IT equipment remote monitoring system based on Internet of Things

Abstract

The invention relates to the technical field of remote monitoring of the Internet of Things, and particularly discloses an IT equipment remote monitoring system based on the Internet of Things, and the system comprises a calculation module which is used for calculating and obtaining a fault evaluation value, a resource consumption evaluation value and a security threat evaluation value of each IT equipment at the current moment; the construction module is used for obtaining all monitoring nodes of the Internet of Things at the current moment based on the fault assessment values, the resource consumption assessment values and the security threat assessment values of all the IT equipment at the current moment; and the control module is used for obtaining a remote monitoring result of the Internet of Things at the current moment based on all monitoring nodes of the Internet of Things at the current moment. According to the method, the coordinate points of the IT devices needing to be monitored in all the IT devices of the Internet of Things at the current moment are accurately screened out, blind monitoring is avoided, unnecessary resource consumption is reduced, optimal allocation of bandwidths of all the IT devices of the Internet of Things is achieved, and the overall quality of monitoring data is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of remote monitoring of the Internet of Things, and in particular to a remote monitoring system for IT equipment based on the Internet of Things. Background Art

[0002] At present, with the rapid development of Internet of Things technology, more and more IT devices are connected to the network, forming a large and complex system. At present, the technology with broad application prospects in the field of Internet of Things is remote monitoring of IT equipment based on narrowband Internet of Things (NB-IoT). This method shows significant advantages in improving monitoring efficiency and reducing costs, especially in remote, low-power and wide-coverage application scenarios. Although NB-IoT has the characteristics of wide coverage, its bandwidth is relatively limited. In an environment with limited resources, if a large number of IT devices are connected for remote monitoring at the same time, the data transmission rate of some devices may decrease due to uneven bandwidth allocation, thereby affecting the real-time and accuracy of monitoring data. Therefore, how to reasonably allocate bandwidth resources to ensure that key IT equipment can obtain sufficient bandwidth for data transmission and communication is an urgent issue.

[0003] However, there is no existing IT equipment remote monitoring system based on the Internet of Things that can accurately screen out the coordinate points of IT equipment that needs to be monitored among all IT equipment in the Internet of Things at the current moment, and achieve the optimal allocation of bandwidth for all IT equipment in the Internet of Things, thereby ensuring the overall quality of monitoring data.

[0004] Therefore, the present invention proposes an IT equipment remote monitoring system based on the Internet of Things. Summary of the invention

[0005] The present invention provides an IT equipment remote monitoring system based on the Internet of Things, which is used to obtain the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment according to the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data and the processed values ​​of all types of security threat data of each IT device at all moments in a preset time period before the current moment, so as to quantify the fault degree, resource consumption degree and security threat degree of each IT device at the current moment, and then obtain the spatial node connection diagram of the Internet of Things at the current moment according to the fault assessment values, resource consumption assessment values ​​and security threat assessment values ​​of all IT devices at the current moment, so as to facilitate the subsequent determination of monitoring nodes, obtain all monitoring nodes of the Internet of Things at the current moment according to the spatial node connection diagram of the Internet of Things at the current moment, and accurately screen out the coordinate points of IT devices that need to be monitored among all IT devices of the Internet of Things at the current moment, and finally obtain the remote monitoring result of the Internet of Things at the current moment according to all monitoring nodes of the Internet of Things at the current moment, so as to achieve the optimal allocation of bandwidth for all IT devices of the Internet of Things, improve the monitoring efficiency and ensure the overall quality of monitoring data.

[0006] The present invention provides an IT equipment remote monitoring system based on the Internet of Things, comprising:

[0007] A monitoring module, for obtaining, based on all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current time, processed values ​​of all types of historical fault data, processed values ​​of all types of resource consumption data and processed values ​​of all types of security threat data of each IT device at the current time;

[0008] A calculation module, used to obtain a fault assessment value, a resource consumption assessment value, and a security threat assessment value of each IT device at the current moment based on the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data, and the processed values ​​of all types of security threat data of each IT device at all times within a preset time period before the current moment;

[0009] A construction module is used to obtain a spatial node connection diagram of the Internet of Things at the current moment based on the fault assessment values, resource consumption assessment values, and security threat assessment values ​​of all IT devices at the current moment, and obtain all monitoring nodes of the Internet of Things at the current moment based on the spatial node connection diagram of the Internet of Things at the current moment;

[0010] The control module is used to obtain the remote monitoring result of the Internet of Things at the current moment based on all monitoring nodes of the Internet of Things at the current moment.

[0011] Preferably, the remote monitoring system for IT equipment based on the Internet of Things, the monitoring module includes:

[0012] The monitoring acquisition submodule obtains all types of historical fault data, all types of resource consumption data, and all types of security threat data of each IT device at all times in the preset time period before the current moment. All types of historical fault data include the number of new faults, the time to solve new faults, and the star rating of the difficulty of new fault maintenance. All types of resource consumption data include CPU usage, memory usage, and network bandwidth usage. All types of security threat data include the number of new intrusion detections and vulnerability scans.

[0013] The processing submodule is used to process all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current moment, and obtain the processed values ​​of all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at the current moment.

[0014] Preferably, the remote monitoring system for IT equipment based on the Internet of Things, the processing submodule includes:

[0015] A first processing unit is used to use the difference and sum of the values ​​of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before the current moment and the standard deviation of the values ​​of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device at all times within the preset time period before the current moment as the lower limit and upper limit of the value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device;

[0016] A second processing unit is used to use a set of all values ​​of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before a current moment, which are not less than a lower limit of a value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data, and whose corresponding values ​​are not greater than an upper limit of a value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data, as a statistical set of the corresponding type of historical fault data or a statistical set of the corresponding type of resource consumption data or a statistical set of the corresponding type of security threat data of the corresponding IT device, and use a set consisting of all data that does not belong to the statistical set of the corresponding type of historical fault data or the statistical set of the corresponding type of resource consumption data or the statistical set of the corresponding type of security threat data of each IT device in each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before a current moment, as a preliminary supplementary statistical set of the corresponding type of historical fault data or a preliminary supplementary statistical set of the corresponding type of resource consumption data or a preliminary supplementary statistical set of the corresponding type of security threat data of the corresponding IT device;

[0017] The third processing unit is used to obtain the processing value of each type of historical fault data or the processing value of each type of resource consumption data or the processing value of each type of security threat data of each IT device at the current moment based on the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device and a preset statistical threshold.

[0018] Preferably, in the remote monitoring system for IT equipment based on the Internet of Things, the method in which the third processing unit obtains the processing value of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at the current moment based on the number of elements in the statistical set of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device and a preset statistical threshold comprises:

[0019] Determine whether the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device is not less than a preset statistical threshold; if so, use the average of the values ​​of all elements in the statistical set of the corresponding type of historical fault data or the statistical set of the corresponding type of resource consumption data or the statistical set of the corresponding type of security threat data of the corresponding IT device as the processed value of the corresponding type of historical fault data or the processed value of the corresponding type of resource consumption data or the processed value of the corresponding type of security threat data of the corresponding IT device at the current moment;

[0020] Otherwise, the absolute value of the difference between the number of elements in the statistical set of each type of historical fault data of each IT device or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data and the preset statistical threshold is used as the supplementary number of the corresponding type of historical fault data of the corresponding IT device or the supplementary number of the corresponding type of resource consumption data or the supplementary number of the corresponding type of security threat data, and the preliminary supplementary statistical set of the corresponding type of historical fault data of the corresponding IT device or the preliminary supplementary statistical set of the corresponding type of resource consumption data of the corresponding IT device is calculated according to the supplementary number of each type of historical fault data of each IT device or the supplementary number of each type of resource consumption data or the supplementary number of each type of security threat data. Elements are extracted from the supplementary statistical set or the prepared supplementary statistical set of the corresponding class of security threat data to obtain a supplementary statistical set of each class of historical fault data of each IT device or a supplementary statistical set of each class of resource consumption data or a supplementary statistical set of each class of security threat data, and the average of the values ​​of all elements in the supplementary statistical set of each class of historical fault data of each IT device or a supplementary statistical set of each class of resource consumption data or a supplementary statistical set of each class of security threat data is used as the processed value of the corresponding class of historical fault data or the processed value of the corresponding class of resource consumption data or the processed value of the corresponding class of security threat data of the corresponding IT device at the current moment.

