Cloud mobile phone dynamic allocation method and device, electronic equipment and storage medium

Abstract

The invention discloses a cloud mobile phone dynamic allocation method and device, electronic equipment and a storage medium. According to the application, a service server state database is constructed and the response performance level between each cloud mobile phone allocation center and a target service server is systematically evaluated; according to the technical scheme, key factors such as physical distance, network topology and link quality can be comprehensively considered, so that the cloud mobile phone allocation strategy is dynamically optimized, and therefore, the technical problems of poor response performance and unbalanced resource utilization rate caused by lack of systematic evaluation on the key factors in the prior art can be solved, and the user experience is improved. The technical effects of improving the processing efficiency of the service with the high response demand and realizing dynamic and balanced distribution of cloud mobile phone resources are achieved.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a method and apparatus for dynamic allocation of cloud mobile phones, electronic devices, and storage media. Background Technology

[0002] Cloud phones, as an important application of cloud computing and network resource scheduling technologies, are widely used in internet business scenarios that rely on high concurrency processing, such as e-commerce, ticketing, and gaming. Among related technologies, the basic scheduling system of the cloud phone center is constructed through the collaborative operation of resource load balancing algorithms, user queuing mechanisms, and static resource allocation strategies.

[0003] Existing cloud phone resource allocation methods systematically evaluate key factors such as the physical distance, network topology, and link quality between the cloud phone server and the target business server. This restricts the application of cloud phone services in high-value business scenarios and causes derivative problems such as uneven resource utilization. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, and storage medium for dynamically allocating cloud phones.

[0005] According to a first aspect of this disclosure, a method for dynamically allocating cloud phones is provided, comprising: Collect characteristic information of the target business server and build a business server status database; Based on the business server status database, evaluate the response performance level between each cloud mobile phone distribution center and the target business server; Identify the service type selected by the user; if the service type is a preset high-response-demand service, obtain the corresponding target service server identifier. Based on the response performance level corresponding to the target service server identifier, the user's cloud phone is dynamically assigned to the cloud phone allocation center with the best response performance.

[0006] Optionally, the step of collecting the characteristic information of the target business server and constructing the business server status database includes: Collect geographic location information, network path information, and cross-data center association information; The business server status database is constructed based on the server basic data provided by the operator's resource management system.

[0007] Optionally, the step of evaluating the response performance level between each cloud mobile phone distribution center and the target business server based on the business server status database includes: The response performance level between each cloud mobile phone distribution center and the target business server is evaluated based on physical distance, number of cross-data center visits, and network bandwidth utilization.

[0008] Optionally, the step of identifying the service type selected by the user, if the service type is a preset high-response-demand service, then obtaining the corresponding target service server identifier includes: The front-end interaction module displays business options to users, and automatically associates the corresponding target business server identifier after the user selects a business.

[0009] Optionally, dynamically allocating a user's cloud phone to the cloud phone allocation center with the best response performance includes: Prioritize matching the cloud phone allocation center with the highest response performance level; when multiple allocation centers with the same highest level exist, the final allocation object is determined based on link transmission efficiency.

[0010] Optionally, the method further includes: The feature information is continuously updated using a timed detection method to ensure the validity of the data in the business server status database.

[0011] According to a second aspect of this disclosure, a cloud phone dynamic allocation device is provided, comprising: The acquisition unit is used to collect characteristic information of the target business server and build a business server status database. The evaluation unit is used to evaluate the response performance level between each cloud mobile phone distribution center and the target business server based on the business server status database. The identification unit is used to identify the service type selected by the user. If the service type is a preset high-response demand service, the corresponding target service server identifier is obtained. The allocation unit is used to dynamically allocate the user's cloud phone to the cloud phone allocation center with the best response performance according to the response performance level corresponding to the target business server identifier.

[0012] Optionally, the acquisition unit is further configured to: Collect geographic location information, network path information, and cross-data center association information; The business server status database is constructed based on the server basic data provided by the operator's resource management system.

[0013] Optionally, the evaluation unit is also used for: The response performance level between each cloud mobile phone distribution center and the target business server is evaluated based on physical distance, number of cross-data center visits, and network bandwidth utilization.

[0014] Optionally, the identification unit is further configured to: The front-end interaction module displays business options to users, and automatically associates the corresponding target business server identifier after the user selects a business.

[0015] Optionally, the allocation unit is further configured to: Prioritize matching the cloud phone allocation center with the highest response performance level; when multiple allocation centers with the same highest level exist, the final allocation object is determined based on link transmission efficiency.

[0016] Optionally, the device further includes: The update unit is used to continuously update feature information using a timed detection method to ensure the validity of the data in the business server status database.

