Data processing method and device based on cloud base station, equipment and storage medium

Abstract

The invention provides a data processing method and device based on a cloud base station, equipment and a storage medium. The method is applied to an acceleration server, a physical layer accelerator is deployed in the acceleration server, the acceleration server is in communication connection with a plurality of base station servers, cloud base stations are deployed on the base station servers, and the base station servers are used for executing services of the cloud base stations. The method comprises the following steps: receiving to-be-processed data sent by a base station server; wherein the to-be-processed data represents data generated by executing the service of the cloud base station, the to-be-processed data comprises a server identifier of a base station server, and the server identifier is used for representing the base station server; processing the to-be-processed data based on a physical layer accelerator in the acceleration server to obtain processed data; and feeding back the processed data to the base station server according to the server identifier in the to-be-processed data. According to the method, the hardware use cost is saved, the data processing efficiency is improved, and the flexibility of cloud base station service deployment is improved.

Description

Technical Field

[0001] This application relates to the field of communications, and in particular to a data processing method, apparatus, device, and storage medium based on a cloud base station. Background Technology

[0002] A base station typically consists of a baseband unit (BBU) and a remote radio unit (RRU). Cloud base stations use a general-purpose CPU processor as the core server of the base station to handle most of the functions of the BBU.

[0003] However, general-purpose CPU processors have low processing efficiency for some functional modules of the base station's physical layer, requiring the use of dedicated physical layer accelerators to improve processing efficiency. How to combine physical layer accelerators to improve data processing efficiency is a pressing issue that needs to be addressed. Summary of the Invention

[0004] This application provides a data processing method, apparatus, device, and storage medium based on a cloud base station to improve the data processing efficiency of the cloud base station.

[0005] In a first aspect, this application provides a data processing method based on a cloud base station. This method is applied to an acceleration server, which deploys a physical layer accelerator. The acceleration server communicates with multiple base station servers, and the cloud base station is deployed on the base station servers. The base station servers are used to execute the services of the cloud base station. The method includes:

[0006] Receive pending data sent by the base station server; wherein, the pending data represents data generated by executing the services of the cloud base station, and the pending data includes the server identifier of the base station server, which is used to identify the base station server;

[0007] Based on the physical layer accelerator in the acceleration server, the data to be processed is processed to obtain processed data;

[0008] Based on the server identifier in the data to be processed, the processed data is fed back to the base station server.

[0009] Secondly, this application provides a data processing apparatus based on a cloud base station. This apparatus is applied to an acceleration server, which deploys a physical layer accelerator. The acceleration server communicates with multiple base station servers. The cloud base station is deployed on the base station servers, and the base station servers execute the services of the cloud base station. The apparatus includes:

[0010] The data receiving module is used to receive data to be processed sent by the base station server; wherein, the data to be processed represents the data generated by performing the services of the cloud base station, and the data to be processed includes the server identifier of the base station server, which is used to identify the base station server.

[0011] The data processing module is used to process the data to be processed based on the physical layer accelerator in the acceleration server to obtain processed data.

[0012] The data feedback module is used to feed back the processed data to the base station server based on the server identifier in the data to be processed.

[0013] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0014] The memory stores computer-executed instructions;

[0015] The processor executes computer execution instructions stored in the memory to implement the method as described in the first aspect.

[0016] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0017] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0018] This application provides a data processing method, apparatus, device, and storage medium based on a cloud base station. The cloud base station is deployed on a base station server, which executes the cloud base station's services. The base station server can communicate with an acceleration server, which deploys a physical layer accelerator. This allows the acceleration server to operate independently of the base station server, eliminating the need to bind accelerators to each base station server, saving hardware costs, increasing the flexibility of base station server deployment, and facilitating base station server upgrades. The acceleration server can receive data to be processed from the base station server in real time, process the data based on the physical layer accelerator in the acceleration server, and obtain processed data. Then, based on the server identifier in the data to be processed, the processed data is fed back to the corresponding base station server, which continues to execute the services. This application embodiment achieves accelerated data processing through an independent acceleration server, supports resource sharing of accelerators among base station servers, reduces the power consumption of the cloud base station, and improves data processing efficiency. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] Figure 1 A flowchart illustrating a data processing method based on a cloud base station provided in an embodiment of this application;

[0021] Figure 2 A server communication architecture diagram provided for embodiments of this application;

[0022] Figure 3 A flowchart illustrating a data processing method based on a cloud base station provided in an embodiment of this application;

[0023] Figure 4 An architecture diagram of the acceleration server provided in the embodiments of this application;

[0024] Figure 5 A structural block diagram of a data processing device based on a cloud base station provided in an embodiment of this application;

[0025] Figure 6 A structural block diagram of a data processing device based on a cloud base station provided in an embodiment of this application;

[0026] Figure 7 A structural block diagram of an electronic device provided in an embodiment of this application;

[0027] Figure 8 This is a structural block diagram of an electronic device provided in an embodiment of this application.

[0028] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0030] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0031] In the following description, when referring to the accompanying drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0032] In the description of this application, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0033] It should be noted that, due to space limitations, this application specification does not exhaustively list all possible implementation methods. Those skilled in the art, after reading this application specification, should be able to deduce that, as long as the technical features do not contradict each other, any combination of technical features can constitute an optional implementation method. The following provides a detailed description of each embodiment.