[0021] Preferably, the remote monitoring system for IT equipment based on the Internet of Things, the computing module includes:

[0022] A preparation submodule, used to obtain the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data, and the processed values ​​of all types of security threat data of all IT devices at all times within a preset time period before the current moment, and use the average of the processed values ​​of each type of historical fault data or the processed values ​​of each type of resource consumption data or the processed values ​​of each type of security threat data of each IT device at all times within the preset time period before the current moment as a reference average value of the corresponding type of historical fault data or the reference average value of the corresponding type of resource consumption data or the reference average value of the corresponding type of security threat data of the corresponding IT device at the current moment;

[0023] The calculation submodule is used to obtain the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment based on the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT device at the current moment.

[0024] Preferably, in the remote monitoring system for IT equipment based on the Internet of Things, the method in which the calculation submodule obtains the fault assessment value, resource consumption assessment value and security threat assessment value of each IT equipment at the current moment based on the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT equipment at the current moment includes:

[0025]

[0026] Among them, α is the fault assessment value of the IT equipment currently calculated at the current moment, β is the resource consumption assessment value of the IT equipment currently calculated at the current moment, γ is the security threat assessment value of the IT equipment currently calculated at the current moment, C is the reference mean of the number of new faults of the IT equipment currently calculated at the current moment, c is the processing value of the number of new faults of the IT equipment currently calculated at the current moment, and c max c is the maximum value of the number of newly added faults of the IT equipment currently calculated at all times in the preset time period before the current time. min is the minimum value of the processing values ​​of the newly added faults of the IT equipment at all times in the preset time period before the current moment, V is the reference mean value of the newly added fault resolution time of the IT equipment at the current moment, v is the processing value of the newly added fault resolution time of the IT equipment at the current moment, and v max v is the maximum value of the newly added fault resolution time of the IT equipment in the preset time period before the current moment. min is the minimum value of the processing values ​​of the newly added fault resolution time of the IT equipment currently calculated at all times in the preset time period before the current moment, L is the reference mean value of the newly added fault maintenance difficulty star number of the IT equipment currently calculated at the current moment, l is the processing value of the newly added fault maintenance difficulty star number of the IT equipment currently calculated at the current moment, l max is the maximum value of the processed values ​​of the newly added fault maintenance difficulty stars of the IT equipment at all times in the preset time period before the current moment, l min is the minimum value of the processed values ​​of the newly added fault maintenance difficulty stars of the IT equipment currently calculated at all times in the preset time period before the current moment, Q is the reference mean value of the CPU utilization rate of the IT equipment currently calculated at the current moment, q is the processed value of the CPU utilization rate of the IT equipment currently calculated at the current moment, and q max The maximum value of the CPU usage of the IT equipment in the preset time period before the current moment. min is the minimum value of the CPU usage of the IT device currently calculated at all times in the preset time period before the current moment, W is the reference mean value of the memory occupancy of the IT device currently calculated at the current moment, w is the processed value of the memory occupancy of the IT device currently calculated at the current moment, w max is the maximum value of the memory usage of the IT device currently calculated at all times in the preset time period before the current time, w minis the minimum value of the processed values ​​of the memory occupancy rate of the currently calculated IT device at all times in the preset time period before the current moment, R is the reference mean value of the network bandwidth occupancy of the currently calculated IT device at the current moment, r is the processed value of the network bandwidth occupancy of the currently calculated IT device at the current moment, and r max is the maximum value of the network bandwidth occupied by the IT equipment at all times in the preset time period before the current moment, r min is the minimum value of the processed values ​​of the network bandwidth occupied by the currently calculated IT equipment at all times in the preset time period before the current moment, E is the reference mean value of the number of new intrusion detections of the currently calculated IT equipment at the current moment, e is the processed value of the number of new intrusion detections of the currently calculated IT equipment at the current moment, and e max is the maximum value of the number of newly added intrusion detections of the IT equipment at all times in the preset time period before the current time. min is the minimum value of the processed values ​​of the newly added intrusion detection times of the currently calculated IT equipment at all times in the preset time period before the current moment, T is the reference mean value of the vulnerability scan times of the currently calculated IT equipment at the current moment, t is the processed value of the vulnerability scan times of the currently calculated IT equipment at the current moment, t max The maximum value of the vulnerability scan count of the IT device currently being calculated at all times within the preset time period before the current time. min It is the minimum value among the processed values ​​of the vulnerability scan numbers of the currently calculated IT equipment at all times in the preset time period before the current time. ln is the natural logarithm, and the value of the natural constant e is 2.718.

[0027] Preferably, the IT equipment remote monitoring system based on the Internet of Things, the building blocks include:

[0028] A coordinate determination submodule, used to obtain the coordinate point of each IT device by taking the fault assessment value of each IT device at the current moment as the horizontal coordinate value, the resource consumption assessment value of the corresponding IT device at the current moment as the vertical coordinate value, and the security threat assessment value of the corresponding IT device at the current moment as the vertical coordinate value;

[0029] A submodule is constructed, which is used to treat two different IT devices among all IT devices as a group of IT devices, obtain all groups of IT devices, and if two IT devices in each group of IT devices have information interaction within a preset time period before the current moment, connect the coordinate points of the two IT devices in the corresponding group of IT devices to obtain a spatial node connection diagram of the Internet of Things at the current moment;

[0030] The node analysis submodule is used to obtain all monitoring nodes of the Internet of Things at the current moment based on the spatial node connection diagram of the Internet of Things at the current moment.

[0031] Preferably, the node analysis submodule of the IT equipment remote monitoring system based on the Internet of Things includes:

[0032] A preparation unit is used to use the number of coordinate points connected to each coordinate point among all coordinate points of the spatial node connection diagram of the Internet of Things at the current moment as the number of connections of the corresponding coordinate point, and use the directly connected coordinate point farthest from the corresponding coordinate point among all directly connected coordinate points of each coordinate point as the farthest directly connected coordinate point of each coordinate point, use the distance between each coordinate point and the farthest directly connected coordinate point of the corresponding coordinate point as the farthest directly connected distance of the corresponding coordinate point, use the directly connected coordinate point closest to the corresponding coordinate point among all directly connected coordinate points of each coordinate point as the nearest directly connected coordinate point of each coordinate point, and use the distance between each coordinate point and the nearest directly connected coordinate point of the corresponding coordinate point as the nearest directly connected distance of the corresponding coordinate point;

[0033] A calculation unit, for obtaining the degree of necessity of monitoring each coordinate point in the spatial node connection graph of the Internet of Things at the current moment based on the number of connections, the farthest direct connection distance, and the closest direct connection distance of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment;

[0034] The analysis unit is used to use the corresponding coordinate point as the monitoring node of the Internet of Things at the current moment when the monitoring necessity of each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment is greater than a preset necessity threshold.

