Access traffic generation method and device of low earth orbit satellite, and storage medium

Abstract

The invention provides an access traffic generation method for a low earth orbit satellite, and the method comprises the steps: generating an interval time sequence of a low earth orbit satellite service based on a service model of the low earth orbit satellite service; according to the base station space-time flow data set of the service corresponding to the low earth orbit satellite service, obtaining a space-time distribution model of the low earth orbit satellite service; global low earth orbit satellite position time data are exported through satellite system simulation software; according to the global low earth orbit satellite position time data and the space-time distribution model of the low earth orbit satellite service, calculating the access traffic of the low earth orbit satellite at any moment; the interval time sequence of the low-earth-orbit satellite service and the access flow size of the low-earth-orbit satellite at any moment are used as control parameters, and the speed and the size of the low-earth-orbit satellite service data generated by the network flow generation software at the client side are controlled; and according to the low earth orbit satellite service data received and transmitted by the server and the client, obtaining a change curve of the low earth orbit satellite access traffic. According to the technical scheme of the invention, the authenticity of low-orbit satellite access traffic can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of low-orbit satellite data processing, and in particular to a method, device and storage medium for generating access traffic for a low-orbit satellite. Background Art

[0002] As the scale of low-orbit satellite network systems gradually increases and business scenarios become more diverse, low-cost, high-fidelity experimental verification is required before system implementation. Therefore, in the field of low-orbit satellite technology, establishing a simulation platform to test the performance of software and hardware in low-orbit satellite networks plays an important role. Similar to ground network testing, the generation of low-orbit satellite access traffic is the most important component of the entire simulation platform and an important factor affecting the performance of low-orbit satellite networks. Existing methods for generating access traffic for low-orbit satellites only consider the self-similarity characteristics (or long-range correlation) of the traffic itself. Not only that, it cannot truly reflect the authenticity of the access traffic of low-orbit satellites, and therefore cannot lay the foundation for testing low-orbit satellite network systems. Summary of the Invention

[0003] The present application provides a method, device and storage medium for generating access traffic of a low-orbit satellite, which can improve the authenticity of the access traffic of the low-orbit satellite while having low dependence on the actual traffic data of the low-orbit satellite.

[0004] On the one hand, the present application provides a method for generating access traffic for a low-orbit satellite, the method comprising:

[0005] generating an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service;

[0006] Obtaining a spatiotemporal distribution model of the low-orbit satellite service based on a base station spatiotemporal traffic dataset corresponding to the low-orbit satellite service;

[0007] Export global low-orbit satellite position and time data through satellite system simulation software;

[0008] Calculating the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service;

[0009] Using the interval time sequence of the low-orbit satellite service and the access traffic volume of the low-orbit satellite at any time as control parameters, the speed and volume of the low-orbit satellite service data generated by the network traffic generation software on the client are controlled;

[0010] According to the low-orbit satellite service data sent and received by the server and the client, a change curve of the low-orbit satellite access traffic is obtained.

[0011] On the other hand, the present application provides an access traffic generation device for a low-orbit satellite, the device comprising:

[0012] A generating module, configured to generate an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service;

[0013] A first acquisition module is configured to acquire a spatiotemporal distribution model of the low-orbit satellite service based on a base station spatiotemporal traffic dataset of a service corresponding to the low-orbit satellite service;

[0014] Data export module, used to export global low-orbit satellite position and time data through satellite system simulation software;

[0015] A calculation module, configured to calculate the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service;

[0016] A control module is configured to use the interval time sequence of the low-orbit satellite service and the access traffic volume of the low-orbit satellite at any time as control parameters to control the speed and volume of low-orbit satellite service data generated by the network traffic generation software on the client;

[0017] The second acquisition module is used to obtain a change curve of low-orbit satellite access traffic based on the low-orbit satellite service data sent and received by the server and the client.

[0018] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the technical solution for the method for generating access traffic for a low-orbit satellite as described above are implemented.

[0019] In a fourth aspect, the present application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the technical solution of the access traffic generation method for the low-orbit satellite as described above.