[0034] Base station systems typically consist of two parts: a Baseband Unit (BBU) and a Remote Response Unit (RRU). The BBU handles the baseband protocol stack and algorithm processing, while the RRU handles mid-range and radio frequency (RF) signal processing. Traditional base station BBUs use dedicated processors such as Digital Signal Processors (DSPs) / Field-Programmable Gate Arrays (FPGAs) or Application Specific Integrated Circuits (ASICs) as their core processors. Cloud base stations use a general-purpose CPU as the core server, along with a physical layer accelerator. The general-purpose processor can be an x86 processor, capable of handling most of the BBU's protocol stack and algorithm functions. The physical layer consists of computationally more complex modules. Due to the lower processing efficiency of x86 processors, a dedicated physical layer accelerator is needed to improve processing efficiency and specifications.

[0035] To improve processing efficiency, physical layer accelerators can be placed externally to general-purpose processors. For example, a physical layer accelerator can be added outside the CPU via a server expansion card. The physical layer accelerator can connect to the CPU through interfaces such as PCI Express (PCIe). The physical layer accelerator can be an FPGA, a Graphics Processing Unit (GPU), etc. Alternatively, the physical layer accelerator can be integrated into the chip, meaning it's built into the CPU.

[0036] However, for solutions using external chip accelerators, a physical layer accelerator needs to be added to each CPU, such as a dedicated accelerator card on each server. This significantly increases cost and power consumption, and the base station service must be tied to the server with the added accelerator card, severely impacting the flexibility of cloud base station deployment. For solutions using integrated chip accelerators, chips with built-in physical layer accelerators must be used, resulting in strong dependence on dedicated hardware. Furthermore, general-purpose cloud platform CPUs typically do not have built-in physical layer accelerators, thus losing processor versatility and making direct deployment on existing cloud servers impossible. In other words, cloud base station services must be deployed on servers with existing built-in or external accelerators. Upgrading the physical layer accelerator in a base station requires upgrading all servers, wasting resources and impacting the efficiency of the cloud base station.

[0037] This application provides a data processing method, apparatus, device, and storage medium based on a cloud base station, relating to the field of communications, particularly the field of mobile communication base stations, and aims to solve the above-mentioned technical problems in the prior art.

[0038] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0039] Figure 1 This is a flowchart illustrating a data processing method based on a cloud base station according to an embodiment of this application. This method can be executed by a data processing device based on a cloud base station. The method is applied to an acceleration server, which deploys a physical layer accelerator. The acceleration server communicates with multiple base station servers. The cloud base station is deployed on the base station servers, and the base station servers execute the services of the cloud base station. Figure 1 As shown, the method includes the following steps:

[0040] S101. Receive data to be processed sent by the base station server; wherein, the data to be processed represents the data generated by executing the cloud base station's services, and the data to be processed includes the server identifier of the base station server, which is used to identify the base station server.

[0041] For example, cloud base station services are deployed on general-purpose cloud platform hardware, such as general-purpose x86 servers. The server deploying the cloud base station is a base station server. In this embodiment, no hardware modification is required to the base station server; for example, no dedicated board with a physical layer accelerator needs to be inserted to directly deploy the cloud base station services. The base station server can execute various services of the cloud base station. The cloud platform includes base station servers and acceleration servers; that is, one or more acceleration servers can be added to a general-purpose base station server. The acceleration servers have high-specification, high-energy-efficiency physical layer hardware acceleration modules. Specifically, at least one acceleration server is deployed, and the acceleration server is a server containing a physical layer accelerator. The acceleration server can communicate with multiple base station servers to provide physical layer acceleration services to cells on multiple base station servers. In this embodiment, a cell refers to the area covered by the base station, and the base station server can provide base station services to the cell. The acceleration server can use a general-purpose processor with a built-in accelerator of the same architecture as the base station server, or it can use a dedicated processor heterogeneous with the base station server. In this embodiment, there are no specific limitations on the hardware selection of the physical layer accelerator. For example, the physical layer accelerator can be a Radio Access Network (RAN) accelerator, and the acceleration server can be a general-purpose processor with a built-in RAN accelerator.

[0042] When executing cloud base station services, the base station server can generate service-related data as pending data. That is, pending data represents the data generated during the execution of cloud base station services. The base station server can send the pending data to the acceleration server in real time, and the acceleration server receives the pending data from the base station server in real time. For example, pending data can be data to be encoded or data to be decoded.

[0043] The acceleration server can communicate with multiple base station servers, each with its own server identifier. When sending data to be processed, different base station servers can send their own server identifiers to the acceleration server; that is, the data to be processed can include the server identifiers of the base station servers, which identify the server. In this embodiment, the content and data structure of the data to be processed are not specifically limited. For example, the data to be processed may also include user communication content and phone numbers.

[0044] In this embodiment, the acceleration server and each base station server are equipped with a network interface card (NIC), and the acceleration server and each base station server communicate with each other through a preset switch. Receiving data to be processed sent by the base station server includes: receiving data to be processed transmitted from the preset switch through the NIC configured on the acceleration server; wherein the data to be processed is transmitted to the switch based on the NIC of the base station server.

[0045] Specifically, the acceleration server interconnects with the base station server deploying the cloud base station service via a high-speed network interface card (NIC) and a switch, centralizing the physical layer acceleration functions of all cells deployed on the base station server onto the acceleration server for accelerated processing. The server is equipped with a NIC; in this embodiment, both the acceleration server and the base station server have NICs, and a switch connects them. Figure 2 This is a diagram of the server communication architecture. Figure 2 There are N base station servers and one acceleration server. Both the base station servers and the acceleration server are x86 servers. The acceleration server has a built-in acceleration (ACC) device as a physical layer accelerator. The base station servers and the acceleration server are connected through a switch.

[0046] The base station server sends the data to be processed to the acceleration server via the network interface card (NIC) and the switch. The acceleration server then receives the data to be processed from the switch via the NIC, thus achieving the reception of the data to be processed.