[0035] Preferably, in the remote monitoring system for IT equipment based on the Internet of Things, the method in which the calculation unit obtains the degree of monitoring necessity of each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment based on the number of connections, the farthest direct connection distance and the closest direct connection distance of all coordinate points in the spatial node connection diagram of the Internet of Things at the current moment comprises:

[0036]

[0037] Where, ρ is the monitoring necessity of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, n is the total number of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, m is the number of connections of the currently calculated coordinate points in the spatial node connection graph of the Internet of Things at the current moment, and m 0 is the mean value of the number of connections of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, is the mean of the longest direct connection distances of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, u max is the farthest direct connection distance of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, u minis the nearest direct connection distance of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, ω is the mean of the nearest direct connection distances of all coordinate points of the spatial node connection graph of the Internet of Things at the current moment, ln is the natural logarithm, and the value of the natural constant e is 2.718.

[0038] Preferably, the remote monitoring system for IT equipment based on the Internet of Things, the control module includes:

[0039] The first control submodule is used to use the maximum value of the processed values ​​of the network bandwidth occupancy of each IT device at all times within a preset time period before the current moment as the predicted bandwidth occupancy of the corresponding IT device, and use the predicted bandwidth occupancy of each IT device as the predicted bandwidth occupancy of the coordinate point corresponding to the corresponding IT device, so as to obtain the predicted bandwidth occupancy of all monitoring nodes of the Internet of Things at the current moment;

[0040] The second control submodule is used to determine whether the sum of the predicted bandwidth occupancy of all monitoring nodes of the Internet of Things at the current moment is greater than the total network bandwidth of the Internet of Things. If so, the quotient between the total network bandwidth of the Internet of Things and the total number of all monitoring nodes of the Internet of Things at the current moment is used as the allocated bandwidth occupancy of each monitoring node of the Internet of Things at the current moment. Otherwise, the predicted bandwidth occupancy of each monitoring node of the Internet of Things at the current moment is used as the allocated bandwidth occupancy of the corresponding monitoring node of the Internet of Things at the current moment to obtain the remote monitoring result of the Internet of Things at the current moment.

[0041] The beneficial effects of the present invention compared with the prior art are as follows: according to the processed values ​​of all types of historical fault data of each IT device at all times within a preset time period before the current moment, the processed values ​​of all types of resource consumption data and the processed values ​​of all types of security threat data, the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment are obtained, so as to quantify the fault degree, resource consumption degree and security threat degree of each IT device at the current moment, and then according to the fault assessment values, resource consumption assessment values ​​and security threat assessment values ​​of all IT devices at the current moment, a spatial node connection diagram of the Internet of Things at the current moment is obtained, which is convenient for the subsequent determination of monitoring nodes, and according to the spatial node connection diagram of the Internet of Things at the current moment, all monitoring nodes of the Internet of Things at the current moment are obtained, so as to accurately screen out the coordinate points of the IT devices that need to be monitored among all IT devices of the Internet of Things at the current moment, and finally according to all monitoring nodes of the Internet of Things at the current moment, the remote monitoring result of the Internet of Things at the current moment is obtained, so as to achieve the optimal allocation of bandwidth for all IT devices of the Internet of Things, improve the monitoring efficiency and ensure the overall quality of the monitoring data.

[0042] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structure specifically pointed out in the written application document.

[0043] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 Schematic diagram of a remote monitoring system for IT equipment based on the Internet of Things in an embodiment of the present invention;

[0046] Figure 2 Detailed diagram of the monitoring module in the embodiment of the present invention. DETAILED DESCRIPTION

[0047] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0048] Embodiment 1:

[0049] The present invention provides an IT equipment remote monitoring system based on the Internet of Things, referring to Figure 1 ,include:

[0050] A monitoring module, for obtaining, based on all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current time, processed values ​​of all types of historical fault data, processed values ​​of all types of resource consumption data and processed values ​​of all types of security threat data of each IT device at the current time;

[0051] A calculation module, used to obtain a fault assessment value, a resource consumption assessment value, and a security threat assessment value of each IT device at the current moment based on the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data, and the processed values ​​of all types of security threat data of each IT device at all times within a preset time period before the current moment;

[0052] A construction module is used to obtain a spatial node connection diagram of the Internet of Things at the current moment based on the fault assessment values, resource consumption assessment values, and security threat assessment values ​​of all IT devices at the current moment, and obtain all monitoring nodes of the Internet of Things at the current moment based on the spatial node connection diagram of the Internet of Things at the current moment;

[0053] The control module is used to obtain the remote monitoring result of the Internet of Things at the current moment based on all monitoring nodes of the Internet of Things at the current moment.

[0054] In this embodiment, the IT equipment is IT equipment that is remotely monitored and managed through the Internet of Things technology, such as servers, routers, switches, etc.

[0055] In this embodiment, the preset time period is a time period preset to obtain all types of historical fault data, all types of resource consumption data, and all types of security threat data.

[0056] In this embodiment, all moments are all moments selected from a preset time period before the current moment, and the time length between each adjacent moment is the same.

[0057] In this embodiment, all types of historical fault data are all data that can reflect the historical fault records of IT equipment in the IT equipment remote monitoring system based on the Internet of Things, including the number of new faults, the time to resolve new faults, and the star rating of the difficulty of maintaining new faults.

[0058] In this embodiment, all types of resource consumption data are all data that can reflect the resource consumption of IT equipment in the IT equipment remote monitoring system based on the Internet of Things, including CPU usage, memory occupancy and network bandwidth occupancy.

[0059] In this embodiment, all types of security threat data are all data that can reflect the security threats suffered by IT equipment in the remote monitoring system of IT equipment based on the Internet of Things, including the number of new intrusion detections and the number of vulnerability scans.

[0060] In this embodiment, the processed value of all types of historical fault data at the current moment is a value that can comprehensively reflect the comprehensive situation of all types of historical fault data of each IT device within a preset time period before the current moment.

[0061] In this embodiment, the processed value of all resource consumption data of the current moment is a value that can overall reflect the comprehensive situation of all resource consumption data of each IT device in a preset time period before the current moment.

[0062] In this embodiment, the processed value of all types of security threat data at the current moment is a value that can comprehensively reflect the comprehensive situation of all types of security threat data of each IT device within a preset time period before the current moment.

[0063] In this embodiment, the fault assessment value at the current moment is a value evaluated based on the processed values ​​of all types of historical fault data of each IT device at all times within a preset time period before the current moment, which can reflect the fault degree of each IT device at the current moment.

[0064] In this embodiment, the resource consumption evaluation value at the current moment is a value evaluated based on the processed values ​​of all types of resource consumption data of each IT device at all times within a preset time period before the current moment, which can reflect the resource consumption level of each IT device at the current moment.

[0065] In this embodiment, the security threat assessment value at the current moment is a value evaluated based on the processed values ​​of all types of security threat data of each IT device at all times within a preset time period before the current moment, which can reflect the degree of security threat suffered by each IT device at the current moment.

[0066] In this embodiment, the spatial node connection diagram of the Internet of Things at the current moment is a connection diagram of the corresponding coordinate points of all IT devices in the Internet of Things obtained based on the fault assessment values, resource consumption assessment values ​​and security threat assessment values ​​of all IT devices at the current moment.

[0067] In this embodiment, all monitoring nodes of the Internet of Things at the current moment are coordinate points of IT devices that need to be monitored among all IT devices of the Internet of Things at the current moment.

