CN111580443A - Cloud data center internet of things management and control and application system - Google Patents

Cloud data center internet of things management and control and application system Download PDF

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Publication number
CN111580443A
CN111580443A CN202010559374.2A CN202010559374A CN111580443A CN 111580443 A CN111580443 A CN 111580443A CN 202010559374 A CN202010559374 A CN 202010559374A CN 111580443 A CN111580443 A CN 111580443A
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cluster head
data
sensor
head node
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孙志敏
位彩红
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Lanjing Zhiyun Intelligent Technology Nanjing Co ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0428—Safety, monitoring
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B19/00—Alarms responsive to two or more different undesired or abnormal conditions, e.g. burglary and fire, abnormal temperature and abnormal rate of flow
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2612—Data acquisition interface

Abstract

The invention discloses a cloud data center internet of things management and control and application system, which comprises: the system comprises a data acquisition terminal, a central sink node and a monitoring management platform; the data acquisition terminal acquires power environment data inside the cabinet and machine room environment data of a machine room environment; forwarding the power environment data and the machine room environment data to a central sink node; the central aggregation node aggregates the received data, and transmits the data to the monitoring management platform after compression processing; and the monitoring management platform analyzes the power environment data and the machine room environment data, and gives an alarm when the analysis result shows that the environment is abnormal. Through the data acquisition terminal, not only can gather the inside environmental data of rack, also can gather computer lab environmental data simultaneously, then carry out the analysis by the environmental data of control management platform to the integration control to the inside and computer lab environment of rack has been realized, the environmental safety of guarantee rack and computer lab.

Description

Cloud data center internet of things management and control and application system
Technical Field
The invention relates to the technical field of intelligent monitoring, in particular to a cloud data center internet of things management and control and application system.
Background
The existing data center is mainly centralized inside an intelligent integrated cabinet, even if the cabinet is involved outside in some enterprise schemes, only machine room environment monitoring (temperature and humidity) and the like are generally concerned, monitoring systems for machine room internal safety (water inflow), security protection (machine room entrance guard), machine room illumination and the like are basically information isolated islands and are respectively administrative, and a unified monitoring and management platform is not provided. The user's computer lab construction is developed by stage, if want to carry out intelligent upgrading transformation to the computer lab, just will face with the technique butt joint of each producer, consuming time and wasting power.
Disclosure of Invention
In order to solve the problems, the invention provides a cloud data center internet of things management and control and application system.
The purpose of the invention is realized by adopting the following technical scheme:
a cloud data center thing allies oneself with management and control and application system, this management and control system includes: the system comprises a data acquisition terminal, a central sink node and a monitoring management platform based on lora communication and serial communication;
the data acquisition terminal is used for acquiring power environment data and machine room environment data in the cabinet; forwarding the power environment data and the machine room environment data to the central sink node;
the central aggregation node aggregates the received data, and forwards the data to the monitoring management platform after compression processing;
and the monitoring management platform is used for analyzing the power environment data and the machine room environment data and giving an alarm when the analysis result shows that the environment is abnormal.
In a possible implementation, the management and control system further includes: and the user terminal is in communication connection with the monitoring management platform and is used for receiving the alarm information from the monitoring management platform.
In one possible embodiment, the data acquisition terminal includes: the system comprises a first data acquisition logic module for acquiring power environment data in the cabinet and a second data acquisition logic module for acquiring machine room environment data;
the first data acquisition logic module and the second data acquisition logic module both comprise: a plurality of sensor monitoring nodes;
the first data acquisition logic module forwards the acquired power environment data to the central sink node based on serial port communication;
and the second data acquisition logic module forwards the acquired machine room environment data to the central sink node based on lora communication.
In one possible embodiment, the sensor monitoring node includes: one or more of a temperature sensor, a humidity sensor, a voltage sensor, a current sensor, a smoke sensor.
In a possible implementation, the management and control system further includes: the door magnetic controller is in communication connection with the monitoring management platform;
and when the monitoring management platform analysis result shows that the environment is abnormal, an operation instruction is sent to the door magnetic controller, and the door magnetic controller controls the skylight to be opened according to the received operation instruction.
