Capacity monitoring method, device, apparatus, storage medium, and program product

Abstract

The application discloses a capacity monitoring method and device, equipment, a storage medium and a program product, and relates to the technical field of communication networks. The capacity monitoring method comprises the following steps: determining the capacity sequence standard entropy of a monitoring area according to N communication capabilities in a communication network topology structure in the monitoring area, wherein the capacity sequence standard entropy is used for representing the uniformity of the communication capabilities in the communication network topology structure; when communication network capacity congestion occurs in the monitoring area, determining the communication capability to be adjusted in the N communication capabilities according to the capacity sequence standard entropy of the monitoring area, wherein the communication capability to be adjusted comprises at least one of the communication capability to be adjusted up and the communication capability to be adjusted down; and adjusting the communication capability to be adjusted to increase the capacity sequence standard entropy of the monitoring area, so as to increase the transmission capacity of the communication network in the monitoring area. The embodiment of the application can avoid the paralysis of the communication network.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of communication network, and particularly relates to a capacity monitoring method and device, equipment, storage medium and program product. BACKGROUND

[0002] The communication network provides a data communication channel for a computing system to deliver data and information, such as text, images, videos and website content. With the large-scale development of wireless communication network, the demand has been transferred from the coverage of the communication network to the capacity. Therefore, it is an urgent problem to be solved to monitor the transmission capacity of the communication network in real time.

[0003] The existing method mainly uses a multiple nonlinear regression function to perform fitting prediction, thereby monitoring the capacity of the communication network.

[0004] However, this method is prone to the phenomenon that the transmission capacity of the communication network is increasingly congested over time, thereby causing the paralysis of the communication network. SUMMARY

[0005] The embodiments of the present application provide a capacity monitoring method, device, equipment, storage medium and program product, which can avoid the paralysis of the communication network.

[0006] In an aspect of the embodiments of the present application, a capacity monitoring method is provided, comprising:

[0007] According to the N communication capabilities in the communication network topology structure in the monitoring area, a capacity sequence standard entropy of the monitoring area is determined, each communication capability is used to represent the communication capability between any two network nodes in the communication network topology structure, and at least one network node in the network nodes corresponding to different communication capabilities is different, N is a positive integer, and the capacity sequence standard entropy is used to represent the uniformity of the communication capability in the communication network topology structure;

[0008] In the case that the communication network capacity is congested in the monitoring area, according to the capacity sequence standard entropy of the monitoring area, a to-be-adjusted communication capability in the N communication capabilities is determined, the to-be-adjusted communication capability includes at least one of a to-be-increased communication capability and a to-be-decreased communication capability;

[0009] The to-be-adjusted communication capability is adjusted to increase the capacity sequence standard entropy of the monitoring area, thereby increasing the transmission capacity of the communication network in the monitoring area.

[0010] In an aspect of the embodiments of the present application, a capacity monitoring device is provided, comprising:

[0011] The standard entropy determination module is configured to determine a capacity sequence standard entropy of the monitoring area according to N communication capabilities in the communication network topology in the monitoring area, each communication capability is used to represent a communication capability between any two network nodes in the communication network topology, and at least one network node in the network nodes corresponding to different communication capabilities is different, N is a positive integer, and the capacity sequence standard entropy is used to represent a uniformity of the communication capabilities in the communication network topology.

[0012] The capability determination module is configured to determine a to-be-adjusted communication capability in the N communication capabilities according to the capacity sequence standard entropy of the monitoring area when the communication network capacity in the monitoring area is congested.

[0013] The capability adjustment module is configured to adjust the to-be-adjusted communication capability to increase the capacity sequence standard entropy of the monitoring area, thereby increasing the transmission capacity of the communication network in the monitoring area.

[0014] In an aspect of an embodiment of the present application, an electronic device is provided, which includes a memory and a program or instructions stored in the memory and executable on a processor, and the program or instructions are executed by the processor to implement the capacity monitoring method provided in any aspect of the above embodiment of the present application.

[0015] In an aspect of an embodiment of the present application, a readable storage medium is provided, and the readable storage medium stores a program or instructions, and the program or instructions are executed by a processor to implement the capacity monitoring method provided in any aspect of the above embodiment of the present application.

[0016] In an aspect of an embodiment of the present application, a computer program product is provided, and instructions in the computer program product are executed by a processor of an electronic device to enable the electronic device to perform the capacity monitoring method provided in any aspect of the above embodiment of the present application.

[0017] In the capacity monitoring method provided in the embodiment of the present application, the capacity sequence standard entropy representing the uniformity of the communication network topology is determined, then when the communication network capacity in the monitoring area is congested, the to-be-adjusted communication capability in the N communication capabilities is obtained according to the capacity sequence standard entropy, and the to-be-adjusted communication capability is adjusted to increase the capacity sequence standard entropy of the monitoring area, thereby making the communication network topology more uniform, and finally improving the transmission capacity of the communication network in the monitoring area. In this way, the capacity sequence standard entropy is increased in the embodiment of the present application, thereby enabling the transmission capacity to be adjusted in real time when the transmission capacity of the communication network is insufficient, and avoiding the phenomenon of communication network paralysis caused by the increasingly congested communication network transmission capacity over time. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced. Those drawings can help the ordinary skilled in the art to obtain other drawings without any creative effort.