[0020] From the technical solution provided in the present application, it can be seen that, on the one hand, since the spatiotemporal distribution model of low-orbit satellite services is obtained based on the spatiotemporal traffic data set of base stations corresponding to the low-orbit satellite services, and the spatiotemporal traffic data set of base stations corresponding to the low-orbit satellite services is real, reliable and public data, the spatiotemporal distribution model of low-orbit satellite services obtained based on the spatiotemporal traffic data set of base stations corresponding to the low-orbit satellite services can more realistically reflect the traffic distribution of global low-orbit satellite services at any time; on the other hand, based on the global low-orbit satellite position time data and the spatiotemporal distribution model of low-orbit satellite services, the access traffic size of the low-orbit satellite at any time is calculated, that is, low-orbit satellite access traffic with spatiotemporal characteristics is generated, which improves the authenticity of the low-orbit satellite access traffic and reduces the dependence on actual low-orbit satellite traffic data. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 This is a flow chart of a method for generating access traffic for a low-orbit satellite provided in an embodiment of the present application;

[0023] Figure 2 This is a schematic diagram of global traffic distribution at any time provided by an embodiment of the present application;

[0024] Figure 3 This is a comparison chart of access traffic curves of three services on the same low-orbit satellite at different times, provided by an embodiment of the present application;

[0025] Figure 4 This is a schematic structural diagram of an access traffic generating device for a low-orbit satellite provided in an embodiment of the present application;

[0026] Figure 5 It is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] In this specification, adjectives such as first and second may be used only to distinguish one element or action from another element or action, without necessarily requiring or implying any actual such relationship or order. Where circumstances permit, reference to an element or component or step (etc.) should not be construed as being limited to only one of the elements, components, or steps, but may be one or more of the elements, components, or steps, etc.

[0029] In this specification, for the convenience of description, the sizes of various parts shown in the drawings are not drawn according to the actual proportions.

[0030] As low-orbit satellite network systems grow in scale and service scenarios become increasingly diverse, low-cost, high-fidelity experimental verification is necessary before system implementation. Therefore, in the field of low-orbit satellite technology, establishing a simulation platform to test the performance of software and hardware in low-orbit satellite networks plays a crucial role. Similar to terrestrial network testing, the generation of low-orbit satellite access traffic is a crucial component of the entire simulation platform and a key factor influencing the performance of low-orbit satellite networks. Current methods for generating low-orbit satellite access traffic only consider the self-similarity (or long-range correlation) of the traffic itself. This fails to truly reflect the authenticity of low-orbit satellite access traffic and therefore does not provide a foundation for testing low-orbit satellite network systems. Currently, due to the level of technological development and economic conditions, terrestrial traffic density is unevenly distributed globally. Furthermore, regional traffic is influenced by local user behavior, resulting in different temporal variations in traffic in different regions. These factors, to a certain extent, reflect the magnitude of low-orbit satellite access traffic. With the development of satellite internet, the scale of satellite users will continue to expand, and spatiotemporal characteristics will become crucial factors in low-orbit satellite access traffic. To truly reflect the distribution of traffic density across regions around the world, it is necessary to collect reliable datasets with strong correlations, such as those on population density, base station distribution, and terminal device distribution. Furthermore, the types of services supported by low-orbit satellite networks are complex, necessitating the selection of representative services and the use of appropriate simulation models. To this end, these two data can be combined with low-orbit satellite position and time data to generate low-orbit satellite access traffic with temporal and spatial characteristics.

[0031] In view of the above problems of the prior art, this application proposes a method for generating access traffic for low-orbit satellites, the flow chart of which is shown in the attached figure. Figure 1 As shown, it mainly includes steps S101 to S106, which are detailed as follows:

[0032] Step S101: Based on the service model of the low-orbit satellite service, an interval time series of the low-orbit satellite service is generated.

[0033] In the embodiment of the present application, the low-orbit satellite service can be three typical services, such as web services, voice services, or video services. Since each low-orbit satellite service has its own characteristics, the method for generating the interval time series for each low-orbit satellite service is different, which is explained below.

[0034] When the low-orbit satellite service is a web service, as an embodiment of the present application, based on the service model of the low-orbit satellite service, generating the interval time series of the low-orbit satellite service can be achieved through steps Sa1011 to Sa1013, as detailed below:

[0035] Step Sa1011: Determine the total sending time of the web page service data packet.

[0036] In the embodiment of the present application, the total sending time of the web service data packet is a pre-determined parameter, which is used to control when the interval time sequence ends. The time starts from the time when the first web service data packet is sent. Once the total sending time T is reached or exceeded, the interval time sequence of the web service stops generating. min represents the sending time of a single web service data packet, then the total sending time T of the web service data packet should be:

[0037]

[0038] Among them, n is the total amount of web service data packets that need to be sent, x i is the element of the interval time series of web page business, C package is the size of a single web page service data packet, and B is the system's sending bandwidth.