In a possible implementation manner, the sensor monitoring node and the central aggregation node in the second data acquisition logic module construct a wireless sensor network with a cluster structure according to a preset clustering mechanism.
In a feasible implementation manner, the wireless sensor network with a cluster structure is constructed according to a preset clustering mechanism, and the specific construction process is as follows:
(1) after the deployment of the sensor monitoring nodes is completed, the central sink node broadcasts a clustering instruction to the whole network, and after each sensor monitoring node receives the clustering instruction, a data packet carrying self information is transmitted back to the central sink node;
(2) the central sink node determines K fixed clusters through an iteration method according to the received data packets, wherein K is the preset optimal clustering number;
(3) updating the cluster head node in each fixed cluster based on the determined K fixed clusters to obtain an optimal cluster head node;
(4) after the optimal cluster head node is determined, a cluster adding instruction is sent to the fixed cluster where the optimal cluster head node is located, and after other sensor monitoring nodes of the fixed cluster where the optimal cluster head node is located receive the cluster adding instruction, the other sensor monitoring nodes are added into the optimal cluster head node to become cluster member nodes of the optimal cluster head node, and clustering is finally achieved.
In a possible implementation manner, the central sink node determines K fixed clusters by an iterative method according to the received data packet, specifically:
step 1: setting the initial value of k to be 1, selecting one sensor monitoring node from all the sensor monitoring nodes as a first cluster head node, and recording as C1；
Step 2: calculating the rest of sensor monitoring nodes and the newly selected cluster head node CkSelecting the sensor monitoring node with the maximum energy efficiency value as the next cluster head node Ck+1(ii) a Wherein, the sensor monitors the node siAnd cluster head node CkThe calculation formula of the energy efficiency value is as follows:
Figure BDA0002545520300000021
in the formula, Eva(s)i,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkEnergy efficiency value between, d(s)i,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkSpatial distance between, Rmax(si)、Rmax(Ck) Respectively, monitoring nodes s for sensorsiAnd cluster head node CkMaximum perceived radius of, E1(si,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkThe value of energy consumed for information interaction between them, i.e. representing the sensor monitoring node siTransmitting unit data to cluster head node CkAnd cluster head node CkThe amount of energy consumed to receive and forward the unit data to the central sink node, Eres(si)、Eres(Ck) Respectively, monitoring nodes s for sensorsiAnd cluster head node CkThe current residual energy values α, β and gamma are preset weight coefficients which meet the condition that α + β + gamma is 1, I is the number of the residual sensor monitoring nodes, and K is 1,2,.
Step 3: repeating Step 2 until K cluster head nodes are selected;
step 4: and taking the sensor monitoring node which is not selected as the cluster head node as a common node, calculating the spatial distance between the common node and each cluster head node, and adding the common node into the cluster head node with the closest spatial distance to the common node to become a cluster member node of the cluster head node until all the common nodes are added into the corresponding cluster head node to finally obtain K fixed clusters.
The invention has the beneficial effects that: the invention aims to provide a cloud data center internet of things management and control and application system.
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The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a framework structure diagram of a cloud data center internet of things management and control and application system according to an embodiment of the present invention.
Reference numerals: the system comprises a data acquisition terminal 1, a first data acquisition logic module 11, a second data acquisition logic module 12, a central sink node 2, a monitoring management platform 3, a user terminal 4 and a door magnetic controller 5.
Detailed Description
The invention is further described with reference to the following examples.
Fig. 1 shows a cloud data center internet of things management and control and application system, where the management and control system includes: the system comprises a data acquisition terminal 1 based on lora communication and serial port communication, a central sink node 2 and a monitoring management platform 3;
the data acquisition terminal 1 is used for acquiring power environment data and machine room environment data in the cabinet; forwarding the power environment data and the machine room environment data to the central sink node 2;
the central aggregation node 2 aggregates the received data, and forwards the data to the monitoring management platform 3 after compression processing;
and the monitoring management platform 3 is used for analyzing the power environment data and the machine room environment data and giving an alarm when the analysis result shows that the environment is abnormal.
The invention aims to provide a cloud data center internet of things management and control and application system.
In a possible implementation, the management and control system further includes: and the user terminal 4 is in communication connection with the monitoring management platform 3, and the user terminal 4 is used for receiving the alarm information from the monitoring management platform 3.
