Intelligent scheduling method based on wireless network gateway station load, storage medium, equipment and computer program product

Abstract

The invention discloses an intelligent scheduling method based on wireless network gateway station load, a storage medium, equipment and a computer program product. The intelligent scheduling method comprises the following steps: deploying a standby gateway station for each gateway station according to a correlation coefficient between the gateway station and the standby gateway station; calculating a wireless signal power attenuation rate of a user beam in a wireless network transmission channel according to weather, if the calculated wireless signal power attenuation rate is lower than an attenuation threshold value, selecting a proper gateway station according to the characteristics of the user beam, and determining idle computing power required by user beam transmission by using a computing power modeling model, a proper transmission channel is selected from the gateway station, and user beam transmission is carried out; and otherwise, selecting a proper gateway station according to the characteristics of the user beam, and carrying out user beam transmission by adopting a standby gateway station corresponding to the gateway station. According to the invention, the resource utilization efficiency of the gateway station is improved, the load balancing of the gateway station is realized, and the influence of weather factors on the communication quality can be greatly reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of integrated space-ground network communications, and in particular, relates to an intelligent scheduling method, storage medium, device and computer program product based on wireless network gateway load. Background Art

[0002] In satellite mobile communication systems, gateways are an important part of the ground segment, responsible for forwarding user terminal communication requests to satellites and transmitting satellite responses back to user terminals. Gateway load refers to the total amount of communication data and number of users processed by the gateway within a certain period of time, which directly reflects the working status and performance of the gateway.

[0003] With the development of information technology and the increase in the number of users, the communication requests that the gateway needs to process will also increase accordingly, resulting in an increase in the load on the gateway. At the same time, the greater the amount of data generated by users during communication, the greater the amount of data that the gateway needs to process, further increasing the load on the gateway.

[0004] The increase in the gateway load may cause the data processing speed to fail to keep up with the speed of data arrival, resulting in increased data transmission delays and affecting the real-time nature of communications. At the same time, the gateway may not be able to effectively process all arriving data packets, resulting in some data packets being lost or processed incorrectly, which in turn affects the accuracy and reliability of communications. Long-term high-load operation may lead to a shortage of gateway system resources, affecting the stability of the gateway system and reducing service quality. In addition, the increase in extreme weather caused by the El Niño phenomenon will also greatly reduce the quality of communication signals received by the gateway, affecting the quality of communications. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides an intelligent scheduling method, storage medium, device and computer program product based on the load of a wireless network gateway, which improves the resource utilization efficiency of the gateway and realizes load balancing of the gateway, thereby improving the real-time, accuracy and reliability of communications, and can greatly reduce the impact of weather factors on communication quality.

[0006] To achieve the above technical objectives, the present invention adopts the following technical solution: an intelligent scheduling method based on wireless network gateway load, specifically comprising the following steps:

[0007] Step S1: deploy a backup gateway station for each gateway station according to the correlation coefficient between the gateway station and the backup gateway station;

[0008] Step S2, calculating the wireless signal power attenuation rate of the user beam in the wireless network transmission channel according to the weather. If the calculated wireless signal power attenuation rate is lower than the attenuation threshold, executing step S3; otherwise, executing step S4;

[0009] Step S3: Select a suitable gateway station according to the characteristics of the user beam, use the computing power quantization model to determine the idle computing power required for the user beam transmission, select a suitable transmission channel from the gateway station, and perform user beam transmission;

[0010] Step S4: Select a suitable gateway according to the characteristics of the user beam, and use the backup gateway corresponding to the gateway to perform user beam transmission.

[0011] Furthermore, the calculation process of the correlation coefficient between the gateway and the standby gateway is as follows:

[0012] ρ=0.94exp(-D / 30)+0.06exp[-(D / 500) 2 ]

[0013] Wherein, ρ represents the correlation coefficient between the gateway station and the corresponding backup gateway station, and D represents the distance between the gateway station and the corresponding backup gateway station.

[0014] Furthermore, the deployment of the backup gateway in step S1 satisfies: ρ<0.1.

[0015] Furthermore, the standby gateway is only equipped with an antenna and a radio frequency link, and the antenna and the radio frequency link are connected via an optical fiber network.