[0039] Step Sa1012: Based on the shape parameter and scale parameter of the Pareto distribution, generate the duration of the ON state and the duration of the OFF state, wherein the ON state is the state of sending web service data packets and the OFF state is the state of not sending web service data packets.

[0040] Pareto distribution is a common probability distribution. The probability density function (PDF) of Pareto distribution is:

[0041]

[0042] Where x is a random variable (usually representing wealth, income, etc.), x m is the minimum value (scale parameter) of the Pareto distribution. μα (α>0) is the shape parameter, which determines the "fat tail" characteristic of the distribution. The Pareto distribution has a heavy tail characteristic, which means that there is a higher probability at extreme values, which makes it very effective in describing extreme phenomena. When α>1, only the mean exists, and the mean calculation formula is When α>2, only variance exists, and the variance calculation formula is

[0043] If T ON Indicates the duration of the ON state, T OFF Indicates the duration of the OFF state, then:

[0044]

[0045] Among them, α ON and α OFFare shape parameters, which are used to control the expected duration of the ON state and the expected duration of the OFF state, respectively. μ and v are both uniformly distributed random numbers, that is, μ∈(0,1), v∈(0,1), k ON is the minimum web service data packet transmission time, which is equal to the transmission time of a single web service data packet T min Equal, that is, k ON =T min , k OFF is the minimum interval time between web service data packets, and its calculation formula is: in, Mean(ON) and Mean(OFF) are the average expected duration of the ON state and the average expected duration of the OFF state, respectively.

[0046] Step Sa1013: Generate an interval time series of web page services according to the duration of the ON state, the duration of the OFF state, and the scale parameter of the Pareto distribution.

[0047] Specifically, according to the duration of the ON state, the duration of the OFF state and the scale parameter of the Pareto distribution, the interval time series of the web page service can be generated as follows: according to the duration of the ON state and the scale parameter of the Pareto distribution, the number n of the interval time series elements sent in the ON state is calculated. ON ; The duration of the OFF state is taken as an element and n ON The sending time intervals of the web service data packets are added as elements one by one to the initial interval time sequence, until the total sending time T of the web service data packets is reached to obtain the interval time sequence of the web service. In the above embodiment, the number of elements of the sending interval time sequence in the ON state is The interval time series X of the web page business finally generated is:

[0048] X={x1,x2,…,x i ,…,x n}

[0049] Among them, x i The size is either equal to the interval time τ in the ON state, which is the minimum resolution time of the electronic device clock, or equal to the value of the random variable T in the OFF state. OFF The physical meaning of this sequence is how long to wait after a data packet is sent before continuing to send it.

[0050] When the low-orbit satellite service is a voice service, as an embodiment of the present application, based on the service model of the low-orbit satellite service, generating the interval time series of the low-orbit satellite service can be achieved through steps Sb1011 to Sb1013, as detailed below:

[0051] Step Sb1011: Determine the total sending time of the voice service data packet.

[0052] The total transmission time of voice service data packets, or the total duration of the voice service interval time series, can be a predetermined parameter used to control when the interval time series ends. Timing begins from the transmission of the first voice service data packet. Once the total transmission time T is reached or exceeded, the voice service interval time series generation stops.

[0053] Step Sb1012: Calculate the duration of the voice service in the ON state and the OFF state according to the rate parameter of the voice service in the ON state, the rate parameter of the voice service in the OFF state, and the exponential distribution.

[0054] In the embodiment of the present application, the model of the voice service is also based on the ON / OFF model. The interval time series generation process is similar to the interval time series generation process of the web service. The difference is that the duration of the ON state or the OFF state is randomly generated by the exponential distribution. Specifically, if λ ON Indicates the rate parameter of the voice service in the ON state, that is, the average number of requests sent per unit time, expressed in λ OFF Indicates the rate parameter of the voice service in the OFF state, that is, the average number of pause requests per unit time. The duration of the voice service in the ON state is T ON And the duration of OFF state T OFF They are:

[0055]

[0056] Wherein, ln() is an exponential function, U and V are random numbers that obey uniform distribution, that is, U ~ Uniform (0, 1) and V ~ Uniform (0, 1).

[0057] Step Sb1013: Add the duration of the voice service in the ON state and the OFF state as elements to the initial interval time sequence, and obtain the interval time sequence of the voice service until the total sending time of the voice service data packet is reached.