In a possible embodiment, the monitoring and management platform 3 is provided with: and the lora module is used for establishing communication connection between the monitoring management platform 3 and the central convergent node 2 through the lora module so as to acquire the environmental parameters sensed by the sensor monitoring nodes. The monitoring management platform 3 is also provided with RS485, RS232, DI and DO interfaces.
In a possible embodiment, the data acquisition terminal 1 comprises: the system comprises a first data acquisition logic module 11 for acquiring power environment data inside the cabinet and a second data acquisition logic module 12 for acquiring environmental data of a machine room;
the first data acquisition logic module 11 and the second data acquisition logic module 12 each include: a plurality of sensor monitoring nodes;
the first data acquisition logic module 11 forwards the acquired power environment data to the central sink node 2 based on serial port communication;
the second data collection logic module 12 forwards the collected machine room environment data to the central sink node 2 based on lora communication.
In one possible embodiment, the sensor monitoring node includes: one or more of a temperature sensor, a humidity sensor, a voltage sensor, a current sensor, a smoke sensor.
Through temperature sensor and humidity transducer, can acquire near its position temperature data and humidity data, then forward to control management platform 3 by central sink node, control management platform 3 carries out the analysis to received temperature data and humidity data, and then can know the temperature and the humidity condition in the rack and the temperature and the humidity condition in the computer lab, realized the long-range control to rack and computer lab, guarantee rack and computer lab environmental safety. In a feasible implementation mode, the temperature sensor and the humidity sensor can be connected through an RS485 interface, then a query instruction of a modbus standard is sent through a program arranged in the monitoring management platform 3, the temperature and humidity sensor returns corresponding data, and an accurate temperature and humidity value can be obtained after processing.
The voltage data and the current data of the power distribution unit can be acquired through the voltage sensor and the current sensor, then the voltage data and the current data are forwarded to the monitoring management platform 3 through the central sink node, the monitoring management platform 3 analyzes the received voltage data and the received current data, intelligent monitoring on the power distribution unit is achieved, and power supply safety is guaranteed. In a possible implementation manner, the RS232 interface is connected to a DP9 interface of the UPS power supply, a program built in the monitoring management platform 3 is used to send a query instruction, and after data is returned, data such as the current, voltage, and temperature of the UPS is obtained by analyzing the content corresponding to each data segment.
The smoke sensor can acquire smoke data which can be acquired nearby the position of the smoke sensor, the smoke data are forwarded to the monitoring management platform 3 through the central sink node, the monitoring management platform 3 analyzes the received smoke data, when the analysis result shows that the smoke data exceed a preset smoke threshold value, the monitoring management platform 3 gives an alarm directly, meanwhile, alarm information can be sent to the user terminal 4, the user is reminded to take measures in time, and potential safety hazards are eliminated. In a possible implementation manner, the smoke sensor may be further connected to the DI interface, when the smoke sensor detects smoke, a signal is sent to the DI port of the monitoring management platform 3, and when the DI port of the monitoring management platform 3 detects that a signal exists, the alarm information is sent through a short message, a mail, or the like.
In a possible implementation, the management and control system further includes: the door magnetic controller 5 is in communication connection with the monitoring management platform 3;
when the analysis result of the monitoring management platform 3 shows that the environment is abnormal, an operation instruction is sent to the door magnetic controller 5, and the door magnetic controller 5 controls the skylight to be opened according to the received operation instruction. In a feasible implementation manner, the door sensor controller 5 of the skylight is connected through a DO interface, when the analysis result of the monitoring management platform 3 shows that the environment is abnormal, a signal can be sent to the door sensor controller 5 through the DO interface, and the door sensor controller 5 controls the skylight to be opened according to the received signal.
