KR102503776B1 - Smart cabinet for high-density data center server and its operation method - Google Patents

Abstract

The present invention monitors and centrally manages a storage, a power distribution device, a firefighting device, and a temperature/humidity sensor system as an interface medium. In addition, the present invention responds to various events and operating states, manages power usage amount control and temperature/humidity balancing control for each rack using a predictive algorithm over time, analyzes sampling data to predict sampling circuit abnormalities, data errors, and data changes, and responds to the same.

Description

Smart cabinet for high-density data center server and its operation method {SMART CABINET FOR HIGH-DENSITY DATA CENTER SERVER AND ITS OPERATION METHOD}

The present invention relates to a smart cabinet for a high-density data center server and an operation method thereof, and more particularly, to configure a smart cabinet used in a high-density data center server, to stably operate the smart cabinet of a high-density data center server, and to It relates to a smart cabinet for a high-density data center server that increases cabinet operation reliability and an operation method thereof.

The prior art related to the present invention includes, for example, water-cooled data centers, integrated cabinets, and modular data centers. Patent Document 1 A water-cooled data center having a coolant supply line supplies coolant to cabinets through the coolant supply line, the cabinets are arranged in at least one row of adjacent cabinets, and each row of adjacent cabinets receives coolant from an alternative coolant supply line. be supplied Also, Patent Document 2 physical infrastructure management system with an integrated cabinet has rack spaces and a cabinet with a sensor. In addition, Patent Document 3 System and method for allocation of virtual machines based on physical information balances computational loads in a virtual machine environment by considering the physical characteristics of the physical machines on which the virtual machines are running. Also, Patent Document 4 system and method for a modular data center is a modular data center, delivering cold air to data center components and conveying hot air from a heat aisle out of the unit structure.

The prior art has a problem in that it cannot respond to various events and operating states, and cannot manage power consumption control for each rack and temperature/humidity balancing control using a prediction algorithm according to time lapse.

Registered Patent Publication No. 10-1476069 Water-cooled data center with coolant supply line Registered Patent Publication No. 10-1743462 Physical infrastructure management system with integrated cabinet Korean Patent Registration No. 10-1771497 System and method for allocating virtual machines based on physical information Registered Patent Publication No. 10-2234195 System and method for modular data center

An object of the present invention is to provide a smart cabinet for a high-density data center server that monitors and centrally manages a storage, a power distribution device, a firefighting device, and a temperature and humidity sensor system through an interface and an operating method thereof.

In addition, the present invention provides a smart cabinet for a high-density data center server that responds to various events and operating conditions and manages power consumption control and temperature/humidity balancing control for each rack using a predictive algorithm according to time lapse and an operating method thereof to do for another purpose.

In addition, another object of the present invention is to analyze sampling data to predict sampling circuit abnormalities, data errors, and data changes, and to provide a smart cabinet and its operating method for a high-density data center server corresponding thereto.

A smart cabinet for a preferred high-density data center server of the present invention is called a data storage of a high-density data center server, and is a storage that records information in a storage medium, retrieves recorded data at an external request, and provides information according to a format. (21); Power Distribution Units (PDUs) (22 ); A firefighting device (23) that detects a fire occurrence point according to a change in device state by using a signal line for a contact embedded in a part and discharges an extinguishing agent directly through a hole in a tube at a fire occurrence point at a close distance; a temperature and humidity sensor system 24 that measures atmospheric temperature and humidity using a capacitive humidity sensor and a thermistor and outputs them as digital sensor signals; By installing it flat, the storage 21, the power distribution device 22, the fire fighting device 23, and the temperature and humidity sensor system 24 can be placed on top of each other, and the shelf 25 is made in several layers as an indoor device. shelf 25; Each component including the storage 21, the power distribution device 22, the firefighting device 23, and the temperature and humidity sensor system 24 is controlled and connected to a rack central management system 27. An interface 26 that efficiently manages rack units or local units; Various events and operation status (31), power consumption by rack (32), dashboard (30) displaying temperature/humidity (33), temperature balancing control (34), report provision (35), remote control (36) A central management system 27 to perform; and a monitoring system 28 mounted in units of the rack to monitor and actively control power quality and the surrounding environment.