[0058] The final generated interval time series X of the voice service is:

[0059] X={x1,x2,…,x i ,…,x n}

[0060] Among them, x i The size is either equal to the duration of the voice service in the ON state or equal to the duration of the voice service in the OFF state.

[0061] When the low-orbit satellite service is a video service, as an embodiment of the present application, based on the service model of the low-orbit satellite service, generating the interval time series of the low-orbit satellite service can be achieved through steps Sc1011 and Sc1012, as detailed below:

[0062] Step Sc1011: Generate the total time interval I of the video service based on the wavelet scale layer number n and the Gaussian distribution of the mean μ and variance σ.

[0063] In the embodiment of the present application, the number of wavelet scale layers n is used to control the level of the fractal, and the mean μ and variance σ represent the average duration of the interval and the degree of fluctuation of the interval, respectively. The total interval length I of the video service is generated by a Gaussian distribution that satisfies the mean μ and variance σ, that is:

[0064] I~G(μ,σ 2 )

[0065] Here, G(μ,σ 2 ) represents a Gaussian distributed random variable with mean μ and variance σ.

[0066] Step Sc1012: Fractalize I layer by layer from 1 to n, and obtain the total number of video services at the nth layer as 2 n interval time series.

[0067] First, the interval time of each layer is calculated to generate the interval time series of each layer; then, the generated interval time series is subjected to wavelet transform to extract its multifractal features; finally, the wavelet coefficients are reconstructed into the original interval time series through inverse wavelet transform. min To represent the transmission time of a single video service data packet, the total transmission time of the video service data packet is T = I + T min *2 n .

[0068] Step S102: obtaining a spatiotemporal distribution model of the low-orbit satellite service based on a base station spatiotemporal traffic data set corresponding to the low-orbit satellite service.

[0069] As an embodiment of the present application, based on the base station spatiotemporal traffic dataset corresponding to the low-orbit satellite service, obtaining the spatiotemporal distribution model of the low-orbit satellite service can be achieved through steps S1021 to S1025, as detailed below:

[0070] Step S1021: collecting and aggregating a service flow data set of a base station at a preset location within a preset time period.

[0071] For example, we can collect a one-month data set of business traffic from a base station in a southwestern city in my country, and aggregate the data into a week through processing.

[0072] Step S1022: Fit the aggregated service traffic data set with the minimum mean square error as the goal, and use the fitted traffic change over time model as the traffic time distribution model of the low-orbit satellite service.

[0073] Specifically, analyzing the time-varying curve of the traffic flow data aggregated over a week in step S1021 reveals significant periodicity. Then, while ensuring minimum mean square error, the aggregated traffic flow data is fitted using a finite-term sine function using a Fourier series, yielding the following fitting formula for traffic flow variation over time:

[0074]

[0075] Where D(t) is the traffic volume at time t, a0 represents the average level of traffic volume, a1 represents the impact of the fundamental component on traffic volume fluctuations, a2 represents the impact of the second harmonic component on traffic volume fluctuations, and a3 represents the impact of the third harmonic component on traffic volume fluctuations. Determine the specific time characteristics of the changes in the fundamental components of business traffic, Determine the specific time characteristics of the changes in the second harmonic components of business traffic, Determines the specific time characteristics of the changes in the third harmonic component of business traffic.

[0076] Step S1023: Divide the global base stations into 180*360 areas according to longitude and latitude, and count the number of base stations of each type of signal in each area.

[0077] If divided according to each degree of longitude and latitude, the world can be divided into 180*360 regions. The signal types in each region can be 2G, 3G, 4G, 5G and other types. The number of base stations of these types of signals in each region is counted.

[0078] Step S1024: Based on the traffic weights of the base stations of various types of signals, the relative traffic of each area is calculated as the elements of a spatial distribution matrix with a size of 180*360, and the spatial distribution matrix with a size of 180*360 is used as the traffic spatial distribution model of low-orbit satellite services.

[0079] Assume that w1, w2, w3, and w4 are the traffic weight values ​​of the base stations of 2G, 3G, 4G, and 5G signals respectively. According to statistics, in a certain area of ​​180*360 areas, the number of base stations of these four signals is n1, n2, n3, etc., then the relative traffic size in the area l is For each of the 180*360 areas, the relative flow is calculated using the same method as the relative flow within the area, and finally a spatial distribution moment of size 180*360 is obtained, where the elements are the relative flow of each area.