In a possible embodiment, the monitoring management platform 3 further comprises: and the human-computer interaction module can acquire the control instruction sent by the manager through the human-computer interaction module, and then the monitoring management platform 3 executes the corresponding task according to the received control instruction. If an air conditioner regulation and control instruction sent by a manager is obtained through the man-machine interaction module, after the air conditioner regulation and control instruction received by the monitoring management platform 3, the air conditioner PLC module of the monitoring management platform 3 controls the working state of the air conditioner according to the received air conditioner regulation and control instruction, such as the power-on/off of the air conditioner, the rotating speed of an EC fan, the air conditioner running temperature and the like. If can obtain the battery life detection instruction that the user sent through man-machine interaction module, control management platform 3 receives battery health detection instruction, sends drive instruction to UPS power, and the UPS power is according to the charge-discharge of received drive instruction control battery, finally obtains the battery loss value to with the battery loss value that obtains send to control management platform 3, control management platform 3 judges whether the battery is healthy according to the battery loss value that obtains, whether need change. If after a relay control instruction sent by a manager is obtained through the man-machine interaction module, the relay control instruction is sent to the intelligent PDU relay by the monitoring management platform 3, and the intelligent PDU relay controls the power-on/power-off of the corresponding socket according to the received relay control instruction.
In a possible implementation manner, the sensor monitoring node and the central aggregation node in the second data acquisition logic module 12 construct a wireless sensor network with a cluster structure according to a preset clustering mechanism.
In a feasible implementation manner, the wireless sensor network with a cluster structure is constructed according to a preset clustering mechanism, and the specific construction process is as follows:
(1) after the deployment of the sensor monitoring nodes is completed, the central sink node 2 broadcasts a clustering instruction to the whole network, and after each sensor monitoring node receives the clustering instruction, a data packet carrying self information is transmitted back to the central sink node 2;
(2) the central sink node 2 determines K fixed clusters through an iteration method according to the received data packets, wherein K is a preset optimal clustering number;
(3) updating the cluster head node in each fixed cluster based on the determined K fixed clusters to obtain an optimal cluster head node;
(4) after the optimal cluster head node is determined, a cluster adding instruction is sent to the fixed cluster where the optimal cluster head node is located, and after other sensor monitoring nodes of the fixed cluster where the optimal cluster head node is located receive the cluster adding instruction, the other sensor monitoring nodes are added into the optimal cluster head node to become cluster member nodes of the optimal cluster head node, and clustering is finally achieved.
In a possible implementation manner, the central aggregation node 2 determines K fixed clusters by an iterative method according to the received data packet, specifically:
step 1: setting the initial value of k to be 1, selecting one sensor monitoring node from all the sensor monitoring nodes as a first cluster head node, and recording as C1；
Step 2: calculating the rest of sensor monitoring nodes and the newly selected cluster head node CkSelecting the sensor monitoring node with the maximum energy efficiency value from the energy efficiency valuesPoint as next cluster head node Ck+1(ii) a Wherein, the sensor monitors the node siAnd cluster head node CkThe calculation formula of the energy efficiency value is as follows:
Figure BDA0002545520300000061
in the formula, Eva(s)i,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkEnergy efficiency value between, d(s)i,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkSpatial distance between, Rmax(si)、Rmax(Ck) Respectively, monitoring nodes s for sensorsiAnd cluster head node CkMaximum perceived radius of, E1(si,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkThe value of energy consumed for information interaction between them, i.e. representing the sensor monitoring node siTransmitting unit data to cluster head node CkAnd cluster head node CkThe amount of energy consumed to receive and forward the unit data to the central sink node, Eres(si)、Eres(Ck) Respectively, monitoring nodes s for sensorsiAnd cluster head node CkThe current residual energy value of each sensor is α, β and gamma which are preset weight coefficients and meet α + β + gamma of 1, I is the number of residual sensor monitoring nodes, specifically, the number of sensor monitoring nodes which are not selected as a cluster head node in the current iteration round is 1,2,.
Step 3: repeating Step 2 until K cluster head nodes are selected;
step 4: and taking the sensor monitoring node which is not selected as the cluster head node as a common node, calculating the spatial distance between the common node and each cluster head node, and adding the common node into the cluster head node with the closest spatial distance to the common node to become a cluster member node of the cluster head node until all the common nodes are added into the corresponding cluster head node to finally obtain K fixed clusters.
