{"id":54228,"date":"2019-12-21T00:00:00","date_gmt":"2019-12-20T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/gde-i-kak-primenyayutsya-granichnye-servery"},"modified":"2020-02-18T14:02:13","modified_gmt":"2020-02-18T11:02:13","slug":"gde-i-kak-primenyayutsya-granichnye-servery","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/administrirovanie\/gde-i-kak-primenyayutsya-granichnye-servery","title":{"rendered":"Where and how are edge servers applied","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/c4f3df5c9efe4875512386e5519340a5.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nWhen developing a network infrastructure, one typically considers either local computing or cloud solutions. However, these two options and their combinations are often insufficient. For instance, what should one do if abandoning cloud computing is not an option, but bandwidth is lacking or traffic costs are too high?<\/p>\n<p>Introduce an intermediary that performs part of the computations at the edge of a local network or production process. This peripheral concept is known as Edge Computing. It complements the current cloud data usage model, and in this article, we will explore the necessary equipment and examples of tasks for it.<br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<h2>Levels of edge computing<\/h2>\n<p>\n<img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/3e7668732a316af6c36afb3d8b946607.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nLet's say you have a bunch of sensors set up at home: a thermometer, hygrometer, light sensor, leak detector, and more. A logic controller processes the incoming information from these devices, implements automation scenarios, sends processed telemetry to the cloud service, and receives updated automation scenarios and new firmware from it. Thus, local computing is performed directly at the site while the equipment is controlled from a node that consolidates many such devices.\u00a0<\/p>\n<p>This is an example of a very simple edge computing system, but it already demonstrates all three levels of edge computing:<\/p>\n<ul>\n<li>IoT devices: generate \u2018raw data\u2019 and transmit it via various protocols.\u00a0<\/li>\n<li>Edge nodes: process data in close proximity to the sources of information and act as temporary data storage.<\/li>\n<li>Cloud services: offer management functions for both edge and IoT devices, perform long-term storage and data analysis. Additionally, they support integration with other corporate systems.\u00a0<\/li>\n<\/ul>\n<p>\nThe concept of Edge computing itself is part of a larger ecosystem that optimizes the technological process. It encompasses both hardware (rack and edge servers) as well as network and software components (for instance, the Codex AI Suite platform).<noindex><a rel=\"nofollow\" href=\"https:\/\/atos.net\/ru\/russia\/products\/codex-ai-suite\"> Codex AI Suite<\/a><\/noindex> for the development of AI algorithms). Since a \"bottleneck\" can occur during the creation, transmission, and processing of \"big data\" and limit the performance of the entire system, these components must be compatible with each other.<\/p>\n<h2>Features of Edge Servers<\/h2>\n<p>\nAt the level of edge nodes in Edge Computing, edge servers are utilized, which are placed directly where the information is generated. Typically, these are production or technical facilities where it is not possible to install a server rack and ensure cleanliness. Therefore, edge servers are designed in compact dust- and moisture-resistant enclosures with an extended temperature range, and they cannot be rack-mounted. Indeed, such a server can comfortably hang on double-sided tape anchors somewhere under the stairs or in a utility room.<\/p>\n<p>Since edge servers are installed outside of protected data centers, they have higher physical security requirements. Protective enclosures are provided for them:<\/p>\n<p><img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/e38f5460732cf0c44702e4e3dbcd97cc.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nAt the data handling level in edge servers, disk encryption and secure boot are implemented. The encryption itself consumes 2-3% of computational power, but edge servers typically use Xeon D processors with integrated AES acceleration modules, which minimize power losses.<\/p>\n<h2>When edge servers are used<\/h2>\n<p>\n<img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/a5724cef018cb5478f3a77be3ac97847.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nIn Edge Computing, only the data that cannot be processed or is impractical to process otherwise is sent to the data center for processing. Thus, edge servers are used when it is necessary to:<\/p>\n<ul>\n<li>Implement a flexible security approach, as in the case of Edge Computing, it is possible to configure the transmission of pre-processed and prepared information to the central data center;\u00a0\n<\/li>\n<li>Protect against information loss, as local nodes will accumulate information in the event of a loss of connection with the center;\u00a0\n<\/li>\n<li>Save on traffic, achieved by processing the main data array on-site.\u00a0\n<\/li>\n<\/ul>\n<p><\/p>\n<h2>Edge Computing for Traffic Savings<\/h2>\n<p>\n<img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/e0a85558ced9a87776423cba06659bda.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nThe Danish company Maersk, one of the leaders in maritime freight transportation worldwide, decided to reduce fuel consumption for its ships and lower harmful emissions into the atmosphere.