[0047] The advantage of this setup is that the acceleration server communicates with the base station server through a high-speed network card and switch, ensuring that it can receive the data to be processed in a timely manner, thereby processing the data and effectively improving the efficiency of data processing.

[0048] S102. Based on the physical layer accelerator in the acceleration server, the data to be processed is processed to obtain the processed data.

[0049] For example, after receiving the data to be processed, the acceleration server can utilize its built-in physical layer accelerator to accelerate the processing of the data, obtaining the processed data. For instance, the acceleration server may have a built-in Low Density Parity Check (LDPC) encoding accelerator, which can accelerate the processing of the received data to be encoded, identifying the encoded data as the processed data. In this embodiment, the specific data processing procedure is not limited.

[0050] Acceleration servers can employ various hardware solutions, such as x86 processors with built-in Virtual Radio Access Network (vRAN) accelerators, FPGAs, eASICs, and GPUs. In this embodiment, the acceleration server uses an x86 processor with a built-in vRAN boost accelerator, isomorphic to the base station server. Besides performing base station acceleration services, the acceleration server can also run other cloud base station services. Virtualization technologies, such as container technology, can be used to isolate different services, fully utilizing processor hardware resources. This embodiment does not specifically limit the virtualization technology used for isolation. Virtualization technologies such as container technology can be used to divide resources into independent groups to better balance conflicting resource usage demands between these groups. That is, a preset virtualization technology can be used to divide the resources in the acceleration server into multiple resource groups, each representing a portion of the resources in the acceleration server. The acceleration server can also execute cloud base station related services; for example, the acceleration server receives service data from the cloud base station, which represents the services to be processed in the cloud base station. A target resource group is determined from multiple resource groups; for example, the resource group with the most remaining resources can be identified as the target resource group. By utilizing resources from the target resource group, the service data of the cloud base station is processed, enabling the execution of cloud base station services using the acceleration server.

[0051] S103. Based on the server identifier in the data to be processed, the processed data is fed back to the base station server.

[0052] For example, the data to be processed contains a server identifier. The acceleration server can determine which base station server sent the data based on the server identifier. After receiving the processed data, it can send the processed data to the corresponding base station server based on the server identifier in the data to be processed. That is, the processed data is sent to the base station server from which the data to be processed originated. For example, a base station server deploying cloud base station services sends the data to be encoded from the base station service to the acceleration server through a network card and a switch. The acceleration server calls its internal LDPC encoding hardware accelerator to complete the LDPC encoding process, and then returns the LDPC-encoded data packet to the original base station server.

[0053] The acceleration server can add a server identifier to the processed data. After receiving the processed data, the base station server can retrieve the server identifier from the processed data and determine whether the server identifier is its own server identifier. If it is, the received data is correct and the service can continue to be executed; if not, the data reception is incorrect and a prompt message can be sent to the acceleration server to remind it to resend the processed data.

[0054] Physical layer accelerators centrally process pending data from various services, supporting more cells to share accelerator hardware resources. This results in high hardware resource utilization and significantly reduces the additional hardware investment cost and power consumption of cloud base station deployments. It also makes cloud base station service deployment more flexible, eliminating the need to bind to servers with dedicated accelerators within the cloud platform. Cloud base station services and cells can be flexibly deployed and migrated on any server. This maximizes the versatility of cloud base station hardware and reduces additional investment for upgrades. For example, when upgrading from 5G to 6G, only a 6G-compatible physical layer accelerator needs to be added; other servers can continue to be used through software upgrades for the cloud base station service.

[0055] In this embodiment, the processed data is fed back to the base station server, including: transmitting the processed data to a preset switch via a network interface card configured on the acceleration server; wherein the preset switch is used to transmit the processed data to the network interface card of the base station server corresponding to the server identifier.

[0056] Specifically, when sending processed data, the acceleration server can transmit it through its own network card and then forward it to the base station server via a switch. One acceleration server can simultaneously provide physical layer acceleration services to multiple cells on multiple base station servers; therefore, it can send processed data to the base station server corresponding to its identifier.

[0057] The switch sends the processed data to the network card of the base station server, and the base station server can receive the processed data through its own network card.

[0058] The advantage of this setup is that it accelerates communication between the server and the base station server via high-speed network cards and switches, ensuring that processed data can be sent in a timely manner, thereby completing the execution of cloud base station services and effectively improving data processing efficiency and service execution efficiency.

[0059] In this embodiment, the cloud base station is deployed on a base station server. The base station server executes the cloud base station's services and can communicate with an acceleration server, which contains a physical layer accelerator. This allows the acceleration server to operate independently of the base station server, eliminating the need to bind accelerators to each base station server, saving hardware costs, increasing the flexibility of base station server deployment, and facilitating base station server upgrades. The acceleration server can receive data to be processed from the base station server in real time, process the data using its physical layer accelerator, and obtain processed data. Then, based on the server identifier in the data to be processed, the processed data is fed back to the corresponding base station server, which continues to execute the services. This achieves accelerated data processing through an independent acceleration server, supports resource sharing of accelerators among base station servers, reduces the power consumption of the cloud base station, and improves data processing efficiency.

[0060] Figure 3 This is a flowchart illustrating a data processing method based on a cloud base station according to an embodiment of this application. This method can be executed by a data processing device based on a cloud base station.

[0061] In this embodiment, the data to be processed is processed based on the physical layer accelerator in the acceleration server to obtain processed data, including: determining the processing priority of the data to be processed; and calling the physical layer accelerator in the acceleration server to process the data to be processed according to the processing priority of the data to be processed to obtain processed data.