[0019] Figure 1 is a flow diagram of a capacity monitoring method provided by an embodiment of the present application;

[0020] Figure 2 is a diagram showing the relationship between the transmission capacity of a communication network and the standard entropy of the capacity sequence on a BA scale-free network model provided by an embodiment of the present application;

[0021] Figure 3 is a diagram showing the relationship between the transmission capacity of a communication network and the standard entropy of the capacity sequence on a WS small-world network model provided by an embodiment of the present application;

[0022] Figure 4 is a structural diagram of a capacity monitoring device provided by an embodiment of the present application;

[0023] Figure 5 is a structural diagram of a capacity monitoring device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0024] The features and exemplary embodiments of various aspects of the present application will be described in detail below, in order to make the purposes, technical solutions and advantages of the present application more clear and apparent, the present application will be further described in detail below with reference to the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, but not to limit the present application. The present application can be implemented without some of these specific details by those skilled in the art. The following description of the embodiments is only intended to provide a better understanding of the present application by showing examples of the present application.

[0025] It should be noted that, in this document, relational terms such as first and second and the like can only be used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or apparatus. Without more limitations, the elements defined by the statement "comprising" do not exclude the presence of additional identical elements in the process, method, article or apparatus including the elements.

[0026] It should be noted that the acquisition, storage, use, processing and the like of data in the technical solutions of the present application comply with relevant provisions of national laws and regulations.

[0027] It should be noted that in the embodiments of the present application, some software, components, models and the like of the prior art may be mentioned, which should be considered as exemplary, and the purpose is only to illustrate the feasibility in the implementation of the technical solutions of the present application, but it does not mean that the applicant has or will necessarily use the scheme.

[0028] In the related art, the capacity of the communication network is mainly monitored by fitting and predicting through a multivariate nonlinear regression function. However, this method is prone to the phenomenon that the transmission capacity of the communication network becomes more and more congested over time, thereby causing the paralysis of the communication network.

[0029] The purpose of the present application is to provide a capacity monitoring method, device, equipment, storage medium and program product. In the capacity monitoring method provided by the embodiments of the present application, the capacity sequence standard entropy representing the uniformity of the communication network topology structure is determined, and then when the communication network capacity congestion occurs in the monitoring area, the to-be-adjusted communication capacity in the N communication capacities is obtained according to the capacity sequence standard entropy, and the to-be-adjusted communication capacity is adjusted to increase the capacity sequence standard entropy of the monitoring area, so that the communication network topology structure is more uniform, and finally the transmission capacity of the communication network in the monitoring area is improved. In this way, the embodiments of the present application can increase the capacity sequence standard entropy, thereby being able to adjust the transmission capacity in real time when the transmission capacity of the communication network is insufficient, and avoiding the phenomenon of paralysis of the communication network caused by the increasing congestion of the transmission capacity of the communication network over time.

[0030] The specific embodiments of the capacity monitoring method, device, equipment, storage medium and program product provided by the embodiments of the present application will be introduced below. First, the capacity monitoring method will be introduced.

[0031] Figure 1 A flowchart of a capacity monitoring method is provided, which can be applied to a server. The capacity monitoring method can include the following steps S101 to S103.

[0032] S101, according to N communication capacities in the communication network topology structure in the monitoring area, determining the capacity sequence standard entropy of the monitoring area, each communication capacity is used to represent the communication capacity between any two network nodes in the communication network topology structure, and the network nodes corresponding to different communication capacities are different, and there is at least one network node in the network nodes corresponding to different communication capacities, N is a positive integer, and the capacity sequence standard entropy is used to represent the uniformity of the communication capacity in the communication network topology structure.

[0033] In this embodiment, the communication capability is used to represent the communication capability between any two network nodes in the communication network topology, and different communication capabilities correspond to at least one different network node in the network nodes. For example, the communication network topology includes three network nodes A, B and C, and there is a communication capability between network node A and network node B, a communication capability between network node A and network node C, and a communication capability between network node B and network node C.

[0034] The capacity sequence standard entropy is used to represent the uniformity of the communication capability in the communication network topology. For example, the greater the capacity sequence standard entropy, the more evenly the communication capabilities in the communication network topology are, and the smaller the capacity sequence standard entropy, the more uneven the communication capabilities in the communication network topology are.

[0035] As an example, the server obtains the communication network topology corresponding to the monitoring area, and then analyzes each network node in the communication network topology to determine the communication capability between any two network nodes in the communication network topology, thereby obtaining N communication capabilities corresponding to the communication network topology.

[0036] S102, in the case of communication network capacity congestion in the monitoring area, determining the to-be-adjusted communication capability in the N communication capabilities according to the capacity sequence standard entropy of the monitoring area, the to-be-adjusted communication capability including at least one of the to-be-increased communication capability and the to-be-decreased communication capability.

[0037] In this embodiment, the to-be-adjusted communication capability is the communication capability in the communication network topology that does not match the average value of the communication capability. The to-be-adjusted communication capability includes at least one of the to-be-increased communication capability and the to-be-decreased communication capability.

[0038] For example, in the case of a communication capability greater than the average value of the communication capability, the corresponding communication capability is determined to be the to-be-decreased communication capability; in the case of a communication capability less than the average value of the communication capability, the corresponding communication capability is determined to be the to-be-increased communication capability.

[0039] As an example, in the case of communication network capacity congestion in the monitoring area, the server indicates that the communication network transmission capacity in the monitoring area needs to be increased. At this time, according to the capacity sequence standard entropy of the monitoring area, the proportion of each communication capability in the sum of the N communication capabilities can be determined.

[0040] Then, according to the proportion of each communication capability in the sum of the N communication capabilities, each communication capability greater than one N is determined to be the to-be-decreased communication capability, and each communication capability less than one N is determined to be the to-be-increased communication capability.

[0041] S103, adjust the communication capability to be adjusted to increase the standard entropy of the capacity sequence in the monitoring area, thereby increasing the transmission capacity of the communication network in the monitoring area.