[0016] Furthermore, the wireless signal power attenuation rate of the user beam in the wireless network transmission channel calculated according to the weather includes: the attenuation rate of the rain communication signal, the attenuation rate of the cloudy and foggy communication signal, the attenuation rate of the snowfall communication signal and the attenuation rate of the sandstorm climate communication signal.

[0017] Furthermore, step S3 includes the following sub-steps:

[0018] Step S3.1, select a suitable gateway according to the communication range and service type of the user beam;

[0019] Step S3.2: Use the computing power quantization model to determine the idle computing power required for the user beam transmission, select a transmission channel from the gateway whose idle computing power is higher than the idle computing power required for the user beam transmission, and perform user beam transmission.

[0020] Furthermore, the computing power quantification model in step S3.2 is specifically:

[0021]

[0022] Among them, C br is the idle computing power, n is the number of logic operation chips, i is the index of n, f(a i ) is the mapping function of logical operation, αi is the mapping ratio coefficient of the i-th logic operation chip, q1 (TOPS) is the redundant computing power of the logic operation; m is the number of parallel computing chips, j is the index of m, f(b j ) is the mapping function for parallel computing, β j is the mapping ratio coefficient of the jth parallel computing chip, q2 (FLOPS) is the redundant computing power of parallel computing; p is the number of neural network acceleration chips, k is the index of p, and f(c k ) is the mapping function of neural network acceleration, γ k is the mapping ratio coefficient of the kth neural network acceleration chip, and q3 (FLOPS) is the redundant computing power of neural network acceleration.

[0023] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the intelligent scheduling method based on wireless network gateway load.

[0024] Furthermore, the present invention also provides 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 intelligent scheduling method based on wireless network gateway load is implemented.

[0025] Furthermore, the present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the intelligent scheduling method based on the wireless network gateway load is implemented.

[0026] Compared with the prior art, the present invention has the following beneficial effects: the present invention equips each gateway with a standby gateway based on the intelligent scheduling method of the wireless network gateway load, and activates the standby gateway when the quality of wireless signal transmission decreases due to abnormal weather. Since the standby gateway is far away from the corresponding gateway, the possibility of the standby gateway being in the same abnormal weather is reduced, thereby ensuring the quality of wireless signal transmission. In addition, the present invention determines the idle computing power required for the user beam transmission through a computing power quantization model, and then selects a suitable transmission channel from the gateway, so as to achieve load balancing of the transmission channel in the gateway, ensure the reasonable use of the transmission channel resources of the gateway, avoid wireless signal transmission delay, and improve the real-time, accuracy and reliability of communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the intelligent scheduling method based on wireless network gateway load of the present invention;

[0028] Figure 2 It is a schematic diagram of the deployment of the CITIC Gateway of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is further explained below in conjunction with the accompanying drawings.

[0030] like Figure 1 The flowchart of the intelligent scheduling method based on the wireless network gateway load of the present invention is as follows:

[0031] Step S1: deploy a backup gateway station for each gateway station according to the correlation coefficient between the gateway station and the backup gateway station, such as Figure 2 As shown, the backup gateway is only equipped with an antenna and a radio frequency link, and the antenna and the radio frequency link are connected through an optical fiber network. When the backup gateway is used, the required baseband equipment is still used on the corresponding gateway, which reduces the difficulty of constructing the backup gateway.

[0032] The calculation process of the correlation coefficient between the gateway and the backup gateway in the present invention is:

[0033] ρ=0.94exp(-D / 30)+0.06exp[-(D / 500) 2 ]

[0034] Among them, ρ represents the correlation coefficient between the gateway station and the corresponding backup gateway station, and D represents the distance between the gateway station and the corresponding backup gateway station, in kilometers. The deployment of the backup gateway station satisfies: ρ<0.1. Generally, the distance between the gateway station and the backup gateway station can be calculated based on the correlation coefficient between the gateway station and the backup gateway station. Since the distance between the two is far, the possibility of both being affected by abnormal weather at the same time is reduced.