[0062] like Figure 3 As shown, the method includes the following steps:

[0063] S301. Receive data to be processed sent by the base station server; wherein, the data to be processed represents the data generated by executing the cloud base station's services, and the data to be processed includes the server identifier of the base station server, which is used to identify the base station server.

[0064] For example, this step can refer to step S101 above, and will not be repeated here.

[0065] S302. Determine the processing priority of the data to be processed.

[0066] For example, different data to be processed can correspond to different processing priorities. The processing priority can represent the urgency or priority of the data to be processed. For instance, the processing priorities of data to be processed under different business scenarios can be different. The data to be processed can include the processing priority, that is, the processing priority of the data can be directly obtained from the data to be processed.

[0067] The data to be processed may include information related to processing priority. This information is retrieved from the data, and the corresponding processing priority is found and used as the processing priority for the data to be processed. For example, different services may correspond to different processing priorities; some services have high processing priorities, while others have low processing priorities. The data to be processed may also include service-related identifiers. By obtaining these identifiers, it is possible to determine which service the data to be processed belongs to, and thus determine the priority of that service, thereby obtaining the processing priority of the data to be processed.

[0068] S303. Based on the processing priority of the data to be processed, call the physical layer accelerator in the acceleration server to process the data to be processed and obtain the processed data.

[0069] For example, since multiple servers and multiple cells share the physical layer accelerator, data queuing may be required during busy periods, leading to increased data processing latency. To ensure the real-time processing requirements of high-priority users and low-latency services, data to be processed can be processed according to processing priority.

[0070] When processing data, physical layer accelerators in the acceleration server can be used. After determining the processing priority of the data, the physical layer accelerator can be invoked according to the priority level. The physical layer accelerator accelerates the processing of the data to obtain the processed data. For example, data with high processing priority can be processed by the physical layer accelerator first; data with low processing priority can be processed by delaying the invocation of the physical layer accelerator.

[0071] Different physical layer accelerators can also be configured in the acceleration server, with different processing priorities corresponding to different physical layer accelerators. Based on the processing priority of the data to be processed, the physical layer accelerator corresponding to that priority is determined, and then that physical layer accelerator is invoked to process the data.

[0072] In this embodiment, the physical layer accelerator in the acceleration server is invoked according to the processing priority of the data to be processed to process the data and obtain the processed data. This includes: caching the data to be processed in a preset waiting queue according to the processing priority of the data to be processed; wherein, the preset waiting queue contains multiple unprocessed data; if the data to be processed is located at a preset sorting position in the preset waiting queue, the physical layer accelerator in the acceleration server is invoked to process the data to be processed to obtain the processed data.

[0073] Specifically, a pre-set waiting queue is used to hold unprocessed pending data. Pending data can be cached in the pre-set waiting queue according to its processing priority, with multiple unprocessed data items arranged in the queue. For example, higher-priority pending data can be placed first, and lower-priority pending data last. The physical layer accelerator can process the first pending data item in the queue each time, that is, it processes the most urgent or highest-priority pending data at a time.

[0074] It can determine in real time whether the data to be processed is located at a preset sorting position in the waiting queue, for example, the first position. If the data to be processed is located at the preset sorting position in the waiting queue, the physical layer accelerator in the acceleration server can be invoked to process the data and obtain the processed data; if the data to be processed is not located at the preset sorting position in the waiting queue, the data ahead of the data to be processed can be processed first until the data to be processed is located at the preset sorting position, and then the data to be processed can be processed.

[0075] The advantage of this setup is that data to be processed can be placed in a waiting queue according to its priority. When data is first in the queue, it can be processed. This ensures the real-time processing requirement for high-priority data and improves data processing efficiency.

[0076] In this embodiment, the data to be processed includes cell information, where cell information represents the cell that issued the data to be processed, and processing priority represents the priority of the cell corresponding to the cell information. According to the processing priority of the data to be processed, the data to be processed is cached in a preset waiting queue, which includes: according to the priority of the cell corresponding to the cell information, the data to be processed is cached in a preset first waiting queue.

[0077] Specifically, the data to be processed can be sent from different cells. The data to be processed can include cell information, which represents the cell that sent the data. For example, the cell information can be the cell's identifier. Different cells have different priorities, and the priority of a cell can be used as the processing priority for the data to be processed sent by that cell.

[0078] Cell information is obtained from the data to be processed, and the cell from which the data was sent is determined based on this information. Different cell priorities are pre-defined, and the priority of each cell is used as the processing priority for the data to be processed. A first waiting queue is pre-defined to store the data to be processed, and the data in the first waiting queue is differentiated by cell priority. Based on the priority of the cell corresponding to the cell information, which is also the processing priority of the data to be processed, the data to be processed is cached in the pre-defined first waiting queue. For example, if the cell corresponding to the cell information has a higher priority, it can be placed earlier in the first waiting queue; if the cell corresponding to the cell information has a lower priority, it can be placed later in the first waiting queue.

[0079] The advantage of this setup is that it distinguishes different priorities by cell level and places the data to be processed in a specific waiting queue, enabling targeted processing of the data to be processed according to cell level and improving the efficiency of data processing.

[0080] In this embodiment, the data to be processed includes user information, where the user information represents the user who sent the data to be processed, and the processing priority represents the priority of the user corresponding to the user information. According to the priority information in the data to be processed, the data to be processed is cached in a preset waiting queue, which includes: according to the priority of the user corresponding to the user information, the data to be processed is cached in a preset second waiting queue.

[0081] Specifically, the data to be processed can be sent by different users. This data may include user information, which identifies the user who sent the data; for example, the user's number or other identifier. Different users have different priorities, and this priority serves as the processing priority for the data sent by that user.