If the sensor monitoring nodes are all in direct communication with the central sink node 2, the sensor monitoring nodes of the type that are relatively far away from the central sink node 2, consume large energy and have small residual energy may prematurely die due to energy exhaustion, which may adversely affect the monitoring capability of the system and affect the accuracy of the environmental monitoring of the whole system. In order to balance the energy consumption of the whole wireless sensor network, the applicant proposes a wireless sensor network with a clustering structure, wherein when determining a cluster, the applicant creatively proposes to determine K cluster head nodes by adopting the above method, and then obtains K fixed clusters based on the determined K cluster head nodes, wherein when determining the cluster head nodes, the applicant creatively proposes to determine the cluster head nodes one by adopting an iteration method, specifically, when determining the cluster head nodes each time, the applicant selects a sensor monitoring node with the largest energy efficiency value as a next cluster head node by calculating the energy efficiency value between the rest of sensor monitoring nodes and a newly selected cluster head node, and considers the influences of a plurality of factors such as the spatial distance between the sensor monitoring node and the cluster head node, the maximum sensing radius between the sensor monitoring node and the cluster head node, and the energy when calculating the energy efficiency value between the sensor monitoring node and the newly selected cluster head node, therefore, the sensor monitoring node which is relatively far away from the cluster head node and consumes overlarge energy in information interaction with the cluster head node can be selected as the next cluster head node, the reasonability of the distribution of the cluster head node is ensured, and the aim of balancing the wireless sensor network is fulfilled.
In a possible implementation manner, the selecting one sensor monitoring node from all the sensor monitoring nodes as the first cluster head node specifically includes:
calculating the priority value of each sensor monitoring node, selecting the sensor monitoring node with the maximum priority value as a first cluster head node, and recording as C1(ii) a The priority value of the sensor monitoring node is calculated by the following formula:
Figure BDA0002545520300000071
in the formula, Pre(s)j) Monitoring nodes s for sensorsjThe value of the priority of (a) is,
Figure BDA0002545520300000072
monitoring nodes s for sensorsjThe maximum radius of perception of (a) is,
Figure BDA0002545520300000073
monitoring nodes s for sensorsjNumber of sensor monitoring nodes in maximum sensing range, Lmax(sj) Monitoring nodes s for sensorsjMaximum data packet length capable of transmission, t being sensor monitoring node sjThe time required to transmit the largest data packet to the central sink node, μ is the time loss factor, d(s)jBS) monitoring node s for a sensorjThe spatial distance from the central sink node.
The sensor monitoring node serving as the cluster head node undertakes tasks of receiving data transmitted by the cluster member nodes in the cluster and forwarding the data to the central sink node, so that compared with a common node, the more energy is consumed, and once the sensor monitoring node dies, the data sensed by the cluster member nodes in the cluster cannot be transmitted to the central sink node, so that adverse effects on the system environment monitoring accuracy are caused, and therefore, the selection of a proper cluster head node is of great importance. In the above embodiment of the present invention, the priority value of each sensor monitoring node is calculated, and then the sensor monitoring node with the largest priority value is selected as the first cluster head node, thereby facilitating the subsequent determination of other suitable cluster head nodes. When the priority value of the sensor monitoring node is calculated, the influences of the number of the sensor monitoring nodes in the maximum sensing range, the length of the maximum data packet which can be transmitted, the time required for transmitting the data packet to the central sink node and the like are considered, so that the sensor monitoring node meeting the requirements can be selected as a first cluster head node, and the subsequent clustering work can be carried out smoothly.