[0068] In this embodiment, the remote monitoring result of the Internet of Things at the current moment is to monitor the running processes and services, log files, patches and updates of IT devices corresponding to all monitoring nodes of the Internet of Things at the current moment.

[0069] The beneficial effects of the above technology are as follows: according to the processed values ​​of all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current moment, the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment are obtained, so as to quantify the fault degree, resource consumption degree and security threat degree of each IT device at the current moment, and then according to the fault assessment value, resource consumption assessment value and security threat assessment value of all IT devices at the current moment, the spatial node connection diagram of the Internet of Things at the current moment is obtained, which is convenient for the subsequent determination of monitoring nodes, and according to the spatial node connection diagram of the Internet of Things at the current moment, all monitoring nodes of the Internet of Things at the current moment are obtained, so as to accurately screen out the coordinate points of the IT devices that need to be monitored among all IT devices of the Internet of Things at the current moment, and finally according to all monitoring nodes of the Internet of Things at the current moment, the remote monitoring result of the Internet of Things at the current moment is obtained, so as to achieve the optimal allocation of bandwidth for all IT devices of the Internet of Things, improve the monitoring efficiency and ensure the overall quality of the monitoring data.

[0070] Embodiment 2:

[0071] Based on Example 1, the remote monitoring system for IT equipment based on the Internet of Things, the monitoring module, reference Figure 2 ,include:

[0072] The monitoring acquisition submodule obtains all types of historical fault data, all types of resource consumption data, and all types of security threat data of each IT device at all times in the preset time period before the current moment. All types of historical fault data include the number of new faults, the time to solve new faults, and the star rating of the difficulty of new fault maintenance. All types of resource consumption data include CPU usage, memory usage, and network bandwidth usage. All types of security threat data include the number of new intrusion detections and vulnerability scans.

[0073] The processing submodule is used to process all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current moment, and obtain the processed values ​​of all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at the current moment.

[0074] In this embodiment, the number of newly added faults is the number of newly added faults detected by each IT device at each moment in a preset time period before the current moment.

[0075] In this embodiment, the newly added fault resolution time is the total time required to resolve all newly added faults detected by each IT device at each moment within a preset time period before the current moment, as estimated by backend personnel.

[0076] In this embodiment, the star rating of the difficulty of maintaining a new fault is the star rating of the maintenance difficulty of the new fault with the highest repair difficulty estimated by the backend staff among all the new faults detected by each IT device at each moment in a preset time period before the current moment (the star rating evaluation of the difficulty of the new fault dimension given by the backend staff).

[0077] In this embodiment, the CPU usage rate is the CPU usage rate of each IT device at each moment in a preset time period before the current moment.

[0078] In this embodiment, the memory occupancy rate is the memory occupancy rate of each IT device at each moment in a preset time period before the current moment.

[0079] In this embodiment, the network bandwidth occupancy is the network bandwidth occupancy of each IT device at each moment in a preset time period before the current moment (the amount of data transmitted by each IT device through the Internet of Things network per unit time).

[0080] In this embodiment, the number of newly added intrusion detections is the number of newly added external attacks and internal illegal operations detected by each IT device at each moment in a preset time period before the current moment.

[0081] In this embodiment, the vulnerability scan number is the number of vulnerabilities scanned by each IT device at each moment in a preset time period before the current moment.

[0082] In this embodiment, data processing is a process of obtaining the processing values ​​of all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at the current moment based on all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all moments within a preset time period before the current moment.

[0083] The beneficial effects of the above technology are: clarifying the specific data items of all types of historical fault data, all types of resource consumption data and all types of security threat data, and based on all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current moment, obtaining the processed values ​​of all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at the current moment, which is convenient for the calculation of subsequent fault assessment values, resource consumption assessment values ​​and security threat assessment values.

[0084] Embodiment 3:

[0085] On the basis of Example 2, the remote monitoring system for IT equipment based on the Internet of Things, the processing submodule includes:

[0086] A first processing unit is used to use the difference and sum of the values ​​of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before the current moment and the standard deviation of the values ​​of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device at all times within the preset time period before the current moment as the lower limit and upper limit of the value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device;

[0087] A second processing unit is used to use a set of all values ​​of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before a current moment, which are not less than a lower limit of a value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data, and whose corresponding values ​​are not greater than an upper limit of a value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data, as a statistical set of the corresponding type of historical fault data or a statistical set of the corresponding type of resource consumption data or a statistical set of the corresponding type of security threat data of the corresponding IT device, and use a set consisting of all data that does not belong to the statistical set of the corresponding type of historical fault data or the statistical set of the corresponding type of resource consumption data or the statistical set of the corresponding type of security threat data of each IT device in each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before a current moment, as a preliminary supplementary statistical set of the corresponding type of historical fault data or a preliminary supplementary statistical set of the corresponding type of resource consumption data or a preliminary supplementary statistical set of the corresponding type of security threat data of the corresponding IT device;

[0088] The third processing unit is used to obtain the processing value of each type of historical fault data or the processing value of each type of resource consumption data or the processing value of each type of security threat data of each IT device at the current moment based on the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device and a preset statistical threshold.

[0089] In this embodiment, the preset statistical threshold is a statistical threshold that is pre-set to obtain the processing value of each type of historical fault data or the processing value of each type of resource consumption data or the processing value of each type of security threat data of each IT device at the current moment, and the statistical set of all types of historical fault data, the statistical set of all types of resource consumption data, and the statistical set of all types of security threat data correspond to the same preset statistical threshold.

[0090] The beneficial effects of the above technology are: according to each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before the current moment, the lower limit and upper limit of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device are obtained, and then according to the lower limit and upper limit of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device, a statistical set of each type of historical fault data or a statistical set of each type of resource consumption data or a statistical set of each type of security threat data of each IT device is obtained; finally, according to the statistical set of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device, the processed value of each type of historical fault data or the processed value of each type of resource consumption data or the processed value of each type of security threat data of each IT device at the current moment is accurately obtained, which is convenient for the calculation of subsequent fault assessment values, resource consumption assessment values ​​and security threat assessment values.

[0091] Embodiment 4:

[0092] On the basis of Example 3, in the remote monitoring system for IT equipment based on the Internet of Things, the third processing unit obtains a method for obtaining a processing value of each type of historical fault data or a processing value of each type of resource consumption data or a processing value of each type of security threat data of each IT device at the current moment based on the number of elements of the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device and a preset statistical threshold, including:

[0093] Determine whether the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device is not less than a preset statistical threshold; if so, use the average of the values ​​of all elements in the statistical set of the corresponding type of historical fault data or the statistical set of the corresponding type of resource consumption data or the statistical set of the corresponding type of security threat data of the corresponding IT device as the processed value of the corresponding type of historical fault data or the processed value of the corresponding type of resource consumption data or the processed value of the corresponding type of security threat data of the corresponding IT device at the current moment;

[0094] Otherwise, the absolute value of the difference between the number of elements in the statistical set of each type of historical fault data of each IT device or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data and the preset statistical threshold is used as the supplementary number of the corresponding type of historical fault data of the corresponding IT device or the supplementary number of the corresponding type of resource consumption data or the supplementary number of the corresponding type of security threat data, and the preliminary supplementary statistical set of the corresponding type of historical fault data of the corresponding IT device or the preliminary supplementary statistical set of the corresponding type of resource consumption data of the corresponding IT device is calculated according to the supplementary number of each type of historical fault data of each IT device or the supplementary number of each type of resource consumption data or the supplementary number of each type of security threat data. Elements are extracted from the supplementary statistical set or the prepared supplementary statistical set of the corresponding class of security threat data to obtain a supplementary statistical set of each class of historical fault data of each IT device or a supplementary statistical set of each class of resource consumption data or a supplementary statistical set of each class of security threat data, and the average of the values ​​of all elements in the supplementary statistical set of each class of historical fault data of each IT device or a supplementary statistical set of each class of resource consumption data or a supplementary statistical set of each class of security threat data is used as the processed value of the corresponding class of historical fault data or the processed value of the corresponding class of resource consumption data or the processed value of the corresponding class of security threat data of the corresponding IT device at the current moment.