[0082] User information is retrieved from the data to be processed, and the user who sent the data is identified based on this information. Priorities for different users are pre-defined, and this priority is used as the processing priority for the data to be processed. A second waiting queue is pre-defined to store the data to be processed, and the data in the second waiting queue is differentiated by user priority. Based on the priority of the user information, which is also the processing priority of the data to be processed, the data to be processed is cached in the pre-defined second waiting queue. For example, if the user information corresponds to a higher priority user, it can be placed at the beginning of the second waiting queue; if the user information corresponds to a lower priority user, it can be placed at the end of the second waiting queue.

[0083] The advantage of this setup is that it differentiates different priorities based on user levels and places the data to be processed in a specific waiting queue, enabling targeted processing of data according to user needs. This ensures the real-time processing requirements of high-priority users and improves the efficiency of data processing.

[0084] In this embodiment, the data to be processed includes business information, which represents the business corresponding to the data to be processed, and the processing priority represents the priority of the business corresponding to the business information. According to the priority information in the data to be processed, the data to be processed is cached in a preset waiting queue, including: according to the priority of the business corresponding to the business information, the data to be processed is cached in a preset third waiting queue.

[0085] Specifically, the data to be processed can be data generated during the execution of different business processes. This data can include business information, which represents the business process corresponding to the data. For example, business information can be a business identifier. Different businesses have different priorities, and the priority of a business can be used as the processing priority for the data to be processed corresponding to that business.

[0086] Retrieve business information from the data to be processed, and determine the corresponding business based on this information. Pre-set priorities for different business processes, and determine the priority of each business process as the processing priority for the data to be processed. Pre-set a third waiting queue to store the data to be processed, with each piece of data in the third waiting queue differentiated by business priority. Based on the priority of the business process corresponding to the business information, which is also the processing priority of the data to be processed, cache the data to be processed in the pre-set third waiting queue. For example, if the business process corresponding to the business information has a higher priority, it can be placed earlier in the third waiting queue; if the business process corresponding to the business information has a lower priority, it can be placed later in the third waiting queue.

[0087] The advantage of this setup is that it distinguishes different priorities based on business level and places the data to be processed in a specific waiting queue, enabling targeted processing of the data to be processed according to business needs, ensuring the real-time processing requirements of low-latency business and improving the efficiency of data processing.

[0088] In this embodiment, determining the processing priority of the data to be processed includes: determining target information from the cell information, user information, and service information based on the priority of the cell corresponding to the cell information, the priority of the user corresponding to the user information, and the priority of the service corresponding to the service information; and determining the priority corresponding to the target information as the processing priority of the data to be processed.

[0089] Specifically, the data to be processed may include one or more of the following: cell information, user information, and service information. Within the same set of data, the priorities of the cell information (cell), the user information (user), and the service information (service) may be the same or different. The cell information, user information, and service information can be determined from the data to be processed, and the processing priority of the data can be determined based on these priorities. For example, the highest priority among these three can be set as the priority of the data to be processed. Alternatively, one type of information can be determined from the cell information, user information, and service information, and the priority corresponding to that determined information can be set as the processing priority of the data to be processed.

[0090] The priority of the cell corresponding to cell information, the priority of the user corresponding to user information, and the priority of the service corresponding to service information can be determined. Based on the priority of these three types of information, one type of information is selected as the target information. For example, the information with the highest priority can be selected as the target information. The priority corresponding to the target information is then determined as the processing priority of the data to be processed. For example, if the target information is cell information, then the priority of the cell corresponding to that cell information is determined as the processing priority of the data to be processed.

[0091] The advantage of this setup is that it allows selection from multiple types of information to determine the processing priority of the data to be processed, avoiding confusion in determining the processing priority due to different priorities of different types of information, and effectively improving the efficiency of data processing.

[0092] In this embodiment, according to the processing priority of the data to be processed, the data to be processed is cached in a preset waiting queue, including: determining the waiting queue corresponding to the target information as the target waiting queue; wherein, the target waiting queue is a first waiting queue, a second waiting queue, or a third waiting queue; and caching the data to be processed in the target waiting queue.

[0093] Specifically, different types of information in the data to be processed can be pre-defined into different waiting queues. For example, cell information corresponds to the first waiting queue, user information corresponds to the second waiting queue, and service information corresponds to the third waiting queue. After determining the target information, the waiting queue corresponding to the target information is determined as the target waiting queue. The target waiting queue can be the first, second, or third waiting queue. For example, if the target information is cell information, then the target waiting queue is the first waiting queue. According to the priority corresponding to the target information, the data to be processed is cached in the target waiting queue.

[0094] The advantage of this setup is that multiple waiting queues can be preset, and one of them can be selected to place the data to be processed. This allows for priority processing of data based on different levels of information, thereby improving the efficiency of data processing.

[0095] In this embodiment, multiple physical layer accelerators are deployed in the acceleration server. If the data to be processed is located at a preset sorting position in a preset waiting queue, the physical layer accelerators in the acceleration server are invoked to process the data to obtain processed data. This includes: if the data to be processed is located at a preset sorting position in the preset waiting queue, determining the service type corresponding to the data to be processed; determining the physical layer accelerator associated with the service type corresponding to the data to be processed as the target accelerator based on the preset association relationship between the service type and the physical layer accelerators; and invoking the target accelerator to process the data to be processed to obtain processed data.