[0042] In this embodiment, the server increases the communication capability to be increased and decreases the communication capability to be decreased, thereby increasing the standard entropy of the capacity sequence in the monitoring area and increasing the uniformity of the communication network topology. At this time, the overall transmission of the communication network topology is more uniform, and the transmission capacity of the communication network in the monitoring area can be further increased.

[0043] like Figure 2 As shown, a schematic diagram illustrating the relationship between the transmission capacity and the standard entropy of the capacity sequence of a communication network on a BA scale-free network model is provided, where R... c S represents the transmission capacity of a communication network. N This represents the standard entropy of the capacity sequence. According to... Figure 2 Simulation results show that in the BA scale-free network model, the standard entropy of the capacity sequence is closely related to the transmission capacity of the communication network. As the standard entropy of the capacity sequence increases, the uniformity of the network topology of the communication network is enhanced, and the transmission capacity increases significantly.

[0044] like Figure 3 As shown, a schematic diagram illustrating the relationship between the transmission capacity and the standard entropy of the capacity sequence of a communication network on a WS small-world network model is provided, where R c S represents the transmission capacity of a communication network. N This represents the standard entropy of the capacity sequence. According to... Figure 3 Simulation results show that in the WS small-world network model, the standard entropy of the capacity sequence is closely related to the transmission capacity of the communication network. As the standard entropy of the capacity sequence increases, the uniformity of the network topology of the communication network is enhanced, and the transmission capacity increases significantly.

[0045] Therefore, it can be concluded that the transmission capacity of a communication network is a monotonically increasing function of the standard entropy of the capacity sequence, and is positively correlated with the standard entropy of the capacity sequence. When congestion is detected in a communication network, increasing the standard entropy of the capacity sequence can increase the transmission capacity of the communication network.

[0046] By the embodiment, the capacity sequence standard entropy characterizing the uniformity of the communication network topology is determined, and then when the communication network capacity congestion occurs in the monitoring area, the to-be-adjusted communication capacity in the N communication capacities is obtained according to the capacity sequence standard entropy, and the to-be-adjusted communication capacity is adjusted to increase the capacity sequence standard entropy of the monitoring area, so that the communication network topology is more uniform, and finally the transmission capacity of the communication network in the monitoring area is improved. In this way, the capacity sequence standard entropy is increased by the embodiment of the application, so that the transmission capacity can be adjusted in real time when the transmission capacity of the communication network is insufficient, and the phenomenon of communication network paralysis caused by the increasingly congested communication network transmission capacity over time is avoided.

[0047] As an optional embodiment, S101 specifically includes:

[0048] According to the connection relationship between the network nodes in the communication network topology in the monitoring area and the path length between the network nodes, N communication capacities corresponding to the communication network topology are determined.

[0049] The entropy value of the N communication capacities is calculated to obtain the capacity sequence standard entropy of the monitoring area.

[0050] In the embodiment, the connection relationship has an influence on the communication capacity between the network nodes. For example, when the network node A is directly connected to the network node B, the communication capacity between the network node A and the network node B is determined to be 1; when the network node A is not directly connected to the network node B, the communication capacity between the network node A and the network node B is determined to be 0.

[0051] The path length has an influence on the communication capacity between the network nodes. For example, when the path length between the network node A and the network node B is short, the communication capacity between the network node A and the network node B is determined to be strong, and a larger weight value is given to the communication capacity; when the path length between the network node A and the network node B is long, the communication capacity between the network node A and the network node B is determined to be weak, and a smaller weight value is given to the communication capacity.

[0052] As an example, the server determines the communication capacity between the network nodes directly connected according to the connection relationship between the network nodes in the communication network topology in the monitoring area, and determines the communication capacity between the network nodes unable to be directly connected to be 0.

[0053] Then, according to the relationship between all paths reaching each network node in the monitoring area and the power adjacency matrix of the network, and considering the influence of path length on communication capacity, a greater weight is given to the communication capacity with shorter path length, a smaller weight is given to the communication capacity with longer path length, and a positive value is used to represent the communication capacity between each network node in the communication network topology, so as to obtain the communication matrix corresponding to the communication network topology as shown in the following formula 1.

[0054]

[0055] In the formula, CA represents the communication matrix corresponding to the communication network topology, the element (ca) in the ith row and the jth column of the communication matrix CA represents the communication capacity between the network node i and the network node j in the communication network topology. ij

[0056] Since in the communication matrix CA, (ca) ij and (ca) ji both represent the communication capacity between the network node i and the network node j in the communication network topology, and are equal in value. Therefore, the server selects each communication capacity on the diagonal line of the communication matrix CA or below the diagonal line of the communication matrix CA to form a communication capacity set, wherein the communication capacity set includes N communication capacities corresponding to the communication network topology. 11 NN

[0057] Finally, the server calculates the entropy value of the N communication capacities included in the communication capacity set, so as to obtain the standard entropy of the capacity sequence corresponding to the monitoring area.

[0058] Through the embodiment, according to the connection relationship between each network node in the communication network topology in the monitoring area and the path length between each network node, the communication capacities included in the communication network topology can be accurately determined, and the standard entropy of the capacity sequence of the monitoring area can be determined according to the communication capacities. It is helpful to increase the standard entropy of the capacity sequence of the monitoring area in the subsequent process, so as to increase the transmission capacity of the communication network in the monitoring area.

[0059] As an optional embodiment, the entropy value of the N communication capacities is calculated to obtain the standard entropy of the capacity sequence of the monitoring area, which can specifically include:

[0060] determining the proportion of each communication capacity in the sum of the N communication capacities;

[0061] calculating the Shannon entropy of the proportion of each communication capacity in the sum of the N communication capacities to obtain the capacity sequence entropy;

[0062] ​​​The capacity sequence standard entropy of the monitoring area is obtained by dividing the capacity sequence entropy of the monitoring area by the logarithm of N.