In addition, the central management system 27 visualizes various current conditions including power, temperature, humidity, and top surface of the high-density data center as a 2D/3D dashboard, and a dashboard 30 displaying various events and operation status ; A power control unit 37 that integrates and manages power consumption by rack in real time through the smart power distribution device 22 and implements an energy-efficient green data center; The temperature/humidity inside the data center is monitored in real time, and appropriate temperature/humidity is adjusted through a smart fan according to the temperature distribution, and multiple temperature/humidity sensors are used for systematic temperature/humidity management inside/outside the containment Temperature balancing control (34), which is configured and operated, supports stable operation by removing the heat source of the high-heating/high-density rack, subdividing the target temperature and delta temperature discharged from the rack, and leveling the temperature distribution through tracking management; Provides various reports to improve operational efficiency of high-density data sensors and supports floor management, enables creation and inquiry of various reports by date and equipment with the Excel export function, and provides a report to manage the floor operation status by rack (35); and a remote control (36) that supports integrated management of the data center by building a server for nationwide integrated monitoring and building an optimal remote control system.

In addition, the smart cabinet visualizes various current conditions, including power, temperature, humidity, and top surface of the high-density data center with a 2D/3D dashboard, displays various events and operation status (S201), and displays power consumption by rack (S202) and displaying temperature/humidity (S203); The temperature/humidity inside the data center is monitored in real time, and appropriate temperature/humidity is adjusted through a smart fan according to the temperature distribution, and multiple temperature/humidity sensors are used for systematic temperature/humidity management inside/outside the containment Temperature balancing control (34) step ( S204); Provides various reports and supports floor management to improve operational efficiency of high-density data sensors, enables creation and inquiry of various reports by date and equipment with the Excel export function, and provides reports to manage the floor operation status by rack (35) Step (S205) ); Remote control (36) step (S206) of establishing a server for nationwide integrated monitoring and establishing an optimal remote control system to support integrated management of the data center; and power control (37) step (S207) of real-time integrated management of power consumption by rack through the smart power distribution device 22 and realization of an energy-efficient green data center.

In addition, the smart cabinet stores sampling data, calculates a probability distribution by accumulating the number of occurrences for each size of sampling data for a certain period of time, calculates a probability distribution for another certain period of time, and calculates the difference between the two probability distributions, Area difference and difference distance accumulation are calculated (S101) to predict sampling circuit failure, data error, data change, and respond to hardware failure, data error, and data change, and the sampling data is power consumption per rack, temperature/humidity, temperature It is characterized by including balancing control and power control.

The present invention can have the effect of configuring a smart cabinet used in a high-density data center server by monitoring and centrally managing a storage, a power distribution device, a firefighting device, and a temperature and humidity sensor system as an interface medium.

In addition, the present invention responds to various events and operating conditions, and manages power consumption control and temperature/humidity balancing control for each rack using a predictive algorithm according to time progress, thereby stably operating smart cabinets of high-density data center servers. can have

In addition, the present invention can have the effect of increasing the operation reliability of the smart cabinet by analyzing the sampling data to predict sampling circuit abnormalities, data errors, and data changes, and responding to them.

1 is a block diagram showing the configuration of a smart cabinet for a high-density data center server of the present invention.
Figure 2 is a block diagram showing the configuration of the control unit of the smart cabinet of Figure 1;
3 is a flowchart showing a method of operating a smart cabinet for a high-density data center server according to the present invention.
4 is an exemplary view illustrating a configuration for verifying data errors for explaining the present invention.
5 is an exemplary diagram illustrating a system authentication configuration for granting authority to execute hardware resources, an operating system, an operation of a control unit, which is a core, and an operation of a control unit for explaining the present invention.