[0095] In this embodiment, according to the supplementary number of each type of historical fault data of each IT device, the supplementary number of each type of resource consumption data, or the supplementary number of each type of security threat data, the element extraction is performed on the preliminary supplementary statistical set of the corresponding type of historical fault data of the corresponding IT device, the preliminary supplementary statistical set of the corresponding type of resource consumption data, or the preliminary supplementary statistical set of the corresponding type of security threat data, to obtain the supplementary statistical set of each type of historical fault data of each IT device, the supplementary statistical set of each type of resource consumption data, or the supplementary statistical set of each type of security threat data, which is:

[0096] The interval range determined by the lower limit and the upper limit of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device is used as the extraction range of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device, and multiple elements (the number of multiple elements corresponds to each type of historical fault data of each IT device) that are closest to the extraction range of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device among all elements of the preliminary supplementary statistical set of each type of historical fault data of each IT device or the preliminary supplementary statistical set of each type of resource consumption data or the preliminary supplementary statistical set of each type of security threat data are taken as the extraction range of each type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device. The supplementary number of each type of historical fault data or the supplementary number of each type of resource consumption data or the supplementary number of each type of security threat data) is used as the supplementary element of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT equipment, and the supplementary element of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT equipment is added to the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT equipment to obtain the supplementary statistical set of each type of historical fault data or the supplementary statistical set of each type of resource consumption data or the supplementary statistical set of each type of security threat data of each IT equipment.

[0097] The beneficial effects of the above technology are: a specific method is given in detail based on the number of elements in the statistical set of each type of historical fault data of each IT device, or the statistical set of each type of resource consumption data, or the statistical set of each type of security threat data, and the preset statistical threshold, to obtain the processing value of each type of historical fault data, or the processing value of each type of resource consumption data, or the processing value of each type of security threat data of each IT device at the current moment, which facilitates the calculation of subsequent fault assessment values, resource consumption assessment values, and security threat assessment values.

[0098] Embodiment 5:

[0099] Based on Example 1, the remote monitoring system for IT equipment based on the Internet of Things, the computing module includes:

[0100] A preparation submodule, used to obtain the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data, and the processed values ​​of all types of security threat data of all IT devices at all times within a preset time period before the current moment, and use the average of the processed values ​​of each type of historical fault data or the processed values ​​of each type of resource consumption data or the processed values ​​of each type of security threat data of each IT device at all times within the preset time period before the current moment as a reference average value of the corresponding type of historical fault data or the reference average value of the corresponding type of resource consumption data or the reference average value of the corresponding type of security threat data of the corresponding IT device at the current moment;

[0101] The calculation submodule is used to obtain the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment based on the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT device at the current moment.

[0102] The beneficial effect of the above technology is: according to the processed values ​​of each type of historical fault data or the processed values ​​of each type of resource consumption data or the processed values ​​of each type of security threat data of each IT device at all times within a preset time period before the current moment, the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT device at the current moment is obtained; then, according to the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT device at the current moment, the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment are obtained, thereby realizing the quantification of the fault degree, resource consumption degree and security threat degree of each IT device at the current moment.

[0103] Embodiment 6:

[0104] On the basis of Example 5, in the remote monitoring system for IT equipment based on the Internet of Things, the calculation submodule obtains the fault assessment value, resource consumption assessment value and security threat assessment value of each IT equipment at the current moment based on the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT equipment at the current moment, including:

[0105]

[0106]

[0107] Among them, α is the fault assessment value of the IT equipment currently calculated at the current moment, β is the resource consumption assessment value of the IT equipment currently calculated at the current moment, γ is the security threat assessment value of the IT equipment currently calculated at the current moment, C is the reference mean of the number of new faults of the IT equipment currently calculated at the current moment, c is the processing value of the number of new faults of the IT equipment currently calculated at the current moment, and c max c is the maximum value of the number of newly added faults of the IT equipment currently calculated at all times in the preset time period before the current time. minis the minimum value of the processing values ​​of the newly added faults of the IT equipment at all times in the preset time period before the current moment, V is the reference mean value of the newly added fault resolution time of the IT equipment at the current moment, v is the processing value of the newly added fault resolution time of the IT equipment at the current moment, and v max v is the maximum value of the newly added fault resolution time of the IT equipment in the preset time period before the current moment. min is the minimum value of the processing values ​​of the newly added fault resolution time of the IT equipment currently calculated at all times in the preset time period before the current moment, L is the reference mean value of the newly added fault maintenance difficulty star number of the IT equipment currently calculated at the current moment, l is the processing value of the newly added fault maintenance difficulty star number of the IT equipment currently calculated at the current moment, l max is the maximum value of the processed values ​​of the newly added fault maintenance difficulty stars of the IT equipment at all times in the preset time period before the current moment, l min is the minimum value of the processed values ​​of the newly added fault maintenance difficulty stars of the IT equipment currently calculated at all times in the preset time period before the current moment, Q is the reference mean value of the CPU utilization rate of the IT equipment currently calculated at the current moment, q is the processed value of the CPU utilization rate of the IT equipment currently calculated at the current moment, and q max The maximum value of the CPU usage of the IT equipment in the preset time period before the current moment. min is the minimum value of the CPU usage of the IT device currently calculated at all times in the preset time period before the current moment, W is the reference mean value of the memory occupancy of the IT device currently calculated at the current moment, w is the processed value of the memory occupancy of the IT device currently calculated at the current moment, w max is the maximum value of the memory usage of the IT device currently calculated at all times in the preset time period before the current time, w min is the minimum value of the processed values ​​of the memory occupancy rate of the currently calculated IT device at all times in the preset time period before the current moment, R is the reference mean value of the network bandwidth occupancy of the currently calculated IT device at the current moment, r is the processed value of the network bandwidth occupancy of the currently calculated IT device at the current moment, and r max is the maximum value of the network bandwidth occupied by the IT equipment at all times in the preset time period before the current moment, r min is the minimum value of the processed values ​​of the network bandwidth occupied by the currently calculated IT equipment at all times in the preset time period before the current moment, E is the reference mean value of the number of new intrusion detections of the currently calculated IT equipment at the current moment, e is the processed value of the number of new intrusion detections of the currently calculated IT equipment at the current moment, and emax is the maximum value of the number of newly added intrusion detections of the IT equipment at all times in the preset time period before the current time. min is the minimum value of the processed values ​​of the newly added intrusion detection times of the currently calculated IT equipment at all times in the preset time period before the current moment, T is the reference mean value of the vulnerability scan times of the currently calculated IT equipment at the current moment, t is the processed value of the vulnerability scan times of the currently calculated IT equipment at the current moment, t max The maximum value of the vulnerability scan count of the IT device currently being calculated at all times within the preset time period before the current time. min It is the minimum value among the processed values ​​of the vulnerability scan numbers of the currently calculated IT equipment at all times in the preset time period before the current time. ln is the natural logarithm, and the value of the natural constant e is 2.718.