[0063] In this embodiment, the server sums up the N communication capabilities to obtain a sum value. Then each communication capability is divided by the sum value in turn to obtain the proportion of each communication capability, thereby obtaining the proportion set P=[P1, P2, …, PN]. N ]。

[0064] Then, according to the proportion of each communication capability included in the proportion set P, the Shannon entropy is calculated by the following formula 2, thereby obtaining the capacity sequence entropy S(P) of the monitoring area.

[0065]

[0066] Wherein, S(P) represents the capacity sequence entropy of the monitoring area, P N represents the proportion of the Nth communication capability in the proportion set.

[0067] Then, according to the capacity sequence entropy S(P) of the monitoring area, the capacity sequence standard entropy of the monitoring area is calculated by the following formula 3:

[0068]

[0069] Wherein, S N represents the capacity sequence standard entropy of the monitoring area, S(P) represents the capacity sequence entropy of the monitoring area, and N represents the number of communication capabilities.

[0070] Through this embodiment, the entropy value of the N communication capabilities is calculated to obtain the capacity sequence standard entropy of the monitoring area. This is helpful for subsequent increase of the capacity sequence standard entropy of the monitoring area, thereby increasing the transmission capacity of the communication network in the monitoring area.

[0071] As an optional embodiment, before S102, the capacity monitoring method can further include:

[0072] According to the actual carrier-to-interference ratio of the communication network in the monitoring area, a maximum bearable capacity value of the communication network in the monitoring area is determined, and the actual carrier-to-interference ratio is used to represent the actual mobile call quality of the global system for mobile communication;

[0073] According to the generation rate of the data packet generated by the communication network and the processing rate of the data packet processed by the communication network, a capacity occupation peak value of the monitoring area is determined;

[0074] The maximum bearable capacity value is compared with the capacity occupation peak value to obtain a capacity identification result, and the capacity identification result is used to indicate whether the phenomenon of communication network capacity congestion actually occurs in the monitoring area.

[0075] In the embodiment, the actual carrier-to-interference ratio is used to represent the actual mobile call quality of the global system for mobile communications, and the maximum bearable capacity value is used to represent the maximum value of bearable data packets of the transmission capacity of the communication network in the monitoring area.

[0076] The capacity occupation peak value is used to represent the peak value of actual bearable data packets of the transmission capacity of the communication network in the monitoring area.

[0077] The capacity identification result is used to indicate whether the communication network capacity congestion phenomenon actually occurs in the monitoring area. For example, when the capacity identification result indicates that the capacity occupation peak value is greater than the maximum bearable capacity value, it indicates that the communication network capacity congestion phenomenon actually occurs in the monitoring area; when the capacity identification result indicates that the capacity occupation peak value is not greater than the maximum bearable capacity value, it indicates that the communication network capacity congestion phenomenon does not actually occur in the monitoring area.

[0078] As an example, the server first determines the actual carrier-to-interference ratio of the communication network in the monitoring area, and then calculates the maximum bearable capacity value of the communication network in the monitoring area according to the actual carrier-to-interference ratio.

[0079] Meanwhile, according to the generation rate of the data packets generated by the communication network and the processing rate of the data packets processed by the communication network, the capacity occupation peak value of the monitoring area at each time is determined.

[0080] Finally, the capacity occupation peak value at each time is compared with the maximum bearable capacity value. When the capacity occupation peak value is greater than the maximum bearable capacity value, it indicates that the communication network capacity congestion phenomenon actually occurs in the monitoring area at the corresponding time, and the server increases the capacity sequence standard entropy of the monitoring area, thereby increasing the transmission capacity of the communication network in the monitoring area.

[0081] When the capacity occupation peak value is not greater than the maximum bearable capacity value, it indicates that the communication network capacity congestion phenomenon does not actually occur in the monitoring area at the current time, and there is no need to increase the transmission capacity of the communication network. The server continues to compare the capacity occupation peak value of the monitoring area at the next time with the maximum bearable capacity value to confirm whether the communication network capacity congestion phenomenon actually occurs in the monitoring area at the next time.

[0082] Through the embodiment, the capacity occupation peak value and the maximum bearable capacity value of the communication network are calculated, and the maximum bearable capacity value of the communication network is used as a critical threshold. By comparing the capacity occupation peak value of the communication network at any time with the maximum bearable capacity value, whether the communication network capacity is insufficient can be monitored. At the same time, online real-time monitoring is realized in a cyclic manner, the transmission capacity of the communication network can be adjusted in time when the congestion phenomenon occurs, and the paralysis of the communication network can be avoided.

[0083] As an optional embodiment, the maximum bearable capacity value of the communication network in the monitoring area is determined according to the actual carrier-to-interference ratio of the communication network in the monitoring area, and specifically can include:

[0084] The actual carrier-to-interference ratio of the communication network in the monitoring area is determined according to the theoretical carrier-to-interference ratio and the path loss rate of the communication network in the monitoring area;

[0085] The minimum value of the frequency reuse degree of the monitoring area is determined according to the actual carrier-to-interference ratio of the communication network in the monitoring area;

[0086] The maximum bearable capacity value of the communication network in the monitoring area is determined according to the minimum value of the frequency reuse degree.

