A remote monitoring system for IT equipment based on the Internet of Things

Abstract

The present invention relates to the field of remote monitoring technology for the Internet of Things, and specifically discloses a remote monitoring system for IT equipment based on the Internet of Things, comprising: a calculation module for calculating and obtaining the fault assessment value, resource consumption assessment value, and security threat assessment value of each IT device at the current moment; a construction module for obtaining all monitoring nodes 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 a control module for obtaining remote monitoring results of the Internet of Things at the current moment based on all monitoring nodes of the Internet of Things at the current moment. The present invention accurately screens out the coordinate points of IT devices that need to be monitored among all IT devices in the Internet of Things at the current moment, avoids blind monitoring, reduces unnecessary resource consumption, and achieves optimal bandwidth allocation for all IT devices in the Internet of Things, ensuring the overall quality of monitoring data.

Description

Technical Field

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

[0002] With the rapid development of IoT technology, an increasing number of IT devices are being connected to the network, forming a large and complex system. A technology currently holding broad application prospects in the IoT field is remote monitoring of IT devices based on narrowband IoT (NB-IoT). This approach offers significant advantages in improving monitoring efficiency and reducing costs, particularly in remote, low-power, and wide-coverage application scenarios. While NB-IoT offers wide coverage, its bandwidth is relatively limited. In resource-constrained environments, connecting a large number of IT devices simultaneously for remote monitoring may result in uneven bandwidth allocation, causing data transmission rates on some devices to decrease, impacting the real-time and accuracy of monitoring data. Therefore, the rational allocation of bandwidth resources to ensure that critical IT devices have sufficient bandwidth for data transmission and communication is an urgent issue.

[0003] However, there is no existing remote monitoring system for IT equipment 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 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 based on 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, thereby quantifying the fault degree, resource consumption degree and security threat degree of each IT device at the current moment. Furthermore, based on 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. Based on 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, thereby accurately screening 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. Finally, based on all monitoring nodes of the Internet of Things at the current moment, a remote monitoring result of the Internet of Things at the current moment is obtained, thereby achieving optimal allocation of bandwidth for all IT devices of the Internet of Things, improving monitoring efficiency and ensuring 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 is configured to obtain, 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, a processed value of all types of historical fault data, a processed value of all types of resource consumption data, and a processed value of all types of security threat data of each IT device at the current time;

[0008] a calculation module, configured to obtain a fault assessment value, a resource consumption assessment value, and a security threat assessment value for each IT device at the current moment based on 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 for each IT device at all moments in 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 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;

[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 for each IT device at all times within a preset time period before the current moment. The historical fault data includes the number of new faults, the time it takes to resolve new faults, and the star rating of the difficulty of maintaining new faults. The resource consumption data includes CPU usage, memory usage, and network bandwidth usage. The security threat data includes 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 processing submodule of the remote monitoring system for IT equipment based on the Internet of Things includes:

[0015] a first processing unit, configured to use a difference and a sum of the values of each type of historical fault data, 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, and the standard deviation of the values of the corresponding type of historical fault data, 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 a lower limit and an upper limit of the value of the corresponding type of historical fault data, 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, configured to use, within 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 moments within a preset time period before a current moment, a set of all values of the corresponding type of historical fault data or each type of resource consumption data or each type of security threat data, whose values are not less than a lower limit 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 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 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, and to use, within 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 moments within a preset time period before a current moment, 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 the corresponding IT device, as a preliminary supplementary statistical set of the corresponding type of historical fault data or 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 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 a processing value of each type of historical fault data, 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, each type of resource consumption data, or each type of security threat data of each IT device and a preset statistical threshold includes:

[0019] Determine whether the number of elements in the statistical set of each type of historical fault data, 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, 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, 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 value 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 prepared 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 the supplementary statistical set of each class of historical fault data of each IT device or the supplementary statistical set of each class of resource consumption data or the 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 the supplementary statistical set of each class of resource consumption data or the 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 computing module of the remote monitoring system for IT equipment based on the Internet of Things includes:

[0022] a preparation submodule, for obtaining 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 all IT devices at all times within a preset time period before the current moment, and taking the average of the processed values of each type of historical fault data, 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, 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 calculation submodule obtains 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, 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, including:

[0025]