[0108] The beneficial effect of the above technology is: according to the reference mean of each type of historical fault data or the reference mean of each type of resource consumption data or the reference mean of each type of security threat data of each IT device at the current moment, the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment are obtained, so that the fault degree, resource consumption degree and security threat degree of each IT device at the current moment are quantified. This embodiment gives in detail a specific method for quantifying the fault degree, resource consumption degree and security threat degree of each IT device at the current moment.

[0109] Embodiment 7:

[0110] Based on Example 1, the remote monitoring system for IT equipment based on the Internet of Things, the building blocks include:

[0111] A coordinate determination submodule, used to obtain the coordinate point of each IT device by taking the fault assessment value of each IT device at the current moment as the horizontal coordinate value, the resource consumption assessment value of the corresponding IT device at the current moment as the vertical coordinate value, and the security threat assessment value of the corresponding IT device at the current moment as the vertical coordinate value;

[0112] A submodule is constructed, which is used to treat two different IT devices among all IT devices as a group of IT devices, obtain all groups of IT devices, and if two IT devices in each group of IT devices have information interaction within a preset time period before the current moment, connect the coordinate points of the two IT devices in the corresponding group of IT devices to obtain a spatial node connection diagram of the Internet of Things at the current moment;

[0113] The node analysis submodule is used to obtain all monitoring nodes of the Internet of Things at the current moment based on the spatial node connection diagram of the Internet of Things at the current moment.

[0114] In this embodiment, information interaction is an action in which an IT device in the Internet of Things sends a data request to another IT device and receives a corresponding response.

[0115] The beneficial effects of the above technology are: based on the fault assessment values, resource consumption assessment values ​​and security threat assessment values ​​of all IT equipment at the current moment, the spatial node connection diagram of the Internet of Things at the current moment is obtained, which is convenient for the subsequent determination of monitoring nodes. According to the spatial node connection diagram of the Internet of Things at the current moment, all monitoring nodes of the Internet of Things at the current moment are obtained, and the coordinate points of the IT equipment that needs to be monitored among all IT equipment in the Internet of Things at the current moment are accurately screened out.

[0116] Embodiment 8:

[0117] Based on Example 7, the node analysis submodule of the remote monitoring system for IT equipment based on the Internet of Things includes:

[0118] A preparation unit is used to use the number of coordinate points connected to each coordinate point among all coordinate points of the spatial node connection diagram of the Internet of Things at the current moment as the number of connections of the corresponding coordinate point, and use the directly connected coordinate point farthest from the corresponding coordinate point among all directly connected coordinate points of each coordinate point as the farthest directly connected coordinate point of each coordinate point, use the distance between each coordinate point and the farthest directly connected coordinate point of the corresponding coordinate point as the farthest directly connected distance of the corresponding coordinate point, use the directly connected coordinate point closest to the corresponding coordinate point among all directly connected coordinate points of each coordinate point as the nearest directly connected coordinate point of each coordinate point, and use the distance between each coordinate point and the nearest directly connected coordinate point of the corresponding coordinate point as the nearest directly connected distance of the corresponding coordinate point;

[0119] A calculation unit, for obtaining the degree of necessity of monitoring each coordinate point in the spatial node connection graph of the Internet of Things at the current moment based on the number of connections, the farthest direct connection distance, and the closest direct connection distance of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment;

[0120] The analysis unit is used to use the corresponding coordinate point as the monitoring node of the Internet of Things at the current moment when the monitoring necessity of each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment is greater than a preset necessity threshold.

[0121] In this embodiment, the degree of necessity for monitoring is a numerical value obtained based on the number of connections, the farthest direct connection distance, and the closest direct connection distance of all coordinate points in the spatial node connection diagram of the Internet of Things at the current moment, which can reflect the degree of necessity for monitoring the IT equipment corresponding to each coordinate point at the current moment.

[0122] In this embodiment, the preset necessity threshold is a threshold preset to obtain the monitoring necessity of the monitoring node of the Internet of Things at the current moment.

[0123] The beneficial effects of the above technology are: according to the spatial node connection diagram of the Internet of Things at the current moment, the number of connections, the farthest direct connection distance and the nearest direct connection distance of all coordinate points in the spatial node connection diagram of the Internet of Things at the current moment are obtained, and then according to the number of connections, the farthest direct connection distance and the nearest direct connection distance of all coordinate points in the spatial node connection diagram of the Internet of Things at the current moment, the necessity of monitoring each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment is accurately obtained; finally, according to the necessity of monitoring each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment and the preset necessity threshold, all monitoring nodes of the Internet of Things at the current moment are obtained, and the IT equipment that most needs to be monitored is screened out, avoiding blind monitoring and reducing unnecessary resource consumption.

[0124] Embodiment 9:

[0125] On the basis of Example 8, in the remote monitoring system for IT equipment based on the Internet of Things, the calculation unit obtains the monitoring necessity of each coordinate point in the spatial node connection graph of the Internet of Things at the current moment based on the number of connections, the farthest direct connection distance and the nearest direct connection distance of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, including:

[0126]

[0127] Where, ρ is the monitoring necessity of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, n is the total number of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, m is the number of connections of the currently calculated coordinate points in the spatial node connection graph of the Internet of Things at the current moment, and m 0 is the mean value of the number of connections of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, φ is the mean value of the farthest direct connection distance of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, and u max is the farthest direct connection distance of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, u min is the nearest direct connection distance of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, ω is the mean of the nearest direct connection distances of all coordinate points of the spatial node connection graph of the Internet of Things at the current moment, ln is the natural logarithm, and the value of the natural constant e is 2.718.

[0128] The beneficial effects of the above technology are: based on the number of connections of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, the farthest direct connection distance and the nearest direct connection distance, the necessity of monitoring each coordinate point in the spatial node connection graph of the Internet of Things at the current moment is accurately obtained, and a quantitative evaluation of the necessity of monitoring the IT equipment corresponding to each coordinate point at the current moment is achieved. This embodiment gives in detail a specific method for accurately obtaining the necessity of monitoring each coordinate point in the spatial node connection graph of the Internet of Things at the current moment based on the number of connections of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, the farthest direct connection distance and the nearest direct connection distance.

[0129] Embodiment 10:

[0130] Based on Example 1, the remote monitoring system for IT equipment based on the Internet of Things, the control module includes:

[0131] The first control submodule is used to use the maximum value of the processed values ​​of the network bandwidth occupancy of each IT device at all times within a preset time period before the current moment as the predicted bandwidth occupancy of the corresponding IT device, and use the predicted bandwidth occupancy of each IT device as the predicted bandwidth occupancy of the coordinate point corresponding to the corresponding IT device, so as to obtain the predicted bandwidth occupancy of all monitoring nodes of the Internet of Things at the current moment;

[0132] The second control submodule is used to determine whether the sum of the predicted bandwidth occupancy of all monitoring nodes of the Internet of Things at the current moment is greater than the total network bandwidth of the Internet of Things. If so, the quotient between the total network bandwidth of the Internet of Things and the total number of all monitoring nodes of the Internet of Things at the current moment is used as the allocated bandwidth occupancy of each monitoring node of the Internet of Things at the current moment. Otherwise, the predicted bandwidth occupancy of each monitoring node of the Internet of Things at the current moment is used as the allocated bandwidth occupancy of the corresponding monitoring node of the Internet of Things at the current moment to obtain the remote monitoring result of the Internet of Things at the current moment.

[0133] In this embodiment, the total network bandwidth of the Internet of Things is the total amount of data that can be transmitted by all IT devices in the Internet of Things per unit time.