[0096] Specifically, an acceleration server can include multiple physical layer accelerators, such as Turbo parallel concatenated convolutional code (Turbo parallel concatenated convolutional code) encoding accelerators, Turbo decoding accelerators, LDPC encoding accelerators, and LDPC decoding accelerators. Different physical layer accelerators can perform different processing procedures, and different business types require different processing procedures; that is, different physical layer accelerators can correspond to different business types. When data needs to be processed, the required physical layer accelerator can be determined, and the corresponding physical layer accelerator can then be used for processing.

[0097] In other words, it can determine whether the data to be processed is located in the preset sorting position in the waiting queue. If so, the business type corresponding to the data to be processed is determined, and the physical layer accelerator associated with the business type corresponding to the data to be processed is determined as the target accelerator based on the preset association between the business type and the physical layer accelerator. If not, it continues to determine whether the data to be processed is located in the preset sorting position in the waiting queue until the data to be processed is located in the preset sorting position.

[0098] After determining the target accelerator, it is invoked. The target accelerator accelerates the processing of the data to be processed, resulting in processed data. For example, if the data to be processed is Turbo data to be encoded, a Turbo encoding accelerator can be used to process the data.

[0099] Figure 4 To accelerate the server architecture diagram, Figure 4The acceleration server can include an interface data transfer module, a waiting queue module, an accelerator scheduling module, and an accelerator module. The interface data transfer module is responsible for storing the data received from the network interface card (NIC) into corresponding waiting queues according to service type or target information type. It determines the position of the data in the waiting queue based on the processing priority, and the data in the waiting queue can be arranged in descending order of priority. The waiting queue module can pre-set different waiting queues according to different service types or different types of information. For example, it can pre-set LDPC encoding and decoding waiting queues, or waiting queues corresponding to cell information and user information. The interface data transfer module is also responsible for packaging and sending the processed data to the corresponding base station server.

[0100] The accelerator scheduling module can extract data to be processed from each waiting queue according to a preset priority scheduling strategy and send it to the corresponding physical layer accelerator for processing. The accelerator module includes multiple physical layer accelerators. Each physical layer accelerator receives the processed data and feeds it back to the base station server through the interface data transfer module.

[0101] The advantage of this setup is that by setting up different physical layer accelerators, different types of data can be processed in a targeted manner, thereby improving the efficiency and accuracy of data processing.

[0102] S304. Based on the server identifier in the data to be processed, the processed data is fed back to the base station server.

[0103] For example, this step can refer to step S103 above, and will not be repeated here.

[0104] In this embodiment, the cloud base station is deployed on a base station server. The base station server executes the cloud base station's services and can communicate with an acceleration server, which contains a physical layer accelerator. This allows the acceleration server to operate independently of the base station server, eliminating the need to bind accelerators to each base station server, saving hardware costs, increasing the flexibility of base station server deployment, and facilitating base station server upgrades. The acceleration server can receive data to be processed from the base station server in real time, process the data using its physical layer accelerator, and obtain processed data. Then, based on the server identifier in the data to be processed, the processed data is fed back to the corresponding base station server, which continues to execute the services. This achieves accelerated data processing through an independent acceleration server, supports resource sharing of accelerators among base station servers, reduces the power consumption of the cloud base station, and improves data processing efficiency.

[0105] Figure 5 This is a structural block diagram of a data processing device based on a cloud base station, provided as an embodiment of this application. For ease of explanation, only the parts relevant to the embodiments of this disclosure are shown. The device is applied to an acceleration server, which deploys a physical layer accelerator. The acceleration server communicates with multiple base station servers. The cloud base station is deployed on the base station servers, which execute the services of the cloud base station. (Refer to...) Figure 5 The device includes: a data receiving module 501, a data processing module 502, and a data feedback module 503.

[0106] The data receiving module 501 is used to receive data to be processed sent by the base station server; wherein, the data to be processed represents the data generated by performing the services of the cloud base station, and the data to be processed includes the server identifier of the base station server, which is used to identify the base station server.

[0107] Data processing module 502 is used to process the data to be processed based on the physical layer accelerator in the acceleration server to obtain processed data;

[0108] The data feedback module 503 is used to feed back the processed data to the base station server according to the server identifier in the data to be processed.

[0109] Figure 6 This application provides a structural block diagram of a data processing device based on a cloud base station, in which... Figure 5 Based on the illustrated embodiments, as Figure 6 As shown, the data processing module 502 includes a priority determination unit 5021 and a data processing unit 5022.

[0110] Priority determination unit 5021 is used to determine the processing priority of the data to be processed;

[0111] The data processing unit 5022 is used to call the physical layer accelerator in the acceleration server to process the data to be processed according to the processing priority of the data to be processed, and obtain the processed data.

[0112] In one example, the data processing unit 5022 includes:

[0113] A data caching subunit is used to cache the data to be processed into a preset waiting queue according to the processing priority of the data to be processed; wherein, the preset waiting queue contains multiple unprocessed data.

[0114] The data processing subunit is used to call the physical layer accelerator in the acceleration server to process the data to be processed and obtain the processed data if the data to be processed is located at a preset sorting position in the preset waiting queue.

[0115] In one example, the data to be processed includes cell information, whereby the cell information represents the cell that issued the data to be processed, and the processing priority represents the priority of the cell corresponding to the cell information; the data buffer subunit is specifically used for:

[0116] Based on the priority of the cell corresponding to the cell information, the data to be processed is cached in a preset first waiting queue.

[0117] In one example, the data to be processed includes user information, whereby the user information represents the user who issued the data to be processed, and the processing priority represents the priority of the user corresponding to the user information; the data caching subunit is specifically used for:

[0118] Based on the priority of the user corresponding to the user information, the data to be processed is cached in a preset second waiting queue.