[0026] Where 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 moment. min is the minimum value of the processing values of the number of new faults of the currently calculated IT equipment at all times in the preset time period before the current moment, V is the reference mean value of the new fault resolution time of the currently calculated IT equipment at the current moment, v is the processing value of the new fault resolution time of the currently calculated 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 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 score of the IT equipment at the current moment, l is the processing value of the newly added fault maintenance difficulty star score of the IT equipment at the current moment, l max The maximum value of the newly added fault maintenance difficulty star number 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 maintenance difficulty stars of the IT equipment at all times in the preset time period before the current moment, Q is the reference average value of the CPU utilization rate of the IT equipment at the current moment, q is the processing value of the CPU utilization rate of the IT equipment at the current moment, 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 usage of the IT device currently calculated at the current moment, and w is the processing value of the memory usage of the IT device currently calculated at the current moment. max The maximum value of the memory usage of the IT device currently calculated at all times in the preset time period before the current moment, w minis the minimum value of the memory usage of the IT device at all times in the preset time period before the current moment, R is the reference mean value of the network bandwidth usage of the IT device at the current moment, r is the processing value of the network bandwidth usage of the IT device at the current moment, and r max 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 The maximum value of the number of newly detected intrusions of the IT equipment in the preset time period before the current moment. min is the minimum value of the processed values of the number of new intrusion detections 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 number of the currently calculated IT equipment at the current moment, t is the processed value of the vulnerability scan number of the currently calculated IT equipment at the current moment, and t max The maximum value of the vulnerability scan count of the IT device currently being calculated in the preset time period before the current moment. min It is the minimum value among the processed values of the vulnerability scan count of the currently calculated IT device 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 building blocks of the remote monitoring system for IT equipment based on the Internet of Things include:

[0028] A coordinate determination submodule is used to obtain the coordinate point of each IT device by using 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 construction submodule is used to treat two different IT devices from all IT devices as a group of IT devices, obtain all groups of IT devices, and connect the coordinate points of the two IT devices in each group if there is information interaction between the two IT devices within a preset time period before the current moment, thereby obtaining 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 remote monitoring system for IT equipment based on the Internet of Things includes:

[0032] a preparation unit, configured to use the number of coordinate points connected to each coordinate point among all coordinate points in the spatial node connection graph 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, configured to obtain a monitoring necessity degree for 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 an IT equipment remote monitoring system based on the Internet of Things, a method in which a calculation unit obtains the degree of 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 closest direct connection distance of all coordinate points in the spatial node connection graph of the Internet of Things at the current moment includes:

[0036]

[0037] Wherein, ρ is the monitoring necessity degree 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, and 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 in 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 in 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 configured to use the maximum value of the processed 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 IT device, thereby obtaining 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 to the prior art are as follows: based on 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, thereby quantifying the degree of fault, resource consumption and security threat suffered by each IT device at the current moment; and then, based on 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; based on 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, thereby accurately screening 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; finally, 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, thereby achieving the optimal allocation of bandwidth for all IT devices of the Internet of Things, improving monitoring efficiency and ensuring the overall quality of monitoring data.

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

[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 Schematic diagram of the monitoring module in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The preferred embodiments of the present invention are described below with reference to 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] Example 1:

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

[0050] A monitoring module is configured to obtain, 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, a processed value of all types of historical fault data, a processed value of all types of resource consumption data, and a processed value of all types of security threat data of each IT device at the current time;

[0051] a calculation module, configured to obtain a fault assessment value, a resource consumption assessment value, and a security threat assessment value for each IT device at the current moment based on 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 for each IT device at all moments in 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 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;

[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 for obtaining 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 lengths between each adjacent moment are 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 it takes 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 at the current moment is a value that can comprehensively 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 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: based on 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 all times in the 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, which realizes the quantification of the fault degree, resource consumption degree and security threat degree of each IT device at the current moment, and then based on 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 based on 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, which realizes the accurate screening of 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 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, which realizes the optimal allocation of bandwidth for all IT devices of the Internet of Things, improves monitoring efficiency and ensures the overall quality of monitoring data.

[0070] Example 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 for each IT device at all times within a preset time period before the current moment. The historical fault data includes the number of new faults, the time it takes to resolve new faults, and the star rating of the difficulty of maintaining new faults. The resource consumption data includes CPU usage, memory usage, and network bandwidth usage. The security threat data includes 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 within 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 back-end 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 back-end 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 within a preset time period before the current moment.

[0081] In this embodiment, the vulnerability scan count is the number of vulnerabilities scanned by each IT device at each moment within 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 in 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 facilitates the calculation of subsequent fault assessment values, resource consumption assessment values and security threat assessment values.

[0084] Example 3:

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

[0086] a first processing unit, configured to use a difference and a sum of the values of each type of historical fault data, 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, and the standard deviation of the values of the corresponding type of historical fault data, 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 a lower limit and an upper limit of the value of the corresponding type of historical fault data, 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, configured to use, within 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 moments within a preset time period before a current moment, a set of all values of the corresponding type of historical fault data or each type of resource consumption data or each type of security threat data, whose values are not less than a lower limit 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 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 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, and to use, within 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 moments within a preset time period before a current moment, 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 the corresponding IT device, as a preliminary supplementary statistical set of the corresponding type of historical fault data or 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 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: based on 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 based on 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, and finally, based on 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 each type of resource consumption data or each type of security threat data of each IT device at the current moment is accurately obtained, which facilitates the calculation of subsequent fault assessment values, resource consumption assessment values and security threat assessment values.

