Wednesday, Sep 29, 2021
The proliferation of smart devices, along with the advent of technologies such as artificial intelligence, machine learning, and blockchain, has dramatically increased the amount of data that is constantly being collected and exchanged between users' devices and servers for analysis and processing. Although the speed of data exchange with the fifth generation of telecommunication networks is increasing dramatically, it will not be enough to respond to this volume of data exchange between all types of modern smart equipment with servers located in data centers. This is where the edge of computing comes into play.
Until recently, most companies They kept their business-related data and software local. For this purpose, they bought servers and placed them in special rooms with a suitable cooling system. Some companies also rented space from a nearby data center to store their servers and data. With the spread of information technology and the advancement of telecommunications, the situation gradually changed. More people started working from home. IT-related businesses are growing rapidly and their offices are being set up one after another in different cities and countries. Thus, the purchase and maintenance of the server in the place of companies and businesses soon lost its justification. For a fast-growing company, the constant purchase and maintenance of new servers is very difficult and can slow down and limit the business development process.
Cloud computing services such as Microsoft Azure and Amazon Web Services (AWS) solve these problems. Companies can rent storage space and processing resources on cloud service platforms according to their needs, and as they develop their business, they can easily use more resources. But like everything else in the world, cloud services have their advantages as well as their advantages. The main drawback of these types of services is that they are centralized. Major cloud service providers such as Microsoft, Amazon and Google are setting up and delivering data centers around the world. But depending on where on the planet you are, there are hundreds or even thousands of miles between you and the nearest data center of the service provider. Every time you plan to use cloud services, your request must be sent via fiber optics to the servers located in these data centers and the relevant response will be returned to your location. So the longer the distance between you and the cloud service provider data center, the more latency you will experience to receive the service. Another problem with reliance on cloud services is the high dependence of Internet services on services and the costs associated with providing adequate bandwidth for this purpose. The problem is especially acute in areas with unstable, slow, and expensive Internet connections.
To solve the problems associated with cloud services, it seems that the only solution is to repeat history. What will happen when the servers come from the overhead on the edge and are close to the user. This seems to be a throwback to the past, but in fact another step in the evolution of data management and processing systems.
In simple terms, edge computing is bringing applications and data closer to the users who use them. For large companies and their internally used software, edge computing can mean setting up dedicated servers near their main offices and branches. But in the case of services used by the general public, edge-based computing operations may be performed by mobile phones, wearables, and other types of smart devices instead of servers. Performing image processing and face recognition operations by smartphones or traffic control devices, instead of sending data and processing operations through cloud services, can be a simple example of this type of edge computing.
Gartner provides edge computing It knows from a distributed processing topology in which information processing operations take place near the edge of the network - where people and equipment produce or consume information. In centralized systems, the data need to be transferred from the place where it was generated and collected to a remote center and then returned to the original location after processing. Such a system causes large volumes of data to be continuously circulated, often with significant delays in processing. In contrast, edge computing, instead of relying on a central and remote location such as a data center, maintains and processes data near the same devices that are responsible for collecting data.
Outdoor food chain centers can be considered as a simple example to understand the concept and application of edge computing. In order to be able to deliver their food to their customers in different parts of the city with less delay and before it cools down, they open new branches in the areas where the most food orders are received. In this way, the food preparation process is done in a place closer to the customers and the ordered food reaches them faster and fresher. Computing Edge computing similarly intends to provide users with the desired results better and faster by performing data processing operations near users.
Utilizing edge computers has various benefits For end users and businesses, the most important of which are:
Speed up: Edge computing with significant deletion or reduction of data back-and-forth between user and processing location, waiting time to receive It greatly reduces the response. For example, when a user uses router applications, if the calculations and processing associated with choosing the best route instead of being performed by servers in a large data center thousands of kilometers away, using the processing power of his smartphone and with the help of information stored in With a local data center, routing operations can be done much faster and even more accurately.
Decreasing Internet Bandwidth Consumption: With the proliferation of smart devices and the growing development of the Internet of Things (IoT) in recent years, the amount of data that is constantly being collected and transferred over the Internet has increased dramatically. Has found. The use of centralized processing systems allows data to travel longer and thus take up more bandwidth. This increase in bandwidth consumption imposes high costs on users and businesses and can pose serious obstacles to IoT development. In such a situation, edge computing can play a major role in reducing Internet bandwidth consumption by performing processing operations near the place where the data is collected and used.
Security: Data transfer is always associated with security risks. In addition, big data centers and cloud service platforms are special and permanent targets for hackers. For these reasons, information in the cloud is not very secure. In edge computing, only some information is sent to cloud servers, and a smaller portion of the data is compromised at any given time. Even in some examples of edge computing, no internet connection is required and no data is sent to the cloud. In this way, less data can be stolen while moving between the user device and cloud servers, and if one of the edge equipment is hacked, only part of the data stored locally on the same device will be stolen or damaged. .
Reliability: Computing increases the edges of reliability and reliance on services. Because unlike cloud computing systems, receiving Internet-dependent services is not stable and users do not need to worry about network outages or Internet slowness. In edge computing, a significant portion of the data may be stored in local small data centers or in the internal memory of the user's smart devices. In this way, access to data and services with much higher reliability will be possible. For this reason, for remote areas and areas with inadequate Internet connection, cloud computing is a useful solution and is especially recommended.