[0119] In one example, the data to be processed includes business information, which represents the business corresponding to the data to be processed, and the processing priority represents the priority of the business corresponding to the business information; the data caching subunit is specifically used for:

[0120] Based on the priority of the business corresponding to the business information, the data to be processed is cached in a preset third waiting queue.

[0121] In one example, priority determination unit 5021 is specifically used for:

[0122] The cell information, user information, and service information are determined from the data to be processed;

[0123] The processing priority of the data to be processed is determined based on the priority of the cell corresponding to the cell information, the priority of the user corresponding to the user information, and the priority of the service corresponding to the service information.

[0124] In one example, priority determination unit 5021 is specifically used for:

[0125] Based on the priority of the cell corresponding to the cell information, the priority of the user corresponding to the user information, and the priority of the service corresponding to the service information, the target information is determined from the cell information, user information, and service information.

[0126] The priority corresponding to the target information is determined as the processing priority of the data to be processed.

[0127] In one example, the data caching subunit is specifically used for:

[0128] The waiting queue corresponding to the target information is determined as the target waiting queue; wherein, the target waiting queue is the first waiting queue, the second waiting queue, or the third waiting queue;

[0129] The data to be processed is cached in the target waiting queue.

[0130] In one example, the acceleration server deploys multiple physical layer accelerators; the data processing subunit is specifically used for:

[0131] If the data to be processed is located at a preset sorting position in the preset waiting queue, then the business type corresponding to the data to be processed is determined.

[0132] Based on the preset association between service types and physical layer accelerators, determine the physical layer accelerator associated with the service type corresponding to the data to be processed, and designate it as the target accelerator.

[0133] The target accelerator is invoked to process the data to be processed, thereby obtaining the processed data.

[0134] In one example, the acceleration server and each of the base station servers are equipped with network interface cards (NICs), and the acceleration server and each base station server communicate with each other through a preset switch; the data receiving module 501 is specifically used for:

[0135] The network interface card (NIC) configured on the acceleration server receives data to be processed transmitted from the preset switch; wherein the data to be processed is transmitted to the switch based on the NIC of the base station server.

[0136] Data feedback module 503 is specifically used for;

[0137] The processed data is transmitted to the preset switch via the network interface card (NIC) configured on the acceleration server; wherein the preset switch is used to transmit the processed data to the NIC of the base station server corresponding to the server identifier.

[0138] In one example, the acceleration server is divided into multiple resource groups based on a preset virtualization technology, and each resource group represents a portion of the resources in the acceleration server; the device also includes:

[0139] A service receiving module is used to receive service data from a cloud base station; wherein, the service data from the cloud base station represents the services to be processed in the cloud base station.

[0140] The service processing module is used to determine a target resource group from the plurality of resource groups, and process the service data of the cloud base station based on the resources in the target resource group.

[0141] Figure 7 This is a structural block diagram of an electronic device provided in an embodiment of this application. Figure 7 As shown, the electronic device includes: a memory 71 and a processor 72; the memory 71 is a memory for storing executable instructions of the processor 72.

[0142] The processor 72 is configured to perform the method provided in the above embodiments.

[0143] The electronic device also includes a receiver 73 and a transmitter 74. The receiver 73 is used to receive instructions and data sent by other devices, and the transmitter 74 is used to send instructions and data to external devices.

[0144] Figure 8 This is a block diagram illustrating a terminal device according to an exemplary embodiment. The device may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0145] The device 800 may include one or more of the following components: a processing component 802, a memory 804, a power supply component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0146] Processing component 802 typically controls the overall operation of device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0147] Memory 804 is configured to store various types of data to support the operation of device 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0148] Power supply component 806 provides power to various components of device 800. Power supply component 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to device 800.

[0149] Multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0150] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0151] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0152] Sensor assembly 814 includes one or more sensors for providing status assessments of various aspects of device 800. For example, sensor assembly 814 may detect the on / off state of device 800, the relative positioning of components such as the display and keypad of device 800, changes in the position of device 800 or a component of device 800, the presence or absence of user contact with device 800, the orientation or acceleration / deceleration of device 800, and temperature changes of device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0153] Communication component 816 is configured to facilitate wired or wireless communication between device 800 and other devices. Device 800 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0154] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0155] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of the device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0156] A non-transitory computer-readable storage medium, wherein when the instructions in the storage medium are executed by the processor of a terminal device, the terminal device is able to execute the aforementioned data processing method based on a cloud base station.

[0157] This application also discloses a computer program product, including a computer program that, when executed by a processor, implements the method described in this embodiment.

[0158] Various embodiments of the systems and technologies described above in this application can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0159] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or electronic device.

[0160] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0161] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0162] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data electronic devices), or computing systems that include middleware components (e.g., application electronic devices), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0163] Computer systems can include client and electronic devices. Clients and electronic devices are generally geographically separated and typically interact via communication networks. The client-electronic device relationship is created by computer programs running on the respective computers and having a client-electronic device relationship with each other. The electronic device can be a cloud electronic device, also known as a cloud computing electronic device or cloud host, a host product within the cloud computing service system, addressing the shortcomings of traditional physical hosts and VPS services ("Virtual Private Server," or simply "VPS") in terms of management difficulty and weak business scalability. The electronic device can also be an electronic device in a distributed system or an electronic device incorporating blockchain technology. It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application is achieved, and this is not limited herein.

[0164] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0165] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A data processing method based on a cloud base station, characterized in that, The method is applied to an acceleration server, which is equipped with a physical layer accelerator. The acceleration server communicates with multiple base station servers. The cloud base station is deployed on the base station server, and the base station server is used to execute the services of the cloud base station. The method includes: Receive pending data sent by the base station server; wherein, the pending data represents data generated by executing the services of the cloud base station, and the pending data includes the server identifier of the base station server, which is used to identify the base station server; Based on the physical layer accelerator in the acceleration server, the data to be processed is processed to obtain processed data; Based on the server identifier in the data to be processed, the processed data is fed back to the base station server.