[0091] Example 4:

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

[0093] Determine whether the number of elements in the statistical set of each type of historical fault data, 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, 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, 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 value 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 prepared 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 the supplementary statistical set of each class of historical fault data of each IT device or the supplementary statistical set of each class of resource consumption data or the 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 the supplementary statistical set of each class of resource consumption data or the 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, based on the supplementary number of each type of historical fault data, the supplementary number of each type of resource consumption data, or the supplementary number of each type of security threat data for each IT device, elements are extracted from the preliminary supplementary statistical set of the corresponding type of historical fault data, 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 for the corresponding IT device, to obtain the supplementary statistical set of each type of historical fault data, the supplementary statistical set of each type of resource consumption data, or the supplementary statistical set of each type of security threat data for each IT device, which is:

[0096] The interval range determined by 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 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 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 of each IT device are used. 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] Example 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, for obtaining 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 all IT devices at all times within a preset time period before the current moment, and taking the average of the processed values of each type of historical fault data, 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, 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 effects of the above technology are: based on 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, and then 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, 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] Example 6:

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

[0105]

[0106]

[0107] Where 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 moment. minis the minimum value of the processing values of the number of new faults of the currently calculated IT equipment at all times in the preset time period before the current moment, V is the reference mean value of the new fault resolution time of the currently calculated IT equipment at the current moment, v is the processing value of the new fault resolution time of the currently calculated 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 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 score of the IT equipment at the current moment, l is the processing value of the newly added fault maintenance difficulty star score of the IT equipment at the current moment, l max The maximum value of the newly added fault maintenance difficulty star number 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 maintenance difficulty stars of the IT equipment at all times in the preset time period before the current moment, Q is the reference average value of the CPU utilization rate of the IT equipment at the current moment, q is the processing value of the CPU utilization rate of the IT equipment at the current moment, 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 usage of the IT device currently calculated at the current moment, and w is the processing value of the memory usage of the IT device currently calculated at the current moment. max The maximum value of the memory usage of the IT device currently calculated at all times in the preset time period before the current moment, w min is the minimum value of the memory usage of the IT device at all times in the preset time period before the current moment, R is the reference mean value of the network bandwidth usage of the IT device at the current moment, r is the processing value of the network bandwidth usage of the IT device at the current moment, and r max 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 The maximum value of the number of newly detected intrusions of the IT equipment in the preset time period before the current moment. min is the minimum value of the processed values of the number of new intrusion detections 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 number of the currently calculated IT equipment at the current moment, t is the processed value of the vulnerability scan number of the currently calculated IT equipment at the current moment, and t max The maximum value of the vulnerability scan count of the IT device currently being calculated in the preset time period before the current moment. min It is the minimum value among the processed values of the vulnerability scan count of the currently calculated IT device 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 effects of the above technology are: based on 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, thereby realizing the quantification of the fault degree, resource consumption degree and security threat degree of each IT device at the current moment. This embodiment provides 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] Example 7:

[0110] Based on Example 1, the remote monitoring system for IT equipment based on the Internet of Things is constructed with modules including:

[0111] A coordinate determination submodule is used to obtain the coordinate point of each IT device by using 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 construction submodule is used to treat two different IT devices from all IT devices as a group of IT devices, obtain all groups of IT devices, and connect the coordinate points of the two IT devices in each group if there is information interaction between the two IT devices within a preset time period before the current moment, thereby obtaining 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 refers to an IT device in the Internet of Things sending a data request to another IT device and receiving 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. Based on 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, which realizes the accurate screening of the coordinate points of IT equipment that need to be monitored among all IT equipment in the Internet of Things at the current moment.

[0116] Example 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, configured to use the number of coordinate points connected to each coordinate point among all coordinate points in the spatial node connection graph 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, configured to obtain a monitoring necessity degree for 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 monitoring necessity of each coordinate point in the spatial node connection diagram of the Internet of Things at the current moment is accurately obtained, and finally, according to the monitoring necessity of 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] Example 9:

[0125] Based on Example 8, in the remote monitoring system for IT equipment based on the Internet of Things, a method in which a calculation unit obtains the degree of necessity for 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 includes:

[0126]

[0127] Wherein, 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 in 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, φ is the mean 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, u max is the farthest direct connection distance of the currently calculated coordinate point in 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 in 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, 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, and a quantitative evaluation of the necessity of monitoring the IT equipment corresponding to each coordinate point at the current moment is realized. This embodiment provides in detail a specific method for accurately obtaining the necessity of monitoring 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 nearest direct connection distance of all coordinate points in the spatial node connection diagram of the Internet of Things at the current moment.