[0134] In this embodiment, the allocated bandwidth occupancy is the bandwidth allocated to the IT device corresponding to each monitoring node of the Internet of Things at the current moment.

[0135] The beneficial effects of the above technology are: based on all monitoring nodes of the Internet of Things at the current moment, the remote monitoring results of the Internet of Things at the current moment are obtained, the optimal allocation of bandwidth for all IT devices of the Internet of Things is achieved, the monitoring efficiency is improved, and the overall quality of the monitoring data is guaranteed.

[0136] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention, and the present invention is also intended to include these changes and modifications.

Claims

1. A remote monitoring system for IT equipment based on the Internet of Things, characterized in that: include: A monitoring module, for obtaining, based on all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current time, processed values ​​of all types of historical fault data, processed values ​​of all types of resource consumption data and processed values ​​of all types of security threat data of each IT device at the current time; A calculation module, used to obtain a fault assessment value, a resource consumption assessment value, and a security threat assessment value of each IT device at the current moment based on the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data, and the processed values ​​of all types of security threat data of each IT device at all times within a preset time period before the current moment; A construction module is used to obtain a spatial node connection diagram of the Internet of Things at the current moment based on the fault assessment values, resource consumption assessment values, and security threat assessment values ​​of all IT devices at the current moment, and obtain all monitoring nodes of the Internet of Things at the current moment based on the spatial node connection diagram of the Internet of Things at the current moment; The control module is used to obtain the remote monitoring result of the Internet of Things at the current moment based on all monitoring nodes of the Internet of Things at the current moment.

2. The remote monitoring system for IT equipment based on the Internet of Things according to claim 1 is characterized in that: Monitoring module, including: The monitoring acquisition submodule obtains all types of historical fault data, all types of resource consumption data, and all types of security threat data of each IT device at all times in the preset time period before the current moment. All types of historical fault data include the number of new faults, the time to solve new faults, and the star rating of the difficulty of new fault maintenance. All types of resource consumption data include CPU usage, memory usage, and network bandwidth usage. All types of security threat data include the number of new intrusion detections and vulnerability scans. The processing submodule is used to process all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at all times within a preset time period before the current moment, and obtain the processed values ​​of all types of historical fault data, all types of resource consumption data and all types of security threat data of each IT device at the current moment.

3. The remote monitoring system for IT equipment based on the Internet of Things according to claim 2 is characterized in that: Processing submodules, including: A first processing unit is used to use the difference and sum of the values ​​of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before the current moment and the standard deviation of the values ​​of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device at all times within the preset time period before the current moment as the lower limit and upper limit of the value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data of the corresponding IT device; A second processing unit is used to use a set of all values ​​of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before a current moment, which are not less than a lower limit of a value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data, and whose corresponding values ​​are not greater than an upper limit of a value of the corresponding type of historical fault data or the corresponding type of resource consumption data or the corresponding type of security threat data, as a statistical set of the corresponding type of historical fault data or a statistical set of the corresponding type of resource consumption data or a statistical set of the corresponding type of security threat data of the corresponding IT device, and use a set consisting of all data that does not belong to the statistical set of the corresponding type of historical fault data or the statistical set of the corresponding type of resource consumption data or the statistical set of the corresponding type of security threat data of each IT device in each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at all times within a preset time period before a current moment, as a preliminary supplementary statistical set of the corresponding type of historical fault data or a preliminary supplementary statistical set of the corresponding type of resource consumption data or a preliminary supplementary statistical set of the corresponding type of security threat data of the corresponding IT device; The third processing unit is used to obtain the processing value of each type of historical fault data or the processing value of each type of resource consumption data or the processing value of each type of security threat data of each IT device at the current moment based on the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device and a preset statistical threshold.

4. The remote monitoring system for IT equipment based on the Internet of Things according to claim 3 is characterized in that: The method in which the third processing unit obtains a processing value of each type of historical fault data or each type of resource consumption data or each type of security threat data of each IT device at the current moment based on the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device and a preset statistical threshold includes: Determine whether the number of elements in the statistical set of each type of historical fault data or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data of each IT device is not less than a preset statistical threshold; if so, use the average of the values ​​of all elements in the statistical set of the corresponding type of historical fault data or the statistical set of the corresponding type of resource consumption data or the statistical set of the corresponding type of security threat data of the corresponding IT device as the processed value of the corresponding type of historical fault data or the processed value of the corresponding type of resource consumption data or the processed value of the corresponding type of security threat data of the corresponding IT device at the current moment; Otherwise, the absolute value of the difference between the number of elements in the statistical set of each type of historical fault data of each IT device or the statistical set of each type of resource consumption data or the statistical set of each type of security threat data and the preset statistical threshold is used as the supplementary number of the corresponding type of historical fault data of the corresponding IT device or the supplementary number of the corresponding type of resource consumption data or the supplementary number of the corresponding type of security threat data, and the preliminary supplementary statistical set of the corresponding type of historical fault data of the corresponding IT device or the preliminary supplementary statistical set of the corresponding type of resource consumption data of the corresponding IT device is calculated according to the supplementary number of each type of historical fault data of each IT device or the supplementary number of each type of resource consumption data or the supplementary number of each type of security threat data. Elements are extracted from the supplementary statistical set or the prepared supplementary statistical set of the corresponding class of security threat data to obtain a supplementary statistical set of each class of historical fault data of each IT device or a supplementary statistical set of each class of resource consumption data or a supplementary statistical set of each class of security threat data, and the average of the values ​​of all elements in the supplementary statistical set of each class of historical fault data of each IT device or a supplementary statistical set of each class of resource consumption data or a supplementary statistical set of each class of security threat data is used as the processed value of the corresponding class of historical fault data or the processed value of the corresponding class of resource consumption data or the processed value of the corresponding class of security threat data of the corresponding IT device at the current moment.

5. The remote monitoring system for IT equipment based on the Internet of Things according to claim 1, characterized in that: Computing module, including: A preparation submodule, used to obtain the processed values ​​of all types of historical fault data, the processed values ​​of all types of resource consumption data, and the processed values ​​of all types of security threat data of all IT devices at all times within a preset time period before the current moment, and use the average of the processed values ​​of each type of historical fault data or the processed values ​​of each type of resource consumption data or the processed values ​​of each type of security threat data of each IT device at all times within the preset time period before the current moment as a reference average value of the corresponding type of historical fault data or the reference average value of the corresponding type of resource consumption data or the reference average value of the corresponding type of security threat data of the corresponding IT device at the current moment; The calculation submodule is used to obtain the fault assessment value, resource consumption assessment value and security threat assessment value of each IT device at the current moment based on the reference mean value of each type of historical fault data or the reference mean value of each type of resource consumption data or the reference mean value of each type of security threat data of each IT device at the current moment.