[0080] Step S1025: Obtain the time weight of each of the 180*360 areas, multiply the time weight of each area by the relative traffic of the corresponding area in the traffic spatial distribution model, and obtain the spatiotemporal distribution model of the low-orbit satellite service.

[0081] Normalize the time fitting formula D(t) to the maximum value, take Beijing time as the benchmark, consider the time difference of each region, and obtain the time weight of each region. Assuming that Beijing time is determined, the time T of each region in the 180*360 regions is local By formula Calculated, among which GST Time is China Standard Time, namely Beijing time, and Lon is the longitude of each region. After the time of each region is determined, the normalized time fitting formula is used. Get the time weight w of all regions local_time The time weight of each area is compared with the relative flow F of the corresponding area in the flow spatial distribution model. l Perform multiplication to obtain the spatiotemporal distribution model of low-orbit satellite services

[0082] Step S103: Exporting global low-orbit satellite position and time data through satellite system simulation software.

[0083] Specifically, you can write a Python script to control STK to create a low-orbit constellation. After the creation is completed, it will export the global low-orbit satellite position (i.e. longitude and latitude) and time data.

[0084] Step S104: Calculate the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service.

[0085] Specifically, based on the global low-orbit satellite position and time data and the spatiotemporal distribution model of low-orbit satellite services, the access traffic size of the low-orbit satellite at any time can be calculated as follows: at any time, based on the global satellite position and time data and the spatiotemporal distribution model of low-orbit satellite services, the traffic of each of the 180*360 areas is evenly distributed to the low-orbit satellites in their respective areas; the traffic obtained by each low-orbit satellite is accumulated to calculate the access traffic size of each low-orbit satellite at any time.

[0086] Step S105: Using the interval time sequence of the low-orbit satellite service and the access traffic size of the low-orbit satellite at any time as control parameters, the speed and size of the low-orbit satellite service data generated by the network traffic generation software on the client are controlled.

[0087] In the embodiment of the present application, the network traffic generation software may be Iperf3. Iperf3 is used to actually generate a data stream of low-orbit satellite access traffic on the client side. The data packet sending rhythm is controlled by the interval time sequence of the low-orbit satellite services generated in step S101, and the data packet size is controlled by the low-orbit satellite access traffic size at any time calculated in step S103.

[0088] Step S106: Obtain a change curve of low-orbit satellite access traffic based on the low-orbit satellite service data sent and received by the server and the client.

[0089] The server opens the receiving state mode of the network traffic generation software Iperf3, uses the network traffic capture and analysis software to capture the data packets sent by the client, and after parsing the data packets, obtains the change curve of the low-orbit satellite access traffic.

[0090] From the above attached Figure 1 From the example method for generating access traffic for low-orbit satellites, it can be seen that, on the one hand, since the spatiotemporal distribution model of low-orbit satellite services is obtained based on the spatiotemporal traffic dataset of base stations corresponding to the low-orbit satellite services, and the spatiotemporal traffic dataset of base stations corresponding to the low-orbit satellite services is real, reliable and public data, the spatiotemporal distribution model of low-orbit satellite services obtained based on the spatiotemporal traffic dataset of base stations corresponding to the low-orbit satellite services can more realistically reflect the traffic distribution of global low-orbit satellite services at any time; on the other hand, based on the global low-orbit satellite position time data and the spatiotemporal distribution model of low-orbit satellite services, the access traffic size of low-orbit satellites at any time is calculated, that is, low-orbit satellite access traffic with spatiotemporal characteristics is generated, which improves the authenticity of the low-orbit satellite access traffic and reduces the dependence on actual low-orbit satellite traffic data.

[0091] To verify Figure 1 The temporal and spatial characteristics and self-similarity characteristics of the access traffic of the low-orbit satellite generated by the example method are as follows: the three service model parameters of the client are set according to Table 1, and the time and space distribution model parameters are set according to Table 2. From this, a heat map can be drawn, that is, a global traffic distribution map at any time, such as Figure 2 As shown. The constellation creation parameters of the low-orbit satellite are set according to Table 3; when the low-orbit satellite numbers are the same, the service type and low-orbit satellite time are set according to Table 4, and finally the access traffic of the low-orbit satellite is generated. Therefore, the server can receive three traffic curves and the corresponding low-orbit satellite latitude and longitude information, and analyze the characteristics of the generated traffic based on this, as shown in Figure 3. Figure 3 shown.

