysis, fifth, intelligent manufacturing, sixth, eliminate excess data, seventh, make the security system respond faster. Eighth, realistic data collection, ninth, reduce operating costs and reduce storage requirements. Tenth, make the diagnosis and ** more targeted.

Edge computing solves the problem of data volume and latency, so many applications related to these two aspects are application fields of edge computing.

What is edge computing.

Before we explain edge computing, let's look at a strange creature on Earth, the octopus. Some researchers lamented, "Octopuses are like alien creatures." "This is because there are many things that distinguish octopuses from other animals.

A distinct feature is that 60% of the neurons are distributed over the eight legs. The distributed mode of one brain + multiple cerebellums makes the octopus extremely sensitive when hunting.

Edge computing is very similar to the distribution of neurons in octopuses. It can provide cloud services and IT environment services for application developers and service providers at the edge of the network. The goal is to provide compute, storage, and network bandwidth close to data input or users.

A technology is often born to solve a certain problem, and the same is true for edge computing. In the traditional cloud computing mode, there are problems such as high latency, unstable network, and low bandwidth. If some or all of the processing procedures are moved to a location closer to the user, these problems can be solved and the data transmission efficiency and stability can be improved.

What can edge computing do?

With the development of the Internet, the amount of data is getting larger and larger, and it is obviously unrealistic to transmit massive amounts of data to the cloud computing center and generate decisions. At this time, edge computing can reflect its advantages, and the data no longer needs to be transmitted to the distant cloud, but can be solved at the edge.

Typical application areas of edge computing: CDN, Internet of Things (Internet of Vehicles), blockchain.