[0087] In this embodiment, the server first obtains the theoretical carrier-to-interference ratio of the communication network in the monitoring area for frequency planning by using the multiple frequency reuse method, and specifically, the theoretical carrier-to-interference ratio can be determined according to the following formula 4:

[0088] C1 / I1=alog(1+D / R)K i Formula 4

[0089] Wherein, C1 / I1 represents the theoretical carrier-to-interference ratio in the monitoring area, a represents the path loss slope in the propagation model, D represents the distance between the centers of two regions A and B corresponding in position in two adjacent region groups, that is, the nearest co-frequency region distance, also known as the frequency reuse distance, R represents the coverage radius of the monitoring area, K i represents the received power of the mobile terminal.

[0090] Specifically, the frequency reuse distance can be determined according to the following formula 5:

[0091]

[0092] Wherein, D represents the frequency reuse distance, N represents the frequency reuse degree, m represents the average number of sectors per base station, and S represents the average distance between base stations.

[0093] The path loss slope can be determined according to the following formula 6:

[0094] a=K i logH x +K j Formula 6

[0095] Wherein, a represents the path loss slope in the propagation model, K i represents the received power of the mobile terminal, K j represents the transmission power of the mobile terminal, H x represents the height of the transmitter.

[0096] Then, the theoretical carrier-to-interference ratio of the communication network in the monitoring area is adjusted according to the path loss slope, so as to obtain the actual carrier-to-interference ratio of the communication network in the monitoring area. Specifically, the actual carrier-to-interference ratio of the communication network in the monitoring area can be determined according to the following formula 7:

[0097]

[0098] Wherein, C2 / I2 represents the actual carrier-to-interference ratio in the monitoring area, a represents the path loss slope in the propagation model, N represents the frequency reuse degree, m represents the average sector number per base station, S represents the average distance between base stations, R represents the coverage radius of the monitoring area, K j represents the transmission power of the mobile terminal.

[0099] Then, the server deforms the actual carrier-to-interference ratio in the monitoring area according to formula 7, so as to determine the minimum value of the frequency reuse degree of the monitoring area, and finally obtains the maximum bearable capacity value of the communication network in the monitoring area according to the minimum value of the frequency reuse degree.

[0100] Specifically, the maximum bearable capacity value of the communication network can be determined according to the following formula 8:

[0101]

[0102] Wherein, C max represents the maximum bearable capacity value of the communication network, T represents the number of available carriers; M represents the area of the monitoring area, C2 / I2 represents the actual carrier-to-interference ratio in the monitoring area, K j represents the transmission power of the mobile terminal, and R represents the coverage radius of the monitoring area.

[0103] Through the embodiment, the maximum bearable capacity value of the communication network in the monitoring area is determined according to the actual carrier-to-interference ratio of the communication network in the monitoring area. It is helpful to monitor whether the capacity of the communication network is insufficient by taking the maximum bearable capacity value of the communication network as a critical threshold value.

[0104] As an optional embodiment, the capacity occupation peak of the monitoring area is determined according to the generation rate of the data packets generated by the communication network and the processing rate of the data packets processed by the communication network, which can specifically include:

[0105] The capacity occupation parameter is determined according to the generation rate of the data packets generated by the communication network and the processing rate of the data packets processed by the communication network, and the capacity occupation parameter is used to represent whether there is a possibility of communication network capacity congestion in the monitoring area;

[0106] In the case that the capacity occupation parameter is greater than zero, the capacity occupation peak of the monitoring area is determined according to the number of available carriers, the area of the monitoring area, the frequency reuse degree and the unit base station area.

[0107] In this embodiment, the capacity occupation parameter is used to represent whether there is a possibility of communication network capacity congestion in the monitoring area. For example, when the capacity occupation parameter is greater than zero, it indicates that more and more data packets are buffered over time steps in the communication network, i.e., there is a possibility of communication network capacity congestion in the monitoring area; when the capacity occupation parameter is not greater than zero, it indicates that there is no possibility of communication network capacity congestion in the monitoring area.

[0108] As an example, the server obtains the capacity occupation parameter according to the generation rate of data packets generated by the communication network and the processing rate of data packets processed by the communication network, so as to determine whether there is a possibility of communication network capacity congestion in the monitoring area.

[0109] Then, when the capacity occupation parameter is greater than zero, it indicates that there is a possibility of communication network capacity congestion in the monitoring area. At this time, the server determines the capacity occupation peak value of the monitoring area according to the number of available carrier frequencies, the area of the monitoring area, the frequency reuse degree, and the unit base station area.

[0110] Specifically, the capacity occupation peak value can be determined according to the following formula 9:

[0111]

[0112] Wherein, C T represents the capacity occupation peak value, T represents the number of available carrier frequencies, M represents the area of the monitoring area, N represents the frequency reuse degree; X represents the unit base station area.

[0113] Specifically, the unit base station area can be determined according to the following formula 10:

[0114]

[0115] Wherein, X represents the unit base station area, and S represents the average distance between base stations.

[0116] Through this embodiment, the capacity occupation parameter is determined according to the generation rate of data packets generated by the communication network and the processing rate of data packets processed by the communication network. Therefore, it is helpful to compare the capacity occupation peak value of the communication network at any time with the maximum bearable capacity value in the subsequent process, so as to realize the monitoring of whether the communication network capacity is insufficient.

[0117] As an optional embodiment, the capacity occupation parameter is determined according to the generation rate of data packets generated by the communication network and the processing rate of data packets processed by the communication network, which can specifically include:

[0118] Divide the processing rate of data packets generated by the communication network by the generation rate of data packets processed by the communication network to obtain a first value;

[0119] The first value is multiplied by the average change amount of the buffered data packets in the communication network within the time window, to obtain a second value, the buffered data packets being the data packets generated but not processed in the communication network;

[0120] The limit of the second value is calculated to obtain the capacity occupation parameter corresponding to the preset time window.