[0092] Table 1 Parameters of three business models

[0093]

[0094] Table 2 Parameters of spatiotemporal distribution model

[0095]

[0096]

[0097] Table 3 Satellite parameters

[0098]

[0099] Table 4 Service types and satellite time parameters

[0100]

[0101]

[0102] analyze Figure 3 At 1:00 AM, the LEO satellite was located over Alexandria, Egypt, at 7:00 PM local time. At 3:00 AM, the LEO satellite was located over Qingdao, Shandong, China, at 3:00 PM local time. At 9:00 AM, the LEO satellite was located over Mexico City, Mexico, at 7:00 PM local time. Because the maximum access traffic in these three regions and their surrounding areas differs significantly, access traffic is primarily influenced by spatial factors. Based on the access traffic density in Qingdao > Mexico City > Alexandria, we can infer that the peak access traffic for voice services is > the peak access traffic for video services > the peak access traffic for web services. This inference is consistent with the results, demonstrating that the generated LEO satellite access traffic has spatiotemporal characteristics.

[0103] The R / S graph estimation method was used for all three access traffic curves, and the self-similarity coefficients of the low-orbit WeChat access traffic for web, voice, and video services were calculated to be 0.5665, 0.6784, and 0.8888, respectively. All of these are between 0.5 and 1, indicating that they are self-similar and meet the self-similarity property of low-orbit satellite network access traffic. The values ​​for web and voice are similar because they are all based on the ON / OFF model.

[0104] Please see the attached Figure 4 , is a low-orbit satellite access traffic generation device provided in an embodiment of the present application. The device may include a generation module 401, a first acquisition module 402, a data export module 403, a calculation module 404, a control module 405, and a second acquisition module 406, which are described in detail as follows:

[0105] A generating module 401 is configured to generate an interval time series of low-orbit satellite services based on a service model of the low-orbit satellite services;

[0106] A first acquisition module 402 is configured to acquire a spatiotemporal distribution model of the low-orbit satellite service based on a base station spatiotemporal traffic dataset corresponding to the low-orbit satellite service;

[0107] The data export module 403 is used to export the global low-orbit satellite position and time data through the satellite system simulation software;

[0108] The calculation module 404 is used to calculate the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service;

[0109] The control module 405 is used to control the speed and size of the low-orbit satellite service data generated by the network traffic generation software on the client by using the interval time sequence of the low-orbit satellite service and the access traffic volume of the low-orbit satellite at any time as control parameters;

[0110] The second acquisition module 406 is configured to acquire a change curve of low-orbit satellite access traffic based on low-orbit satellite service data received and sent by the server and the client.

[0111] From the above attached Figure 4 It can be seen from the example low-orbit satellite access traffic generation device that, on the one hand, since the spatiotemporal distribution model of the low-orbit satellite service is obtained based on the base station spatiotemporal traffic data set of the service corresponding to the low-orbit satellite service, and the base station spatiotemporal traffic data set of the service corresponding to the low-orbit satellite service is real, reliable and public data, the spatiotemporal distribution model of the low-orbit satellite service obtained based on the base station spatiotemporal traffic data set of the service corresponding to the low-orbit satellite service can more realistically reflect the traffic distribution of the global low-orbit satellite service at any time; on the other hand, based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service, the access traffic size of the low-orbit satellite at any time is calculated, that is, the low-orbit satellite access traffic with spatiotemporal characteristics is generated, which improves the authenticity of the low-orbit satellite access traffic and reduces the dependence on the actual low-orbit satellite traffic data.

[0112] Figure 5 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 5 As shown, the electronic device 5 of this embodiment mainly includes: a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50, such as a program for a method for generating access traffic for a low-orbit satellite. When the processor 50 executes the computer program 52, the steps in the embodiment of the method for generating access traffic for a low-orbit satellite are implemented, such as Figure 1 Alternatively, when the processor 50 executes the computer program 52, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 4 The functions of the generation module 401, the first acquisition module 402, the data export module 403, the calculation module 404, the control module 405 and the second acquisition module 406 are shown.