Cost, scalability and agile development: In centralized and cloud computing, it is necessary that All data is sent to a data center and processed there. Therefore, the growth and expansion of services requires the development of data centers, improving stability and increasing Internet bandwidth. Things that can be very time consuming, tedious and costly. With edge computing, companies can quickly increase their data processing and storage capacity as needed with a combination of mobile smart devices, IoT equipment and small local data centers. The development of edge computing services with the addition of this type of equipment also requires much less Internet bandwidth.
Like any other technology, edge computing, in addition to all the advantages mentioned, also has various disadvantages. Some of these inherent disadvantages and others are related to the emergence of this technology and may gradually fade or disappear completely.
Security: Computing carries its own risks to information. The sheer variety of intelligent equipment that can participate in edge-to-edge computing poses challenges to the integrated information security of these devices. While a centralized system or cloud platform can be secured better and more easily by using specialized information security teams and special equipment.
Occupancy of resources in edge equipment: Storage and processing of data in edge equipment It would mean occupying hardware resources in this equipment. Data storage requires that part of the memory of these devices be occupied, and as a result the need for larger internal memory in a variety of edge smart devices will increase. Also, for processing this data at the edge, the processor of this equipment is used more and energy consumption is increased in them.
Data loss: In computing the edges of data that are not used for the current needs of the user and momentary decisions May be a lower priority or may be ignored altogether. If this data may be of great importance. For example, when driving a car on an empty road alone, it may seem useless to store data from sensors and cameras. While this seemingly insignificant data can provide useful information about road conditions and vehicle condition in those specific conditions. This information may be useful in the future for the same car or other self-driving car on that road.
Maintenance: Computing is the edge of a distributed system that has more components and more complex communications than a centralized system. Composed. Maintaining such systems will naturally be more difficult and costly.
One of the main applications of edge computing is the Internet of Things. In fact, the Internet of Things may be the most important factor in the development of edge computing. Today, a variety of smart devices in homes, workplaces and urban environments require an Internet connection to provide services. These devices typically collect data and send it to cloud platforms, or vice versa, receiving information from cloud platforms. With the growing use of such equipment around the world, resorting to distributed and local solutions for computing large volumes of data related to them seems obvious and inevitable. Therefore, the largest application of edge computing is expected to be the Internet of Things, or IoT, which includes smart cities, smart homes, self-driving cars, live video streaming services, security systems, telecommunications platforms, and smart medical services.
Other areas of application of edge computing include cloud gaming and virtual reality (VR) platforms. The main reason for the failure of cloud gaming platforms such as Google Stadia can be found in the centrality of these systems and their complete dependence on high-speed, stable and low-delay Internet connection with servers located in the relevant data centers. The problem, perhaps the most obvious solution, is the use of edge computing. Bringing cloud game servers to small data centers near the user, along with improving and upgrading communication technologies with the development and expansion of 5G technology, will finally provide the necessary conditions for the flourishing and success of this type of service. Thus, in the not-too-distant future, we may see the possibility of playing high-end games with the help of cloud services and seamlessly on a variety of devices, including smartphones, virtual reality glasses and televisions.
Mobile Edge Computing Computing, also known as "multi-access edge computing," refers to a type of edge computing that occurs on the outermost part of the network, near where mobile devices and their applications are generating or consuming data. Mobile edge computing is the process of increasing the speed of response and reducing network traffic by storing and processing data related to mobile applications near their users' locations, in fact, if mobile computing operations near the intersection of mobile networks with the Internet infrastructure This huge amount of data is prevented from entering the main Internet network and the speed of providing services in mobile applications is significantly increased.MEC technology is designed to be located at mobile network stations or other bases in the connection area of this Implement networks on the Internet ی شد.
Technical standards for this technology are being developed by the European Telecommunications Standards Institute, and companies including HP, Huawei, Cisco, Motorola Mobility, IBM, Nokia, Intel and AT&T are involved. Since the MEC architecture and its standards have just been introduced and are being developed, it has not yet been widely used and applied. Some conceivable applications for this technology include content delivery, big data mobile analysis, computational offloading, edge vieo caching, collaborative computing, connected vehicles. Networking, smart locations, healthcare, internal positioning, and more. Amazon's AWS Wavelength service can be considered the first commercial product based on MEC technology that has been widely used. Services on Amazon Web Services (AWS) allow applications to run on the edge of specific operators' 4G and 5G networks, and respond to relevant users with very little delay.
Using mobile edge computing (MEC) technology, mobile operators can offer new computing services locally to specific subscribers or special groups of subscribers. Utilization of this technology also reduces the signal load on the core of the operators' network and allows hosting applications and services at a lower cost. Application developers and multimedia content providers will also be able to take advantage of proximity to mobile users and use telecommunications network information live.
With the development of IoT technology, the business need for more processing capacity and location closer to the data collection point is increasing day by day. Especially in the fields of agriculture, oil, gas and wind energy industries, which are usually located in rural and sometimes remote areas. Expanding the use of sensors to collect large amounts of data, especially in areas with limited high-speed Internet access, will greatly increase the need and demand for mobile edge computing, thus making it possible to analyze data on the spot and in the photo. Provide prompt action based on received data.