[0121] In the embodiment, the buffered data packets are the data packets generated but not processed in the communication network, that is, the generated data packets minus the processed data packets.

[0122] As an example, the server obtains the generation rate of the data packets generated by the communication network according to the number of the data packets generated in the time interval divided by the number of the time steps in the time interval, and obtains the processing rate of the data packets processed by the communication network according to the number of the data packets processed in the time interval divided by the number of the time steps in the time interval. Then, the first value is obtained by dividing the processing rate of the data packets processed by the communication network by the generation rate of the data packets generated by the communication network.

[0123] Then, a time window is preset, and the average change amount of the buffered data packets in the communication network within the time window is obtained. The first value is multiplied by the average change amount of the buffered data packets in the communication network within the time window, to obtain a second value. Finally, the limit of the second value is calculated to obtain the capacity occupation parameter corresponding to the time window.

[0124] Specifically, the capacity occupation parameter can be determined according to the following formula 11:

[0125]

[0126] Wherein, θ represents the capacity occupation parameter, F represents the processing rate of the data packets generated by the communication network, R represents the generation rate of the data packets processed by the communication network, and ΔP represents the change amount of the buffered data packets in the communication network within the window time of the time window ΔT.

[0127] Through the embodiment, the generation rate of the data packets generated by the communication network and the processing rate of the data packets processed by the communication network are used to depict the capacity occupation parameter of the communication network from the free state to the congestion state, so as to help judging whether the transmission capacity of the communication network is likely to appear congestion phenomenon by taking the capacity occupation parameter as the critical condition.

[0128] Based on the capacity monitoring method. Correspondingly, the application also provides specific embodiments of the capacity monitoring device.

[0129] As shown in Figure 4 The capacity monitoring device provided by the embodiment of the application includes a standard entropy determination module 410, a capacity determination module 420, and a capacity adjustment module 430.

[0130] The standard entropy determination module 410 is configured to determine a capacity sequence standard entropy of the monitoring area according to N communication capabilities in the communication network topology in the monitoring area, each of the communication capabilities is used to represent a communication capability between any two network nodes in the communication network topology, and at least one of the network nodes corresponding to different communication capabilities is different, N is a positive integer, and the capacity sequence standard entropy is used to represent a uniformity of the communication capabilities in the communication network topology.

[0131] The capability determination module 420 is configured to determine an adjusted communication capability in the N communication capabilities according to the capacity sequence standard entropy of the monitoring area when the communication network capacity in the monitoring area is congested, the adjusted communication capability including at least one of an up-regulated communication capability and a down-regulated communication capability.

[0132] The capability adjustment module 430 is configured to adjust the adjusted communication capability to increase the capacity sequence standard entropy of the monitoring area, so as to increase the transmission capacity of the communication network in the monitoring area.

[0133] By the embodiment, the capacity sequence standard entropy representing the uniformity of the communication network topology is determined, and then when the communication network capacity in the monitoring area is congested, the adjusted communication capability in the N communication capabilities is obtained according to the capacity sequence standard entropy, and the adjusted communication capability is adjusted to increase the capacity sequence standard entropy of the monitoring area, so that the communication network topology is more uniform, and finally the transmission capacity of the communication network in the monitoring area is improved. In this way, the capacity sequence standard entropy is increased by the embodiment of the application, so that the transmission capacity can be adjusted in real time when the transmission capacity of the communication network is insufficient, and the phenomenon of communication network paralysis caused by the increasingly congested transmission capacity of the communication network over time is avoided.

[0134] As an optional embodiment, the standard entropy determination module 410 specifically includes the following units:

[0135] The capability determination unit is configured to determine the N communication capabilities corresponding to the communication network topology according to the connection relationship between the network nodes and the path length between the network nodes in the communication network topology in the monitoring area;

[0136] The standard entropy calculation unit is configured to perform entropy value calculation on the N communication capabilities to obtain the capacity sequence standard entropy of the monitoring area.

[0137] As an optional embodiment, the standard entropy calculation unit specifically includes the following sub-units:

[0138] The proportion determination sub-unit is configured to determine a proportion of each communication capability in a sum of the N communication capabilities.

[0139] a Shannon entropy calculation subunit configured to calculate a proportion of each communication capability in a sum of the N communication capabilities by using Shannon entropy calculation, and obtain a capacity sequence entropy;

[0140] a standard entropy determination subunit configured to divide the capacity sequence entropy by a logarithm of N, and obtain a capacity sequence standard entropy of the monitoring area.

[0141] As an optional embodiment, the capacity monitoring apparatus can further include the following modules:

[0142] a capacity value determination module configured to determine a maximum bearable capacity value of the communication network in the monitoring area according to an actual carrier-to-interference ratio of the communication network in the monitoring area, the actual carrier-to-interference ratio being used to represent an actual mobile call quality of the global system for mobile communications;

[0143] a peak value determination module configured to determine a capacity occupation peak value of the monitoring area according to a generation rate of data packets generated by the communication network and a processing rate of the data packets processed by the communication network;

[0144] a result determination module configured to compare the maximum bearable capacity value with the capacity occupation peak value, and obtain a capacity recognition result, the capacity recognition result being used to indicate whether a communication network capacity congestion phenomenon actually occurs in the monitoring area.

[0145] As an optional embodiment, the capacity value determination module specifically includes the following units:

[0146] a carrier-to-interference ratio determination unit configured to determine the actual carrier-to-interference ratio of the communication network in the monitoring area according to a theoretical carrier-to-interference ratio of the communication network in the monitoring area and a path loss rate;

[0147] a multiplexing degree determination unit configured to determine a minimum value of frequency multiplexing degree of the monitoring area according to the actual carrier-to-interference ratio of the communication network in the monitoring area;

[0148] a capacity value determination unit configured to determine the maximum bearable capacity value of the communication network in the monitoring area according to the minimum value of frequency multiplexing degree.