Hereinafter, a smart cabinet for a high-density data center server and an operating method thereof according to an embodiment of the present invention will be described in detail with reference to the drawings. Hereinafter, descriptions of conventionally known matters are omitted or simplified to clarify the gist of the present invention. The configurations included in the description of the present invention operate in individual or complex combination configurations.

1 is a block diagram showing the configuration of a smart cabinet for a high-density data center server according to the present invention. Referring to FIG. 1, the smart cabinet includes a storage 21, a power distribution device 22, a fire protection device 23, and a temperature and humidity sensor. It includes a system 24, a shelf 25, an interface 26, a central management system 27, and a monitoring system 28.

The storage 21 is called the data storage of the high-density data center server, records information in the storage medium, retrieves the recorded data upon external request, and provides information according to a format.

A power distribution unit (PDU) 22 is a plug-in, prefabricated cabling solution for distributing power from a high-density data center uninterruptible power supply (UPS) to a rack power distribution unit. to provide.

The firefighting device 23 detects a fire occurrence point according to a change in device state by utilizing a contact signal line built into a part, and directly discharges an extinguishing agent through a hole in a tube at a fire occurrence point at a close distance.

The temperature and humidity sensor system 24 measures air temperature and humidity using a capacitive humidity sensor and a thermistor, and outputs the digital sensor signal.

The shelf 25 can be installed flat to put the storage 21, the power distribution device 22, the fire fighting device 23, and the temperature and humidity sensor system 24, and the shelf 25 can be installed in several layers as an indoor device. make

The interface 26 controls parts including the storage 21, the power distribution device 22, the fire protection device 23, and the temperature and humidity sensor system 24, respectively, and is connected to the rack central management system 27. and manage efficiently in rack units or local units.

The central management system (27) provides a dashboard (30) displaying various events and operation status (31), power consumption by rack (32), temperature/humidity (33), temperature balancing control (34), and report (35) , performs remote control (36).

The monitoring system 28 is mounted in units of racks to monitor and actively control power quality and the surrounding environment.

2 is a block diagram showing the configuration of a control unit of the smart cabinet of FIG. 1. Referring to FIG. 2, the control unit 5 includes a dashboard 30, temperature balancing control 34, report provision 35, and remote control 36. ) is performed.

The dashboard 30 visualizes various current conditions including power, temperature, humidity, and top surface of the high-density data center as a 2D/3D dashboard, and displays various events and operation status.

The power control unit 37 integrates and manages power consumption per rack in real time through the smart power distribution device 22 and realizes an energy-efficient green data center.

The temperature balancing control (34) monitors the temperature/humidity inside the data center in real time and adjusts the appropriate temperature/humidity through a smart fan according to the temperature distribution, and for systematic temperature/humidity management inside/outside the containment. It is operated by configuring multiple temperature/humidity sensors, removes heat sources from high-heat/high-density racks, subdivides target temperature and delta temperature discharged from racks, and levels out temperature distribution through tracking management to support stable operation.

Report provision (35) supports provision of various reports and surface management to improve operational efficiency of high-density data sensors, and with the Excel export function, various reports can be created and inquired by date and equipment, and management of surface operation status by rack.

The remote control 36 supports integrated management of the data center by constructing a server for nationwide integrated monitoring and establishing an optimal remote control system.

3 is a flowchart showing a method of operating a smart cabinet for a high-density data center server according to the present invention. Referring to FIG. 3, the smart cabinet displays various events and operation status (S201), displays power consumption by rack (S202), turns on/off Humidity display (S203), temperature balancing control (S204), report provision (S205), remote control (S206), and power control (S207) are performed.

The smart cabinet visualizes various current conditions including power, temperature, humidity, and top surface of the high-density data center in a 2D/3D dashboard, displays various events and operation status (S201), displays power consumption by rack (S202) , and displays temperature/humidity (S203).