[0035] Step S2, calculate the wireless signal power attenuation rate of the user beam in the wireless network transmission channel according to the weather. If the calculated wireless signal power attenuation rate is lower than the attenuation threshold, execute step S3; otherwise, execute step S4; when abnormal weather occurs, that is, when the wireless signal power attenuation rate is lower than the attenuation threshold, the wireless signal cannot be transmitted normally, and the backup gateway station is activated. Since the distance between the backup gateway station and the corresponding gateway station is far, the possibility of the backup gateway station being in the same abnormal weather is reduced, and the quality of wireless signal transmission can be guaranteed.

[0036] The wireless signal power attenuation rate of the user beam in the wireless network transmission channel is calculated according to the weather in the present invention, including: the attenuation rate of rain communication signals, the attenuation rate of cloudy and foggy communication signals, the attenuation rate of snowfall communication signals and the attenuation rate of sandstorm climate communication signals.

[0037] The attenuation rate of the rain communication signal in the present invention is γ R The calculation process is:

[0038] γ R =KRA

[0039] Among them, R is the rainfall, K is the parameter when polarized in the horizontal case, and A is the parameter when polarized in the vertical case;

[0040] Attenuation rate of cloudy and foggy communication signals γ cf The calculation process is:

[0041]

[0042] Where f represents the operating frequency, V m For visibility in fog;

[0043] Attenuation rate of snowfall communication signal γ s The calculation process is:

[0044] γ s =7.47×10 -5 f×I(1+5.77×10 -5 f 3 I 0.6 )

[0045] Where, I is the snowfall intensity;

[0046] Attenuation rate of dust weather communication signals γ F The calculation process is:

[0047]

[0048] Among them, σ represents the standard deviation of dust density, ε represents the dielectric constant of dust, N0 is the dust density, and m is the mean dust density.

[0049] Step S3: Select a suitable gateway station according to the characteristics of the user beam, use the computing power quantization model to determine the idle computing power required for the user beam transmission, select a suitable transmission channel from the gateway station, and perform user beam transmission, which can achieve load balancing of the transmission channel in the gateway station, ensure the reasonable use of the transmission channel resources of the gateway station, avoid wireless signal transmission delay, and improve communication real-time, accuracy and reliability; specifically includes the following sub-steps:

[0050] Step S3.1, select a suitable gateway according to the communication range and service type of the user beam;

[0051] Step S3.2: Use the computing power quantization model to determine the idle computing power required for the user beam transmission, select a transmission channel from the gateway whose idle computing power is higher than the idle computing power required for the user beam transmission, and perform user beam transmission.

[0052] The computing power quantification model in the present invention is specifically:

[0053]

[0054] Among them, C br is the idle computing power, n is the number of logic operation chips, i is the index of n, f(a i ) is the mapping function of logical operation, α i is the mapping ratio coefficient of the i-th logic operation chip, q1 (TOPS) is the redundant computing power of the logic operation; m is the number of parallel computing chips, j is the index of m, f(b j ) is the mapping function for parallel computing, β j is the mapping ratio coefficient of the jth parallel computing chip, q2 (FLOPS) is the redundant computing power of parallel computing; p is the number of neural network acceleration chips, k is the index of p, and f(c k ) is the mapping function of neural network acceleration, γ k is the mapping ratio coefficient of the kth neural network acceleration chip, and q3 (FLOPS) is the redundant computing power of neural network acceleration.

[0055] Step S4: Select a suitable gateway according to the characteristics of the user beam, and use the backup gateway corresponding to the gateway to perform user beam transmission. Since the backup gateway is used for a short time, the idle computing resources on each transmission channel are sufficient. A transmission channel is randomly selected for user beam transmission, which can achieve real-time and high-quality transmission of wireless signals.

[0056] The present invention is based on the intelligent scheduling method of wireless network gateway station load, improves the resource utilization efficiency of the gateway station, realizes the load balancing of the gateway station, thereby improving the real-time, accuracy and reliability of communication, and can greatly reduce the impact of weather factors on communication quality.

[0057] In a technical solution of the present invention, a computer-readable storage medium is further provided, storing a computer program, wherein the computer program enables a computer to execute the intelligent scheduling method based on wireless network gateway load.