[0113] Exemplarily, a computer program 52 for generating access traffic for a low-orbit satellite includes: generating an interval time series of low-orbit satellite services based on a service model for low-orbit satellite services; obtaining a spatiotemporal distribution model for the low-orbit satellite services based on a base station spatiotemporal traffic dataset corresponding to the low-orbit satellite services; deriving global low-orbit satellite position and time data using satellite system simulation software; calculating the access traffic volume of the low-orbit satellite at any time based on the global low-orbit satellite position and time data and the spatiotemporal distribution model for the low-orbit satellite services; controlling the speed and volume of low-orbit satellite service data generated by the network traffic generation software on the client using the interval time series of the low-orbit satellite services and the access traffic volume of the low-orbit satellite at any time as control parameters; and obtaining a curve of the low-orbit satellite access traffic based on the low-orbit satellite service data sent and received between the server and the client. The computer program 52 may be divided into one or more modules / units, one or more of which may be stored in the memory 51 and executed by the processor 50 to implement the present application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 52 in the electronic device 5. For example, the computer program 52 can be divided into the functions of a generation module 401, a first acquisition module 402, a data export module 403, a calculation module 404, a control module 405 and a second acquisition module 406 (modules in the virtual device), and the specific functions of each module are as follows: the generation module 401 is used to generate an interval time series of low-orbit satellite services based on the service model of low-orbit satellite services; the first acquisition module 402 is used to obtain the spatiotemporal distribution model of low-orbit satellite services based on the spatiotemporal traffic data set of the base station corresponding to the low-orbit satellite services; the data export module 403 is used to obtain the spatiotemporal distribution model of low-orbit satellite services through the satellite system The simulation software exports global low-orbit satellite position and time data; a calculation module 404 is used to calculate the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position and time data and the spatiotemporal distribution model of the low-orbit satellite service; a control module 405 is used to control the speed and size of the low-orbit satellite service data generated by the network traffic generation software on the client using the interval time series of the low-orbit satellite service and the access traffic size of the low-orbit satellite at any time as control parameters; a second acquisition module 406 is used to obtain a change curve of the low-orbit satellite access traffic based on the low-orbit satellite service data sent and received by the server and the client.

[0114] The electronic device 5 may include but is not limited to a processor 50 and a memory 51. Those skilled in the art will appreciate that Figure 5 It is only an example of the electronic device 5 and does not constitute a limitation of the electronic device 5. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0115] The processor 50 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0116] The memory 51 can be an internal storage unit of the electronic device 5, such as the hard drive or memory of the electronic device 5. The memory 51 can also be an external storage device of the electronic device 5, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped on the electronic device 5. Furthermore, the memory 51 can include both the internal storage unit of the electronic device 5 and an external storage device. The memory 51 is used to store computer programs and other programs and data required by the electronic device. The memory 51 can also be used to temporarily store data that has been output or is about to be output.

[0117] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0118] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0119] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] In the embodiments provided in this application, it should be understood that the disclosed devices / equipment and methods can be implemented in other ways. For example, the device / equipment embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0121] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0122] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0123] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program of the low-orbit satellite access traffic generation method can be stored in a storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments, that is, based on the service model of the low-orbit satellite service, generate the interval time series of the low-orbit satellite service; obtain the spatiotemporal distribution model of the low-orbit satellite service based on the base station spatiotemporal traffic data set of the service corresponding to the low-orbit satellite service: export the global low-orbit satellite position time data through the satellite system simulation software; calculate the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service; use the interval time series of the low-orbit satellite service and the access traffic size of the low-orbit satellite at any time as control parameters to control the speed and size of the low-orbit satellite service data generated by the network traffic generation software on the client; obtain the change curve of the low-orbit satellite access traffic based on the low-orbit satellite service data sent and received by the server and the client. Among them, computer programs include computer program code, which may be in source code form, object code form, executable files, or some intermediate form. Storage media may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunications signals, and software distribution media. It should be noted that the content contained in storage media may be appropriately increased or decreased based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, storage media do not include electric carrier signals and telecommunications signals.

[0124] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application. The specific implementation methods described above further explain the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only the specific implementation method of the present application and is not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included in the protection scope of the present invention.

Claims

1. A method for generating access traffic for a low-orbit satellite, characterized in that: The method comprises: generating an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service; Obtaining a spatiotemporal distribution model of the low-orbit satellite service based on a base station spatiotemporal traffic dataset corresponding to the low-orbit satellite service; Export global low-orbit satellite position and time data through satellite system simulation software; Calculating the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service; Using the interval time sequence of the low-orbit satellite service and the access traffic volume of the low-orbit satellite at any time as control parameters, the speed and volume of the low-orbit satellite service data generated by the network traffic generation software on the client are controlled; According to the low-orbit satellite service data sent and received by the server and the client, a change curve of the low-orbit satellite access traffic is obtained.