2. The method according to claim 1, characterized in that, Based on the physical layer accelerator in the acceleration server, the data to be processed is processed to obtain processed data, including: Determine the processing priority of the data to be processed; Based on the processing priority of the data to be processed, the physical layer accelerator in the acceleration server is invoked to process the data to be processed, and the processed data is obtained.

3. The method according to claim 2, characterized in that, Based on the processing priority of the data to be processed, the physical layer accelerator in the acceleration server is invoked to process the data to be processed, resulting in processed data, including: According to the processing priority of the data to be processed, the data to be processed is cached in a preset waiting queue; wherein, the preset waiting queue contains multiple unprocessed data. If the data to be processed is located at a preset sorting position in the preset waiting queue, then the physical layer accelerator in the acceleration server is invoked to process the data to be processed, and processed data is obtained.

4. The method according to claim 3, characterized in that, The data to be processed includes cell information, which represents the cell that sent the data to be processed, and the processing priority represents the priority of the cell corresponding to the cell information. Based on the processing priority of the data to be processed, the data to be processed is cached in a preset waiting queue, including: Based on the priority of the cell corresponding to the cell information, the data to be processed is cached in a preset first waiting queue.

5. The method according to claim 3, characterized in that, The data to be processed includes user information, which represents the user who sent the data to be processed, and the processing priority represents the priority of the user corresponding to the user information. Based on the priority information in the data to be processed, the data to be processed is cached in a preset waiting queue, including: Based on the priority of the user corresponding to the user information, the data to be processed is cached in a preset second waiting queue.

6. The method according to claim 3, characterized in that, The data to be processed includes business information, which represents the business corresponding to the data to be processed, and the processing priority represents the priority of the business corresponding to the business information. Based on the priority information in the data to be processed, the data to be processed is cached in a preset waiting queue, including: Based on the priority of the business corresponding to the business information, the data to be processed is cached in a preset third waiting queue.

7. The method according to any one of claims 4-6, characterized in that, Determining the processing priority of the data to be processed includes: The cell information, user information, and service information are determined from the data to be processed; The processing priority of the data to be processed is determined based on the priority of the cell corresponding to the cell information, the priority of the user corresponding to the user information, and the priority of the service corresponding to the service information.

8. The method according to claim 7, characterized in that, Based on the priority of the cell corresponding to the cell information, the priority of the user corresponding to the user information, and the priority of the service corresponding to the service information, the processing priority of the data to be processed is determined, including: Based on the priority of the cell corresponding to the cell information, the priority of the user corresponding to the user information, and the priority of the service corresponding to the service information, the target information is determined from the cell information, user information, and service information. The priority corresponding to the target information is determined as the processing priority of the data to be processed.

9. The method according to claim 8, characterized in that, Based on the processing priority of the data to be processed, the data to be processed is cached in a preset waiting queue, including: The waiting queue corresponding to the target information is determined as the target waiting queue; wherein, the target waiting queue is the first waiting queue, the second waiting queue, or the third waiting queue; The data to be processed is cached in the target waiting queue.

10. The method according to claim 3, characterized in that, The acceleration server is equipped with multiple physical layer accelerators. If the data to be processed is located at a preset sorting position in the preset waiting queue, the physical layer accelerators in the acceleration server are invoked to process the data to obtain processed data, including: If the data to be processed is located at a preset sorting position in the preset waiting queue, then the business type corresponding to the data to be processed is determined. Based on the preset association between service types and physical layer accelerators, determine the physical layer accelerator associated with the service type corresponding to the data to be processed, and designate it as the target accelerator. The target accelerator is invoked to process the data to be processed, thereby obtaining the processed data.

11. The method according to claim 1, characterized in that, The acceleration server and each of the base station servers are equipped with network cards, and the acceleration server and each base station server communicate with each other through a preset switch. Receive the data to be processed sent by the base station server, including: The network interface card (NIC) configured on the acceleration server receives data to be processed transmitted from the preset switch; wherein the data to be processed is transmitted to the switch based on the NIC of the base station server. Feeding the processed data back to the base station server includes: The processed data is transmitted to the preset switch via the network interface card (NIC) configured on the acceleration server; wherein the preset switch is used to transmit the processed data to the NIC of the base station server corresponding to the server identifier.

12. The method according to claim 1, characterized in that, The acceleration server is divided into multiple resource groups based on preset virtualization technology, and each resource group represents a portion of the resources in the acceleration server; the method further includes: Receive service data from cloud base stations; wherein, the service data from cloud base stations represents the services to be processed in the cloud base station; A target resource group is determined from the plurality of resource groups, and the service data of the cloud base station is processed based on the resources in the target resource group.

13. A data processing device based on a cloud base station, characterized in that, The device is applied to an acceleration server, which deploys a physical layer accelerator. The acceleration server communicates with multiple base station servers. The cloud base station is deployed on the base station server, and the base station server executes the services of the cloud base station. The device includes: The data receiving module is used to receive data to be processed sent by the base station server; wherein, the data to be processed represents the data generated by performing the services of the cloud base station, and the data to be processed includes the server identifier of the base station server, which is used to identify the base station server. The data processing module is used to process the data to be processed based on the physical layer accelerator in the acceleration server to obtain processed data. The data feedback module is used to feed back the processed data to the base station server based on the server identifier in the data to be processed.

14. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-12.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-12.

16. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-12.

Images