6. The remote monitoring system for IT equipment based on the Internet of Things according to claim 5, characterized in that: The calculation submodule obtains a method for obtaining a fault assessment value, a resource consumption assessment value, and a security threat assessment value of each IT device at the current moment based on a reference mean value of each type of historical fault data or a reference mean value of each type of resource consumption data or a reference mean value of each type of security threat data of each IT device at the current moment, including: Among them, α is the fault assessment value of the IT equipment currently calculated at the current moment, β is the resource consumption assessment value of the IT equipment currently calculated at the current moment, γ is the security threat assessment value of the IT equipment currently calculated at the current moment, C is the reference mean of the number of new faults of the IT equipment currently calculated at the current moment, c is the processing value of the number of new faults of the IT equipment currently calculated at the current moment, and c max c is the maximum value of the number of newly added faults of the IT equipment currently calculated at all times in the preset time period before the current time. min is the minimum value of the processing values ​​of the newly added faults of the IT equipment at all times in the preset time period before the current moment, V is the reference mean value of the newly added fault resolution time of the IT equipment at the current moment, v is the processing value of the newly added fault resolution time of the IT equipment at the current moment, and v max v is the maximum value of the newly added fault resolution time of the IT equipment in the preset time period before the current moment. min is the minimum value of the processing values ​​of the newly added fault resolution time of the IT equipment currently calculated at all times in the preset time period before the current moment, L is the reference mean value of the newly added fault maintenance difficulty star number of the IT equipment currently calculated at the current moment, l is the processing value of the newly added fault maintenance difficulty star number of the IT equipment currently calculated at the current moment, l max is the maximum value of the processed values ​​of the newly added fault maintenance difficulty stars of the IT equipment at all times in the preset time period before the current moment, l min is the minimum value of the processed values ​​of the newly added fault maintenance difficulty stars of the IT equipment currently calculated at all times in the preset time period before the current moment, Q is the reference mean value of the CPU utilization rate of the IT equipment currently calculated at the current moment, q is the processed value of the CPU utilization rate of the IT equipment currently calculated at the current moment, and q max The maximum value of the CPU usage of the IT equipment in the preset time period before the current moment. min is the minimum value of the CPU usage of the IT device currently calculated at all times in the preset time period before the current moment, W is the reference mean value of the memory occupancy of the IT device currently calculated at the current moment, w is the processed value of the memory occupancy of the IT device currently calculated at the current moment, w max is the maximum value of the memory usage of the IT device currently calculated at all times in the preset time period before the current time, w min is the minimum value of the processed values ​​of the memory occupancy rate of the currently calculated IT device at all times in the preset time period before the current moment, R is the reference mean value of the network bandwidth occupancy of the currently calculated IT device at the current moment, r is the processed value of the network bandwidth occupancy of the currently calculated IT device at the current moment, and r max is the maximum value of the network bandwidth occupied by the IT equipment at all times in the preset time period before the current moment, r min is the minimum value of the processed values ​​of the network bandwidth occupied by the currently calculated IT equipment at all times in the preset time period before the current moment, E is the reference mean value of the number of new intrusion detections of the currently calculated IT equipment at the current moment, e is the processed value of the number of new intrusion detections of the currently calculated IT equipment at the current moment, and e max is the maximum value of the number of newly added intrusion detections of the IT equipment at all times in the preset time period before the current time. min is the minimum value of the processed values ​​of the newly added intrusion detection times of the currently calculated IT equipment at all times in the preset time period before the current moment, T is the reference mean value of the vulnerability scan times of the currently calculated IT equipment at the current moment, t is the processed value of the vulnerability scan times of the currently calculated IT equipment at the current moment, t max The maximum value of the vulnerability scan count of the IT device currently being calculated at all times within the preset time period before the current time. min It is the minimum value among the processed values ​​of the vulnerability scan numbers of the currently calculated IT equipment at all times in the preset time period before the current time. ln is the natural logarithm, and the value of the natural constant e is 2.

718.

7. The remote monitoring system for IT equipment based on the Internet of Things according to claim 1, characterized in that: Building blocks, including: A coordinate determination submodule, used to obtain the coordinate point of each IT device by taking the fault assessment value of each IT device at the current moment as the horizontal coordinate value, the resource consumption assessment value of the corresponding IT device at the current moment as the vertical coordinate value, and the security threat assessment value of the corresponding IT device at the current moment as the vertical coordinate value; A submodule is constructed, which is used to treat two different IT devices among all IT devices as a group of IT devices, obtain all groups of IT devices, and if two IT devices in each group of IT devices have information interaction within a preset time period before the current moment, connect the coordinate points of the two IT devices in the corresponding group of IT devices to obtain a spatial node connection diagram of the Internet of Things at the current moment; The node analysis submodule is used to obtain all monitoring nodes of the Internet of Things at the current moment based on the spatial node connection diagram of the Internet of Things at the current moment.

8. The remote monitoring system for IT equipment based on the Internet of Things according to claim 7, characterized in that: Node analysis submodule, including: A preparation unit is used to use the number of coordinate points connected to each coordinate point among all coordinate points of the spatial node connection diagram of the Internet of Things at the current moment as the number of connections of the corresponding coordinate point, and use the directly connected coordinate point farthest from the corresponding coordinate point among all directly connected coordinate points of each coordinate point as the farthest directly connected coordinate point of each coordinate point, use the distance between each coordinate point and the farthest directly connected coordinate point of the corresponding coordinate point as the farthest directly connected distance of the corresponding coordinate point, use the directly connected coordinate point closest to the corresponding coordinate point among all directly connected coordinate points of each coordinate point as the nearest directly connected coordinate point of each coordinate point, and use the distance between each coordinate point and the nearest directly connected coordinate point of the corresponding coordinate point as the nearest directly connected distance of the corresponding coordinate point; A calculation unit, for obtaining the degree of necessity of monitoring each coordinate point in the spatial node connection graph of the Internet of Things at the current moment based on the number of connections, the farthest direct connection distance, and the closest direct connection distance of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment; The analysis unit is used to use the corresponding coordinate point as the monitoring node of the Internet of Things at the current moment when the monitoring necessity of each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment is greater than a preset necessity threshold.

9. The remote monitoring system for IT equipment based on the Internet of Things according to claim 8, characterized in that: The method of obtaining the monitoring necessity degree of each coordinate point of the spatial node connection graph of the Internet of Things at the current moment based on the number of connections, the farthest direct connection distance and the closest direct connection distance of all coordinate points of the spatial node connection graph of the Internet of Things at the current moment by the calculation unit includes: Among them, ρ is the monitoring necessity of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, n is the total number of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, m is the number of connections of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, m0 is the mean number of connections of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, is the mean of the longest direct connection distances of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment, u max is the farthest direct connection distance of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, u min is the nearest direct connection distance of the currently calculated coordinate point of the spatial node connection graph of the Internet of Things at the current moment, ω is the mean of the nearest direct connection distances of all coordinate points of the spatial node connection graph of the Internet of Things at the current moment, ln is the natural logarithm, and the value of the natural constant e is 2.

718.

10. The remote monitoring system for IT equipment based on the Internet of Things according to claim 1, characterized in that: Control module, including: The first control submodule is used to use the maximum value of the processed values ​​of the network bandwidth occupancy of each IT device at all times within a preset time period before the current moment as the predicted bandwidth occupancy of the corresponding IT device, and use the predicted bandwidth occupancy of each IT device as the predicted bandwidth occupancy of the coordinate point corresponding to the corresponding IT device, so as to obtain the predicted bandwidth occupancy of all monitoring nodes of the Internet of Things at the current moment; The second control submodule is used to determine whether the sum of the predicted bandwidth occupancy of all monitoring nodes of the Internet of Things at the current moment is greater than the total network bandwidth of the Internet of Things. If so, the quotient between the total network bandwidth of the Internet of Things and the total number of all monitoring nodes of the Internet of Things at the current moment is used as the allocated bandwidth occupancy of each monitoring node of the Internet of Things at the current moment. Otherwise, the predicted bandwidth occupancy of each monitoring node of the Internet of Things at the current moment is used as the allocated bandwidth occupancy of the corresponding monitoring node of the Internet of Things at the current moment to obtain the remote monitoring result of the Internet of Things at the current moment.

Images