2. The method for generating access traffic for a low-orbit satellite according to claim 1, wherein: The low-orbit satellite service includes a webpage service, and generating an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service includes: Determine the total sending time of web service data packets; Generate an ON state duration and an OFF state duration based on a shape parameter and a scale parameter of a Pareto distribution, wherein the ON state is a state in which the webpage service data packet is sent, and the OFF state is a state in which the webpage service data packet is not sent; An interval time series of the webpage service is generated according to the duration of the ON state, the duration of the OFF state, and the scale parameter of the Pareto distribution.

3. The method for generating access traffic for a low-orbit satellite according to claim 2, wherein: Generating the interval time series of the webpage service according to the duration of the ON state, the duration of the OFF state, and the scale parameter of the Pareto distribution includes: According to the duration of the ON state and the scale parameter of the Pareto distribution, the number n of the sending interval time series elements in the ON state is calculated. ON ; The duration of the OFF state is taken as an element and n oN The sending time intervals of the webpage service data packets are respectively added as elements to the initial interval time sequence one by one until the total sending time of the webpage service data packets is reached, thereby obtaining the interval time sequence of the webpage service.

4. The method for generating access traffic for a low-orbit satellite according to claim 1, wherein: The low-orbit satellite service includes a voice service, and generating an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service includes: Determine the total transmission time of voice service data packets; Calculating durations of the voice service in the ON state and the OFF state based on a rate parameter of the voice service in the ON state, a rate parameter of the voice service in the OFF state, and an exponential distribution; The duration of the voice service in the ON state and the OFF state is added as an element to the initial interval time sequence until the total sending time of the voice service data packet is reached, thereby obtaining the interval time sequence of the voice service.

5. The method for generating access traffic for a low-orbit satellite according to claim 1, wherein: The low-orbit satellite service includes a video service, and generating an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service includes: Generate a total time interval I of the video service based on the wavelet scale layer number n and the Gaussian distribution of the mean μ and the variance σ; I is fracted layer by layer from 1 to n, and the total number of video services obtained at the nth layer is 2 n interval time series.

6. The method for generating access traffic for a low-orbit satellite according to claim 1, wherein: The acquiring, based on a base station spatiotemporal traffic data set corresponding to the low-orbit satellite service, a spatiotemporal distribution model of the low-orbit satellite service includes: Collect and aggregate service traffic data sets for a preset time period at a base station at a preset location; Fitting the aggregated service traffic data set with the minimum mean square error as the goal, and using the fitted traffic change over time model as the traffic time distribution model of the low-orbit satellite service; Divide global base stations into 180*360 regions according to longitude and latitude, and count the number of base stations of various signals in each region; Based on the traffic weights of the base stations of the various types of signals, the relative traffic of each area is calculated as elements to form a spatial distribution matrix of size 180*360, and the spatial distribution matrix of size 180*360 is used as the traffic spatial distribution model of the low-orbit satellite service; Obtain the time weight of each of the 180*360 areas, multiply the time weight of each area by the relative traffic of the corresponding area in the traffic spatial distribution model, and obtain the spatiotemporal distribution model of the low-orbit satellite service.

7. The method for generating access traffic for a low-orbit satellite according to claim 6, wherein: The calculating the access traffic size of the low-orbit satellite at any time according to the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service includes: At any time, based on the global satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service, the traffic of each of the 180*360 areas is evenly distributed to the low-orbit satellites in the respective areas; The traffic equally divided by each of the low-orbit satellites is accumulated to calculate the access traffic size of each of the low-orbit satellites at any time.

8. A low-orbit satellite access traffic generation device, characterized in that: The device comprises: A generating module, configured to generate an interval time series of the low-orbit satellite service based on a service model of the low-orbit satellite service; A first acquisition module is configured to acquire a spatiotemporal distribution model of the low-orbit satellite service based on a base station spatiotemporal traffic dataset of a service corresponding to the low-orbit satellite service; Data export module, used to export global low-orbit satellite position and time data through satellite system simulation software; A calculation module, configured to calculate the access traffic size of the low-orbit satellite at any time based on the global low-orbit satellite position time data and the spatiotemporal distribution model of the low-orbit satellite service; A control module is configured to use the interval time sequence of the low-orbit satellite service and the access traffic volume of the low-orbit satellite at any time as control parameters to control the speed and volume of low-orbit satellite service data generated by the network traffic generation software on the client; The second acquisition module is used to obtain a change curve of low-orbit satellite access traffic based on the low-orbit satellite service data sent and received by the server and the client.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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