[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 configured to use the maximum value of the processed 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 IT device, thereby obtaining 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 equipment 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 the 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 to all IT devices in 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 is configured to obtain, 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, a processed value of all types of historical fault data, a processed value of all types of resource consumption data, and a processed value of all types of security threat data of each IT device at the current time; a calculation module, configured to obtain a fault assessment value, a resource consumption assessment value, and a security threat assessment value for each IT device at the current moment based on 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 for each IT device at all moments in 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 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; 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; Among them, the building blocks include: A coordinate determination submodule is used to obtain the coordinate point of each IT device by using 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 construction submodule is used to treat two different IT devices from all IT devices as a group of IT devices, obtain all groups of IT devices, and connect the coordinate points of the two IT devices in each group if there is information interaction between the two IT devices within a preset time period before the current moment, thereby obtaining 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 graph of the Internet of Things at the current moment; Among them, the node analysis submodule includes: a preparation unit, configured to use the number of coordinate points connected to each coordinate point among all coordinate points in the spatial node connection graph 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, configured to obtain a monitoring necessity degree for 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.

2. The remote monitoring system for IT equipment based on the Internet of Things according to claim 1, 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 for each IT device at all times within a preset time period before the current moment. The historical fault data includes the number of new faults, the time it takes to resolve new faults, and the star rating of the difficulty of maintaining new faults. The resource consumption data includes CPU usage, memory usage, and network bandwidth usage. The security threat data includes 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, characterized in that: Processing submodules, including: a first processing unit, configured to use a difference and a sum of the values of each type of historical fault data, 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, and the standard deviation of the values of the corresponding type of historical fault data, 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 a lower limit and an upper limit of the value of the corresponding type of historical fault data, the corresponding type of resource consumption data, or the corresponding type of security threat data of the corresponding IT device; a second processing unit, configured to use, within 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 moments within a preset time period before a current moment, a set of all values of the corresponding type of historical fault data or each type of resource consumption data or each type of security threat data, whose values are not less than a lower limit 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 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 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, and to use, within 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 moments within a preset time period before a current moment, 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 the corresponding IT device, as a preliminary supplementary statistical set of the corresponding type of historical fault data or 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 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, characterized in that: The method for the third processing unit to obtain a processing value of each type of historical fault data, each type of resource consumption data, or each type of security threat data of each IT device at a current moment based on the number of elements in the statistical set of each type of historical fault data, each type of resource consumption data, or 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, 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, 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, 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 value 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 prepared 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 the supplementary statistical set of each class of historical fault data of each IT device or the supplementary statistical set of each class of resource consumption data or the 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 the supplementary statistical set of each class of resource consumption data or the 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, for obtaining 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 all IT devices at all times within a preset time period before the current moment, and taking the average of the processed values of each type of historical fault data, 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, 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 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, 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: Where 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 moment. min is the minimum value of the processing values of the number of new faults of the currently calculated IT equipment at all times in the preset time period before the current moment, V is the reference mean value of the new fault resolution time of the currently calculated IT equipment at the current moment, v is the processing value of the new fault resolution time of the currently calculated 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 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 score of the IT equipment at the current moment, l is the processing value of the newly added fault maintenance difficulty star score of the IT equipment at the current moment, l max The maximum value of the newly added fault maintenance difficulty star number 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 maintenance difficulty stars of the IT equipment at all times in the preset time period before the current moment, Q is the reference average value of the CPU utilization rate of the IT equipment at the current moment, q is the processing value of the CPU utilization rate of the IT equipment at the current moment, 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 usage of the IT device currently calculated at the current moment, and w is the processing value of the memory usage of the IT device currently calculated at the current moment. max The maximum value of the memory usage of the IT device currently calculated at all times in the preset time period before the current moment, w min is the minimum value of the memory usage of the IT device at all times in the preset time period before the current moment, R is the reference mean value of the network bandwidth usage of the IT device at the current moment, r is the processing value of the network bandwidth usage of the IT device at the current moment, and r max 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 The maximum value of the number of newly detected intrusions of the IT equipment in the preset time period before the current moment. min is the minimum value of the processed values of the number of new intrusion detections 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 number of the currently calculated IT equipment at the current moment, t is the processed value of the vulnerability scan number of the currently calculated IT equipment at the current moment, and t max The maximum value of the vulnerability scan count of the IT device currently being calculated in the preset time period before the current moment. min It is the minimum value among the processed values of the vulnerability scan count of the currently calculated IT device 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: The method 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 by the calculation unit includes: Wherein, ρ is the monitoring necessity degree 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, and 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 in 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 in 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.

8. 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 configured to use the maximum value of the processed 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 IT device, thereby obtaining 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.

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