In a feasible implementation manner, the updating is performed on the cluster head node in each fixed cluster based on the determined K fixed clusters to obtain an optimal cluster head node, specifically:
to fix a cluster FCkBy way of example, in which a cluster FC is fixedkThe cluster head node in (1) is marked as CkFixed cluster FCkCluster member node in (1) is marked as svWherein V is 1,2, V is a fixed cluster FCkThe number of middle cluster member nodes;
with cluster head node CkTaking r as a radius to draw a circular area I, wherein all sensor monitoring nodes in the fixed cluster are positioned in the circular area, and r is a fixed cluster FCkMiddle cluster member node to cluster head node CkThe maximum distance of (d);
with cluster head node CkAs a center, to
Figure BDA0002545520300000081
Drawing a circular area II for the radius, and marking an annular area formed by the circular area I and the circular area II as an annular area Ш;
respectively counting the number of sensor monitoring nodes in the circular area II and the number of sensor monitoring nodes in the annular area III;
then, the reference position coordinates of the optimal cluster head node are determined according to the following formula:
Figure BDA0002545520300000082
Figure BDA0002545520300000083
in the formula, x0、y0Respectively being the abscissa and the ordinate of the reference position of the optimal cluster head node; saFor sensor monitoring nodes located in the circular area II, A is the number of the sensor monitoring nodes in the circular area II, sbThe number of sensor monitoring nodes located in the annular region Ш is B, and the number of sensor monitoring nodes in the annular region Ш is B;
Figure BDA0002545520300000091
respectively, monitoring nodes s for sensorsaThe abscissa and ordinate of (a);
Figure BDA0002545520300000092
respectively, monitoring nodes s for sensorsbThe abscissa and ordinate of (a);
based on the determined reference position coordinates of the optimal cluster head node, calculating a cluster head node C by using a lower deviation functionkThe deviation degree value from the reference position of the optimal cluster head node, if the deviation degree value is smaller than a preset deviation degree threshold value, the cluster head node CkThe node is the optimal cluster head node; otherwise, the fixed cluster FC is calculated by using the lower deviation functionkSelecting the cluster member node with the minimum deviation degree value as the optimal cluster head node according to the deviation degree values of the reference positions of the inner cluster member nodes and the optimal cluster head node, wherein the cluster head node CkAnd restoring the common node to be added into the optimal cluster head node to become a cluster member node of the optimal cluster head node. Wherein the expression of the deviation function is:
Figure BDA0002545520300000093
in the formula (I), the compound is shown in the specification,
Figure BDA0002545520300000094
is a cluster head node CkThe abscissa and ordinate of (a);
has the advantages that: in the embodiment, the optimal cluster head node is determined based on the determined fixed cluster, wherein when the position coordinate of the optimal cluster head node is determined, the cluster head node in the fixed cluster is taken as the center to determine two areas, namely the circular area II and the annular area III, and based on the determined areas, the horizontal coordinate and the vertical coordinate of the optimal cluster head node are determined by adopting the method in the embodiment of the invention, and the coordinates obtained by the method enable the position of the obtained optimal cluster head node to be close to the area where the sensor monitoring nodes in the fixed cluster are relatively concentrated, so that the energy loss of information transmission between the cluster member nodes and the cluster head in the cluster is reduced, and the timeliness and the effectiveness of the information transmission are ensured.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims (8)

1. A cloud data center thing allies oneself with management and control and application system, characterized by includes: the system comprises a data acquisition terminal, a central sink node and a monitoring management platform based on lora communication and serial communication;
the data acquisition terminal is used for acquiring power environment data and machine room environment data in the cabinet; forwarding the power environment data and the machine room environment data to the central sink node;
the central aggregation node aggregates the received data, and forwards the data to the monitoring management platform after compression processing;
and the monitoring management platform is used for analyzing the power environment data and the machine room environment data and giving an alarm when the analysis result shows that the environment is abnormal.
2. The system of claim 1, further comprising: and the user terminal is in communication connection with the monitoring management platform and is used for receiving the alarm information from the monitoring management platform.
3. The system according to claim 1, wherein the data acquisition terminal comprises: the system comprises a first data acquisition logic module for acquiring power environment data in the cabinet and a second data acquisition logic module for acquiring machine room environment data;
the first data acquisition logic module and the second data acquisition logic module both comprise: a plurality of sensor monitoring nodes;
the first data acquisition logic module forwards the acquired power environment data to the central sink node based on serial port communication;
the second data acquisition logic module forwards the acquired machine room environment data to the central sink node based on lora communication;
and the sensor monitoring node is used for sensing the environmental parameters near the position of the sensor monitoring node and forwarding the environmental parameters to the central aggregation node.
4. The system of claim 3, wherein the sensor monitoring node comprises: one or more of a temperature sensor, a humidity sensor, a voltage sensor, a current sensor, a smoke sensor.
5. The system of claim 1, further comprising: the door magnetic controller is in communication connection with the monitoring management platform;
and when the monitoring management platform analysis result shows that the environment is abnormal, an operation instruction is sent to the door magnetic controller, and the door magnetic controller controls the skylight to be opened according to the received operation instruction.