The smart cabinet monitors the temperature/humidity inside the data center in real time in the temperature balancing control (34), adjusts the appropriate temperature/humidity through the smart fan according to the temperature distribution, and systematically controls the temperature/humidity inside/outside the containment. It is operated by configuring a number of temperature/humidity sensors for management, removes heat sources from high-heating/high-density racks, subdivides target temperature and delta temperature discharged from racks, and levels out temperature distribution through tracking management to ensure stable operation. support

Smart cabinet provides various reports and supports floor management to improve operation efficiency of high-density data sensors in report provision (35), and with the Excel export function, various reports can be created and inquired by date and equipment, and management of floor operation status by rack do.

The smart cabinet supports the integrated management of the data center by building a server for nationwide integrated monitoring and building an optimal remote control system in the remote control (36).

The smart cabinet implements an energy-efficient green data center by real-time integrated management of power usage per rack through the smart power distribution device 22 in the power control unit 37.

4 is an exemplary view illustrating a configuration for verifying data errors to explain the present invention.

Referring to FIG. 4, the control unit 5 stores sampling data, calculates a probability distribution by accumulating the number of occurrences for each size of the sampling data for a predetermined time, calculates a probability distribution for another predetermined time, and calculates two probabilities. By calculating the distribution difference, area difference, and difference distance accumulation (S101), sampling circuit abnormalities, data errors, and data changes can be predicted and responded to (S102). The control unit 5 may respond to the user by notifying the user of the prediction result, or the control unit 5 may respond to hardware failure, data error, or data change.

Sampling data may include power consumption per rack, temperature/humidity, temperature balancing control, and power control.

The controller 5 looks at the trend of each probability distribution for a certain period of time, predicts an abnormal phenomenon among the probability distribution, responds to an abnormal accident, and informs the outside of normal operation if the data change is constant with respect to the probability distribution. In addition, the control unit 5 feeds back the data change rate in order to adjust the predetermined time interval. For example, if the data change rate is large, the certain time interval is increased, and if the data change rate is small, the certain time interval is decreased.

FIG. 5 is an exemplary diagram illustrating a system authentication configuration for granting authority to execute hardware resources, an operating system, a core control unit, and a control unit operation for explaining the present invention. Referring to FIG. 5, the present invention is a processor (1) ), memory 2, input/output device 3, operating system 4, and control unit 5.

The processor 1 is a CPU (Central Processing Units), a GPU (Graphic Processing Unit), an FPGA (Field Programmable Gate Array), and an NPU (Neural Processing Unit). ) executes the executable code.

The memory 2 includes a permanent mass storage device such as random access memory (RAM), read only memory (ROM), disk drive, solid state drive (SSD), flash memory, etc. can do.

The input/output device 3 is an input device, such as a camera, keyboard, microphone, mouse, etc., including an audio sensor and/or an image sensor, and an output device, such as a display, speaker, haptic feedback device, etc. device may be included.

The operating system 4 may include Windows, Linux, IOS, a virtual machine, a web browser, and an interpreter, and supports tasks, threads, timer execution, scheduling, resource management, graphics, font processing, communication, and the like.

The control unit 5 determines the state of the input/output device 3 by sensor, key, touch, and mouse input under the support of the operating system 4, and performs an operation according to the determined state. The control unit 5 performs task scheduling using a timer and thread as a parallel execution routine.

The control unit 5 determines a state using the sensor value of the input/output device 3 and performs an algorithm according to the determined state.

Referring to FIG. 5 , the system authentication configuration includes a terminal 6 including a control unit 5 and an authentication server 7 .

The terminal 6 duplicates the data channels, receives the key value and biometric information of the terminal 6, and requests user authentication from the authentication server 7 through the first data channel. It is displayed on the display and transmitted to the authentication server (7).