\u00a0<\/p>\n<p>To address this issue, technology was used <noindex><a rel=\"nofollow\" href=\"https:\/\/new.siemens.com\/global\/en\/markets\/marine\/innovations.html\">Siemens EcoMain Suite<\/a><\/noindex>, sensors on engines and main components of the ship, as well as the local BullSequana Edge server for on-site computations.\u00a0<\/p>\n<p>Thanks to the sensors, the EcoMain Suite system continuously monitors the condition of critical ship components and their deviations from the pre-calculated norms. This allows for quick diagnosis of faults and localization down to the problematic component. Since telemetry is constantly transmitted 'to the center', the service technician can analyze remotely and provide recommendations to the onboard team. The main question here is how much data and in what volume to send to the central data center.\u00a0<\/p>\n<p>Since connecting cheap wired internet to a marine container ship is quite problematic, transmitting large amounts of raw data to the central server turns out to be too costly. At the central BullSequana S200 server, an overall logical model of the ship is calculated, while data processing and direct control are handed over to the local server. As a result, the implementation of this system paid for itself within three months.<\/p>\n<h2>Edge computing for resource savings<\/h2>\n<p>\n<img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/0ea8fb0bccf0cdb79ef23e1346876884.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nAnother example of edge computing is video analytics. For example, for the gas equipment manufacturer Air Liquide, one of the local tasks in the production cycle is the quality control of painted gas cylinders. This was done manually and took about 7 minutes per cylinder.<\/p>\n<p>To speed up this process, a block of 7 high-resolution video cameras replaced the human inspector. The cameras capture the cylinder from several angles, generating about 1 GB of video per minute. The video is sent to the edge server BullSequana Edge with an Nvidia T4 on board, where a neural network trained to detect defects analyzes the stream in real-time. As a result, the average inspection time was reduced from several minutes to just a few seconds.<\/p>\n<h2>Edge computing in analytics<\/h2>\n<p>\n<img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/469c0b33b65da66cc3f5ecac3dcb1bb8.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nAttractions in Disneyland are not just about fun; they are complex technical objects. For instance, the 'American Roller Coaster' is equipped with about 800 different sensors. They constantly send data about the ride's operation to the server, while the local server processes this data, calculates the likelihood of the ride malfunctioning, and alerts the central data center.\u00a0<\/p>\n<p>Based on this data, the likelihood of technical failure is determined, and preventive maintenance is initiated. The attraction continues to operate until the end of the working day, during which a repair order has already been issued, and workers are promptly fixing the attraction at night.\u00a0<\/p>\n<h2>BullSequana Edge\u00a0<\/h2>\n<p>\n<img decoding=\"async\" alt=\"Where and how are edge servers applied\" src=\"\/wp-content\/uploads\/2019\/12\/72006ca009c56e573453bf2fa0189b14.jpg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nBullSequana Edge servers are part of a larger infrastructure for working with big data, already tested with Microsoft Azure and Siemens MindSphere platforms, VMware WSX, and have NVidia NGC\/EGX certifications. These servers are specifically designed for edge computing and are available in U2 form factor enclosures for standard rack installation, DIN rail, wall mount, and floor installation.\u00a0<\/p>\n<p>BullSequana Edge is built on a custom-designed motherboard and Intel Xeon D-2187NT processor. They support installation of up to 512 GB of RAM, 2 SSDs of 960 GB each, or 2 HDDs of 8 or 14 TB each. Additionally, they can accommodate 2 Nvidia T4 16 GB GPUs for video processing; Wi-Fi, LoRaWAN, and 4G modules; and up to 2 ten-gigabit SFP modules. The servers already include a lid opening sensor connected to the BMC, which manages the IPMI module. It can be configured for automatic power shutdown upon sensor activation.\u00a0<\/p>\n<p>You can find the full technical specifications of BullSequana Edge servers at <noindex><a rel=\"nofollow\" href=\"https:\/\/atos.net\/wp-content\/uploads\/2019\/12\/BullSequana-Edge.pdf\">this link<\/a><\/noindex>. If you would like more details, we would be happy to answer any questions in the comments.<br \/>\n<br \/>Source: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/bull\/blog\/481120\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u0440\u0438 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0435 \u0441\u0435\u0442\u0435\u0432\u043e\u0439 \u0438\u043d\u0444\u0440\u0430\u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u044b \u043e\u0431\u044b\u0447\u043d\u043e \u0440\u0430\u0441\u0441\u043c\u0430\u0442\u0440\u0438\u0432\u0430\u044e\u0442 \u043b\u0438\u0431\u043e \u043b\u043e\u043a\u0430\u043b\u044c\u043d\u044b\u0435 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u044f, \u043b\u0438\u0431\u043e \u043e\u0431\u043b\u0430\u0447\u043d\u044b\u0435. \u041d\u043e \u044d\u0442\u0438\u0445 \u0434\u0432\u0443\u0445 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u043e\u0432 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