[0149] As an optional embodiment, the peak value determination module specifically includes the following units:

[0150] a parameter determination unit configured to determine a capacity occupation parameter according to the generation rate of data packets generated by the communication network and the processing rate of the data packets processed by the communication network, the capacity occupation parameter being used to represent a possibility of whether a communication network capacity congestion occurs in the monitoring area;

[0151] a peak value determination unit configured to, in a case where the capacity occupation parameter is greater than zero, determine the capacity occupation peak value of the monitoring area according to the number of available carrier frequencies, an area of the monitoring area, the frequency multiplexing degree and a unit base station area.

[0152] As an optional embodiment, the parameter determining unit specifically comprises the following sub-units:

[0153] The result calculating sub-unit is configured to divide the processing rate of the communication network to generate the data packet by the generation rate of the communication network to process the data packet, to obtain a first value.

[0154] The result calculating sub-unit is further configured to multiply the first value by the average change amount of the buffered data packet in the communication network in the time window, to obtain a second value, the buffered data packet being the data packet that has been generated but not processed in the communication network.

[0155] The parameter determining sub-unit is configured to calculate a limit of the second value, to obtain the capacity occupation parameter corresponding to the time window.

[0156] Based on the capacity monitoring method, the application further provides a specific embodiment of the capacity monitoring device.

[0157] Figure 5 A hardware structure schematic diagram of the capacity monitoring device provided by the embodiment of the application is shown.

[0158] The capacity monitoring device can comprise a processor 501 and a memory 502 storing computer program instructions.

[0159] Specifically, the processor 501 can comprise a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured to implement one or more integrated circuits of the embodiment of the application.

[0160] The memory 502 can comprise a mass storage for data or instructions. By way of example and not limitation, the memory 502 can include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 502 can include removable or non-removable (or fixed) media. Where appropriate, the memory 502 can be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, the memory 502 is a non-volatile solid-state memory.

[0161] The memory can include read-only memory (ROM), random-access memory (RAM), magnetic disk storage mediums devices, optical storage mediums devices, flash memory devices, electrical, optical, or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage mediums (e.g., a memory device) encoded with software that, when executed (e.g., by one or more processors), is operable to perform the operations described with reference to the methods according to an aspect of the present disclosure.

[0162] The processor 501 implements the capacity monitoring method of any of the above-described embodiments by reading and executing computer program instructions stored in the memory 502.

[0163] In one example, the capacity monitoring device can further include a communication interface 503 and a bus 510. Wherein, as shown, the processor 501, the memory 502, the communication interface 503 are connected through the bus 510 and complete the communication between each other. Figure 5

[0164] The communication interface 503 is mainly used to realize the communication between each module, device, unit and / or equipment in the embodiments of the present application.

[0165] The bus 510 includes hardware, software or both to couple the components of the capacity monitoring device to each other. By way of example, and not limitation, the bus can include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association local (VLB) bus, or another suitable bus or combination of two or more of these. Where suitable, the bus 510 can include one or more buses. Although specific buses are described and shown in the embodiments of the present application, the present application contemplates any suitable bus or interconnect.

[0166] In addition, in combination with the capacity monitoring method in the above-described embodiments, the embodiments of the present application can provide a computer storage medium to implement. The computer storage medium has computer program instructions stored thereon; the computer program instructions are executed by the processor to implement any of the capacity monitoring methods in the above-described embodiments.

[0167] ​In addition, in combination with the capacity monitoring method in the above embodiments, the embodiments of the present application can provide a computer program product for implementation. The instructions in the computer program product are executed by the processor of the electronic device to implement any of the capacity monitoring methods in the above embodiments.

[0168] It should be noted that the present application is not limited to the specific configurations and processes described above and illustrated in the drawings. For the sake of brevity, detailed descriptions of known methods are omitted. In the above embodiments, several specific steps are described and illustrated as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and one skilled in the art can make various changes, modifications and additions, or change the order of the steps, after understanding the spirit of the present application.

[0169] The functional blocks shown in the structural block diagrams described above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc. When implemented in software, the elements of the present application are program or code segments used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. The "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via a computer network such as the Internet, an intranet, etc.

[0170] It should also be noted that the exemplary embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be performed simultaneously.