The terminal 6 inputs the kit value displayed on the display of the terminal 6 and transmits it to the authentication server 7 through the second data channel along with user information. The terminal 6 requests the authentication server 7 to authenticate the system installed in the terminal 6 using the kit value and user information. The kit value of the terminal 6 can be generated from computer-specific information such as the CPU manufacturing number and the address of the Ethernet chip. The terminal 6 may obtain user information through face recognition using a camera, voice recognition using a microphone, and handwriting recognition using a display, and may use it for authentication.

The authentication server 7 receives the kit value from the terminal 6, receives the kit value and user information from the terminal 6 through a duplicated data channel, compares the kit value of the terminal 6 with the user information, and returns the user information Correspondingly, authentication for system use of the terminal 6 is processed. The authentication server 7 transmits the authentication result to the terminal 6 to allow the user to use the system. Due to the duplicated data channel of the terminal 6, loss of kit value can be minimized.

The authentication server 7 performs a history analysis of user information, and compares and determines consistency and change of user information over time. In the history analysis, if the user information shows consistency, the user's use is permitted, and if it shows change, the user's use is not permitted. When the user information shows consistency, the user's use of the system is permitted, thereby strengthening security to prevent a user whose user information has been altered from accessing the system.

The authentication server 7 assigns weights to consistency, change, frequency, frequency trend, and high frequency, and blocks access by untrusted users with a combination of weights. For example, if the frequency threshold is exceeded, access by untrusted users is blocked in proportion to the excess cumulative number, and users attempting access over a long period of time can be authenticated. At this time, additional authentication is requested for untrusted users.

The terminal 6, which is a means of authenticating the use of the system, does not directly connect to the system, but forms a detour through the authentication server 7, so that the network constituting the Internet network is composed of an internal network and an external network, and the IP address setting process When this is cumbersome, there is an advantage in that the authentication process using the terminal 6 is smoothly performed. At this time, the system is mounted on the terminal 6, the terminal 6 serves as an authentication terminal means, and the authentication server 7 serves as an authentication server means.

The cloud 12 is modularized by the container 7 under the support of the operating system 4 that manages the processor 1, memory 2, input/output device 3, and communication unit 6, and the web 8, DB ( 9), protocol 10, and library 11 services are provided, and the control unit 5 executes a cloud application using the container 7 service. A standard software package, called a container 7, bundles the application's code along with relevant configuration files, libraries 11 and the dependencies required to run the app.

The cloud 12 performs integrated control of a plurality of terminals 6, stores sensor values received from the terminals 6, monitors them over time, processes operation errors of the terminals 6, and transmits error messages to other terminals. The terminal 6 is notified, and the control target terminal 6 is switched and controlled.

Neural network learning selects a model through feature selection and algorithm selection from time-series data collected from input devices such as various sensors such as temperature, altitude, and fingerprints, cameras such as images and infrared rays, and LIDAR, and then repeats learning and performance verification processes. Repeat model selection through trial and error. After performance verification is complete, an artificial intelligence model is selected.

The control unit 5 performs a deep learning algorithm using a neural network to determine the sensor value, uses training data to learn the neural network, and verifies the performance of the neural network with test data.

The present invention is not limited to the specific preferred embodiments described above, and various modifications can be made by anyone skilled in the art without departing from the gist of the present invention claimed in the claims. Of course, such changes are within the scope of the claims.