[0058] In a technical solution of the present invention, an electronic device is also provided, including: 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 intelligent scheduling method based on the wireless network gateway load is implemented.

[0059] In a technical solution of the present invention, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the intelligent scheduling method based on the wireless network gateway load is implemented.

[0060] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0061] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application 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 to be beyond the scope of this application. In the embodiments disclosed in this application, the computer storage medium can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in conjunction with an instruction execution system, device or equipment. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0062] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application 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 to be beyond the scope of this application.

[0063] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. An intelligent scheduling method based on wireless network gateway load, characterized in that: The specific steps include: Step S1: deploy a backup gateway station for each gateway station according to the correlation coefficient between the gateway station and the backup gateway station; Step S2, calculating the wireless signal power attenuation rate of the user beam in the wireless network transmission channel according to the weather. If the calculated wireless signal power attenuation rate is lower than the attenuation threshold, executing step S3; otherwise, executing step S4; Step S3: Select a suitable gateway station according to the characteristics of the user beam, use the computing power quantization model to determine the idle computing power required for the user beam transmission, select a suitable transmission channel from the gateway station, and perform user beam transmission; Step S4: Select a suitable gateway according to the characteristics of the user beam, and use the backup gateway corresponding to the gateway to perform user beam transmission.

2. The intelligent scheduling method based on wireless network gateway load according to claim 1, characterized in that: The calculation process of the correlation coefficient between the gateway and the backup gateway is as follows: ρ=0.94exp(-D / 30)+0.06exp[-(D / 500) 2 ] Wherein, ρ represents the correlation coefficient between the gateway station and the corresponding backup gateway station, and D represents the distance between the gateway station and the corresponding backup gateway station.

3. The intelligent scheduling method based on wireless network gateway load according to claim 2, characterized in that: The deployment of the backup gateway in step S1 satisfies: ρ<0.

1.

4. The intelligent scheduling method based on wireless network gateway load according to claim 1, characterized in that: The standby gateway station is only equipped with an antenna and a radio frequency link, and the antenna and the radio frequency link are connected via an optical fiber network.

5. The intelligent scheduling method based on wireless network gateway load according to claim 1, characterized in that: The wireless signal power attenuation rate of the user beam in the wireless network transmission channel calculated according to the weather includes: the attenuation rate of the rain communication signal, the attenuation rate of the cloudy and foggy communication signal, the attenuation rate of the snowfall communication signal and the attenuation rate of the dust climate communication signal.

6. The intelligent scheduling method based on wireless network gateway load according to claim 5, characterized in that: Step S3 includes the following sub-steps: Step S3.1, select a suitable gateway according to the communication range and service type of the user beam; Step S3.2: Use the computing power quantization model to determine the idle computing power required for the user beam transmission, select a transmission channel from the gateway whose idle computing power is higher than the idle computing power required for the user beam transmission, and perform user beam transmission.

7. The intelligent scheduling method based on wireless network gateway load according to claim 5, characterized in that: The specific calculation power quantification model in step S3.2 is: Among them, C br is the idle computing power, n is the number of logic operation chips, i is the index of n, f(a i ) is the mapping function of logical operation, α i is the mapping ratio coefficient of the i-th logic operation chip, q1 (TOPS) is the redundant computing power of the logic operation; m is the number of parallel computing chips, j is the index of m, f(b j ) is the mapping function for parallel computing, β j is the mapping ratio coefficient of the jth parallel computing chip, q2 (FLOPS) is the redundant computing power of parallel computing; p is the number of neural network acceleration chips, k is the index of p, and f(c k ) is the mapping function of neural network acceleration, γ k is the mapping ratio coefficient of the kth neural network acceleration chip, and q3 (FLOPS) is the redundant computing power of neural network acceleration.

8. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the intelligent scheduling method based on wireless network gateway load as described in any one of claims 1 to 7.

9. An electronic device, characterized in that: include: 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 intelligent scheduling method based on the load of a wireless network gateway is implemented as claimed in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the intelligent scheduling method based on wireless network gateway load according to any one of claims 1 to 7 is implemented.

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