[0171] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other processing device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other processing device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0172] The above describes only specific implementation of the present application. For the convenience and brevity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described herein. It should be understood that the protection scope of the present application is not limited in this way. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed in the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A capacity monitoring method, characterized in that, The method includes: Based on N communication capabilities in the communication network topology within the monitoring area, the standard entropy of the capacity sequence of the monitoring area is determined. Each communication capability is used to characterize the communication capability between any two network nodes in the communication network topology, and at least one network node is different among the network nodes corresponding to different communication capabilities. N is a positive integer, and the standard entropy of the capacity sequence is used to characterize the uniformity of communication capabilities in the communication network topology. In the event of communication network capacity congestion within the monitoring area, the communication capacity to be adjusted among the N communication capacities is determined based on the standard entropy of the capacity sequence of the monitoring area. The communication capacity to be adjusted includes at least one of the communication capacity to be increased and the communication capacity to be decreased. The communication capability to be adjusted is adjusted to increase the standard entropy of the capacity sequence of the monitoring area, thereby increasing the transmission capacity of the communication network within the monitoring area; The step of determining the standard entropy of the capacity sequence of the monitoring area based on N communication capabilities in the communication network topology within the monitoring area includes: Based on the connection relationships between network nodes in the communication network topology within the monitoring area and the path lengths between network nodes, determine N communication capabilities corresponding to the communication network topology. The entropy values ​​of the N communication capabilities are calculated to obtain the standard entropy of the capacity sequence of the monitoring area; The step of calculating the entropy value of the N communication capabilities to obtain the standard entropy of the capacity sequence of the monitoring area includes: Determine the proportion of each of the aforementioned communication capabilities to the sum of the N communication capabilities; The Shannon entropy is calculated to obtain the capacity sequence entropy by taking into account the proportion of each of the aforementioned communication capabilities to the sum of the N communication capabilities. Divide the capacity sequence entropy by the logarithm of N to obtain the standard entropy of the capacity sequence of the monitoring area; Before determining the communication capacity to be adjusted among the N communication capacities based on the standard entropy of the capacity sequence of the monitoring area in the event of communication network capacity congestion within the monitoring area, the method further includes: Based on the actual carrier-to-interference ratio of the communication network within the monitoring area, the maximum carrying capacity of the communication network within the monitoring area is determined. The actual carrier-to-interference ratio is used to characterize the actual mobile call quality of the global mobile communication system. The peak capacity occupancy of the monitoring area is determined based on the data packet generation rate and data packet processing rate of the communication network. The maximum carrying capacity value is compared with the peak capacity occupancy to obtain a capacity identification result, which is used to indicate whether a communication network capacity congestion phenomenon actually occurs in the monitoring area.

2. The method according to claim 1, characterized in that, The step of determining the maximum carrying capacity of the communication network within the monitoring area based on the actual carrier-to-interference ratio of the communication network within the monitoring area includes: The actual carrier-to-interference ratio of the communication network within the monitoring area is determined based on the theoretical carrier-to-interference ratio and path loss rate of the communication network within the monitoring area. The minimum frequency reuse rate of the monitoring area is determined based on the actual carrier-to-interference ratio of the communication network within the monitoring area. Based on the minimum frequency reuse value, the maximum carrying capacity of the communication network within the monitoring area is determined.

3. The method according to claim 1, characterized in that, Determining the peak capacity occupancy of the monitoring area based on the data packet generation rate and data packet processing rate of the communication network includes: Based on the data packet generation rate and data packet processing rate of the communication network, a capacity occupancy parameter is determined. This capacity occupancy parameter is used to characterize whether there is a possibility of communication network capacity congestion within the monitoring area. When the capacity occupancy parameter is greater than zero, the peak capacity occupancy of the monitoring area is determined based on the number of available carrier frequencies, the area of ​​the monitoring area, the frequency reuse rate, and the area per unit base station.

4. The method according to claim 3, characterized in that, The step of determining the capacity occupancy parameter based on the data packet generation rate and data packet processing rate of the communication network includes: Divide the data packet processing rate of the communication network by the data packet generation rate of the communication network to obtain the first value; The first value is multiplied by the average change in the cached data packets in the communication network within the time window to obtain the second value, wherein the cached data packets are data packets that have been generated but not processed in the communication network; The limit is calculated for the second value to obtain the capacity occupancy parameter corresponding to the time window.

5. A capacity monitoring device, characterized in that, The device includes: The standard entropy determination module is used to determine the capacity sequence standard entropy of the monitoring area based on N communication capabilities in the communication network topology within the monitoring area. Each communication capability is used to characterize the communication capability between any two network nodes in the communication network topology, and at least one network node is different among the network nodes corresponding to different communication capabilities. N is a positive integer, and the capacity sequence standard entropy is used to characterize the uniformity of communication capabilities in the communication network topology. The capacity determination module is used to determine, in the event of communication network capacity congestion within the monitoring area, the communication capacity to be adjusted among the N communication capabilities based on the standard entropy of the capacity sequence of the monitoring area. The communication capacity to be adjusted includes at least one of communication capacity to be increased and communication capacity to be decreased. A capacity adjustment module is used to adjust the communication capacity to be adjusted in order to increase the capacity sequence standard entropy of the monitoring area, thereby increasing the transmission capacity of the communication network in the monitoring area; The standard entropy determination module includes: The capability determination unit is used to determine N communication capabilities corresponding to the communication network topology based on the connection relationship between each network node in the communication network topology within the monitoring area and the path length between each network node. A standard entropy calculation unit is used to calculate the entropy value of the N communication capabilities to obtain the standard entropy of the capacity sequence of the monitoring area; The standard entropy calculation unit includes: The proportion determination subunit is used to determine the proportion of each of the aforementioned communication capabilities to the sum of the N communication capabilities; The Shannon entropy calculation subunit is used to calculate the Shannon entropy of the proportion of each of the aforementioned communication capabilities to the sum of the N communication capabilities, and obtain the capacity sequence entropy; The standard entropy determination subunit is used to divide the capacity sequence entropy by the logarithm of N to obtain the standard entropy of the capacity sequence of the monitoring area; The device further includes: The capacity value determination module is used to determine the maximum carrying capacity value of the communication network in the monitoring area based on the actual carrier-to-interference ratio of the communication network in the monitoring area. The actual carrier-to-interference ratio is used to characterize the actual mobile call quality of the global mobile communication system. The peak value determination module is used to determine the peak capacity occupancy of the monitoring area based on the generation rate of data packets generated by the communication network and the processing rate of data packets processed by the communication network. The result determination module is used to compare the maximum bearable capacity value with the peak capacity occupancy to obtain a capacity identification result. The capacity identification result is used to indicate whether a communication network capacity congestion phenomenon actually occurs in the monitoring area.

6. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the capacity monitoring method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the capacity monitoring method as described in any one of claims 1-4.

8. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the capacity monitoring method as described in any one of claims 1-4.

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