1: Processor
2: memory
3: I/O device
4: operating system
5: control unit
6: Terminal
7: authentication server
8: web
9: DB
11: Library
12: cloud
14: container
16: Department of Communications
21: Storage
22: power distribution device
23: fire fighting device
24: temperature and humidity sensor system
25: shelf
26: Interface
27: central management system
28: monitoring system
30: Dashboard
31: Various events and operation status
32: Power consumption per rack
33: temperature/humidity
34: temperature balancing control
35: Provide report
36: remote control
37: power control

Claims (4)

Storage 21, which is called a data storage of a high-density data center server, records information in a storage medium, retrieves recorded data at an external request, and provides information according to a format;
Power Distribution Units (PDUs) (22 );
A firefighting device (23) that detects a fire occurrence point according to a change in device state by using a signal line for a contact embedded in a part and discharges an extinguishing agent directly through a hole in a tube at a fire occurrence point at a close distance;
a temperature and humidity sensor system 24 that measures atmospheric temperature and humidity using a capacitive humidity sensor and a thermistor and outputs them as digital sensor signals;
By installing it flat, the storage 21, the power distribution device 22, the fire fighting device 23, and the temperature and humidity sensor system 24 can be placed on top of each other, and the shelf 25 is made in several layers as an indoor device. shelf 25;
Each component including the storage 21, the power distribution device 22, the firefighting device 23, and the temperature and humidity sensor system 24 is controlled and connected to a rack central management system 27. An interface 26 that efficiently manages rack units or local units;
Various events and operation status (31), power consumption by rack (32), dashboard (30) displaying temperature/humidity (33), temperature balancing control (34), report provision (35), remote control (36) A central management system 27 to perform; and
A monitoring system 28 mounted in the rack unit to monitor power quality and the surrounding environment and actively control the monitoring system 28;
The central management system 27,
A dashboard 30 that visualizes various current conditions including power, temperature, humidity, and top surface of a high-density data center in a 2D/3D dashboard, and displays various events and operation status;
A power control unit 37 that integrates and manages power consumption by rack in real time through the smart power distribution device 22 and implements an energy-efficient green data center;
The temperature/humidity inside the data center is monitored in real time, and appropriate temperature/humidity is adjusted through a smart fan according to the temperature distribution, and multiple temperature/humidity sensors are used for systematic temperature/humidity management inside/outside the containment Temperature balancing control (34), which is configured and operated, supports stable operation by removing the heat source of the high-heating/high-density rack, subdividing the target temperature and delta temperature discharged from the rack, and leveling the temperature distribution through tracking management;
Provides various reports to improve operational efficiency of high-density data sensors and supports floor management, enables creation and inquiry of various reports by date and equipment with the Excel export function, and provides a report to manage the floor operation status by rack (35); and
Remote control (36) that supports integrated management of the data center by establishing a server for nationwide integrated monitoring and establishing an optimal remote control system;
smart cabinets,
Various statuses including power, temperature, humidity, and top surface of the high-density data center are visualized in a 2D/3D dashboard, various events and operation status are displayed (S201), power consumption by rack is displayed (S202), and on/off Displaying humidity (S203);
The temperature/humidity inside the data center is monitored in real time, and appropriate temperature/humidity is adjusted through a smart fan according to the temperature distribution, and multiple temperature/humidity sensors are used for systematic temperature/humidity management inside/outside the containment The temperature balancing control (34) step ( S204);
Provides various reports and supports floor management to improve operational efficiency of high-density data sensors, enables creation and inquiry of various reports by date and equipment with the Excel export function, and provides reports to manage floor operation status by rack (35) Step (S205) );
Remote control (36) step (S206) of establishing a server for nationwide integrated monitoring and establishing an optimal remote control system to support integrated management of the data center; and
Performs power control (37) step (S207) of real-time integrated management of power consumption by rack through the smart power distribution device 22 and realization of an energy-efficient green data center;
The smart cabinet,
Sampling data is stored, a first probability distribution is calculated by accumulating the number of occurrences for each size of the sampling data for a certain period of time, a second probability distribution is calculated for another certain period of time, and the two first and second probability distributions are calculated. Calculate the area difference (S101) to predict sampling circuit abnormalities, data errors, and data changes, respond to hardware failures, data errors, and data changes,
The sampling data is a smart cabinet for a high-density data center server, characterized in that it includes power consumption per rack, temperature / humidity, temperature balancing control, and power control. delete delete delete

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