6. The system according to claim 3, wherein the sensor monitoring nodes and the central aggregation node in the second data acquisition logic module construct a wireless sensor network with a clustering structure according to a preset clustering mechanism.
7. The system according to claim 6, wherein the wireless sensor network with a cluster structure is constructed according to a preset clustering mechanism, and the specific construction process is as follows:
(1) after the deployment of the sensor monitoring nodes is completed, the central sink node broadcasts a clustering instruction to the whole network, and after each sensor monitoring node receives the clustering instruction, a data packet carrying self information is transmitted back to the central sink node;
(2) the central sink node determines K fixed clusters through an iteration method according to the received data packets, wherein K is the preset optimal clustering number;
(3) updating the cluster head node in each fixed cluster based on the determined K fixed clusters to obtain an optimal cluster head node;
(4) after the optimal cluster head node is determined, a cluster adding instruction is sent to the fixed cluster where the optimal cluster head node is located, and after other sensor monitoring nodes of the fixed cluster where the optimal cluster head node is located receive the cluster adding instruction, the other sensor monitoring nodes are added into the optimal cluster head node to become cluster member nodes of the optimal cluster head node, and clustering is finally achieved.
8. The system according to claim 7, wherein the central sink node determines K fixed clusters by an iterative method according to the received data packet, specifically:
step 1: setting the initial value of k to be 1, selecting one sensor monitoring node from all the sensor monitoring nodes as a first cluster head node, and recording as C1；
Step 2: calculating the rest of sensor monitoring nodes and the newly selected cluster head node CkSelecting the sensor monitoring node with the maximum energy efficiency value as the next cluster head node Ck+1(ii) a Wherein, the sensor monitors the node siAnd cluster head node CkThe calculation formula of the energy efficiency value is as follows:
Figure FDA0002545520290000021
in the formula, Eva(s)i,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkEnergy efficiency value between, d(s)i,Ck) Monitoring nodes s for sensorsiAnd clusterHead node CkSpatial distance between, Rmax(si)、Rmax(Ck) Respectively, monitoring nodes s for sensorsiAnd cluster head node CkMaximum perceived radius of, E1(si,Ck) Monitoring nodes s for sensorsiAnd cluster head node CkThe value of energy consumed for information interaction between them, i.e. representing the sensor monitoring node siTransmitting unit data to cluster head node CkAnd cluster head node CkThe amount of energy consumed to receive and forward the unit data to the central sink node, Eres(si)、Eres(Ck) Respectively, monitoring nodes s for sensorsiAnd cluster head node CkThe current residual energy values α, β and gamma are preset weight coefficients which meet the condition that α + β + gamma is 1, I is the number of the residual sensor monitoring nodes, and K is 1,2,.
Step 3: repeating Step 2 until K cluster head nodes are selected;
step 4: and taking the sensor monitoring node which is not selected as the cluster head node as a common node, calculating the spatial distance between the common node and each cluster head node, and adding the common node into the cluster head node with the closest spatial distance to the common node to become a cluster member node of the cluster head node until all the common nodes are added into the corresponding cluster head node to finally obtain K fixed clusters.
CN202010559374.2A 2020-06-18 2020-06-18 Cloud data center internet of things management and control and application system Pending CN111580443A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113300457A (en) * 2021-04-21 2021-08-24 浙江纳特智能网络工程有限公司 Weak current monitoring system based on intelligent internet of things
CN114199304A (en) * 2021-11-05 2022-03-18 华能金昌光伏发电有限公司 Abnormity detection method and device for communication machine room of photovoltaic power station and computer equipment

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113300457A (en) * 2021-04-21 2021-08-24 浙江纳特智能网络工程有限公司 Weak current monitoring system based on intelligent internet of things
CN113300457B (en) * 2021-04-21 2022-06-10 浙江纳特智能网络工程有限公司 Weak current monitoring system based on intelligent internet of things
CN114199304A (en) * 2021-11-05 2022-03-18 华能金昌光伏发电有限公司 Abnormity detection method and device for communication machine room of photovoltaic power station and computer equipment

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