[0017] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0018] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0019] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0020] The cloud phone dynamic allocation method, apparatus, electronic device, and storage medium disclosed herein, through the construction of a business server status database and the systematic evaluation of the response performance levels between each cloud phone allocation center and the target business server, can comprehensively consider key factors such as physical distance, network topology, and link quality, thereby dynamically optimizing the cloud phone allocation strategy. Therefore, it can solve the technical problems of poor response performance and uneven resource utilization caused by the lack of systematic evaluation of key factors in the prior art, and achieve the technical effect of improving the processing efficiency of high-response-demand services and realizing the dynamic and balanced allocation of cloud phone resources.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0022] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1This is a flowchart illustrating a cloud phone dynamic allocation method provided in an embodiment of the present disclosure. Figure 2 This is a schematic diagram of the structure of a cloud phone dynamic allocation device provided in an embodiment of the present disclosure; Figure 3 This is a schematic diagram of another cloud phone dynamic allocation device provided in an embodiment of the present disclosure; Figure 4 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0023] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0024] The following description, with reference to the accompanying drawings, outlines a cloud phone dynamic allocation method, apparatus, electronic device, and storage medium according to embodiments of the present disclosure.

[0025] Figure 1 This is a flowchart illustrating a cloud phone dynamic allocation method provided in an embodiment of the present disclosure.

[0026] like Figure 1 As shown, the method includes the following steps: Step 101: Collect the characteristic information of the target business server and build a business server status database; The process of collecting characteristic information of target business servers and constructing a business server status database mainly involves automatically collecting or obtaining key attribute data of the target business servers from external systems. This characteristic information includes, but is not limited to, the geographical region where the business server is located, the specific data center location, rack deployment, network distance, backbone network connection status, and whether it spans different data centers. This comprehensively reflects the network environment and physical layout of the business server. The data collection process can be implemented through periodic dial-up testing or access to the operator's OSS resource management system to ensure the real-time nature and accuracy of the data.

[0027] When constructing the business server status database, the aforementioned characteristic information is stored and managed in a structured manner, forming a queryable and updatable data set to provide foundational support for subsequent cloud phone resource allocation. This database aims to optimize the response efficiency between cloud phones and business servers, guiding cloud phone scheduling decisions by analyzing server characteristics, thereby improving user access speed in high-concurrency business scenarios. The entire process focuses on efficient data collection and database construction, avoiding the introduction of unnecessary details to ensure the method's universality and implementability.

[0028] Step 102: Based on the business server status database, evaluate the response performance level between each cloud mobile phone distribution center and the target business server; The system evaluates the response performance level between each cloud phone distribution center and the target business server based on a business server status database. This evaluation process analyzes feature information in the database, comprehensively considering key parameters such as the physical distance between the cloud phone distribution center and the target business server, network response time, backbone network connection status, bandwidth capacity, and whether they cross data centers, thereby quantifying the communication efficiency between them. During the evaluation, the system performs weighted calculations or comparisons of the above parameters according to preset rules or algorithms to generate corresponding response performance level indicators. These levels are typically expressed numerically or in categorical form; a higher level indicates a faster response speed and better network quality between the cloud phone distribution center and the target business server.

[0029] The aim is to dynamically identify the optimal deployment location for cloud phones, ensuring that centers with high response performance are prioritized during resource allocation, thereby improving the overall efficiency of users accessing business servers. The entire process relies on real-time or periodic database updates to maintain the accuracy of the evaluation results and avoids introducing specific implementation details, only summarizing the evaluation mechanism at the methodological level to provide a basis for subsequent cloud phone scheduling decisions.

[0030] Step 103: Identify the service type selected by the user. If the service type is a preset high-response demand service, obtain the corresponding target service server identifier. The system provides service type selection options through a user interface, receiving user selections and classifying them. Preset high-response-demand services typically refer to application scenarios sensitive to network latency and requiring rapid server response, such as online flash sales or instant ticketing. When the system identifies that the user's selected service type matches the preset high-response-demand category, it automatically triggers an association mechanism to retrieve and extract the target service server identifier corresponding to that specific service type from a predefined service mapping relationship. This identifier uniquely identifies the backend server providing this service, providing target guidance for subsequent cloud phone resource allocation.

[0031] The entire process achieves business-oriented server location, ensuring that subsequent scheduling processes accurately align with users' actual business needs and laying the foundation for optimizing cloud phone deployment locations. This method focuses on identifying business types and obtaining corresponding server identifiers, without delving into specific interactive interface implementation details, thus maintaining the versatility and adaptability of the technical solution.

[0032] Step 104: Based on the response performance level corresponding to the target service server identifier, dynamically allocate the user's cloud phone to the cloud phone allocation center with the best response performance.

[0033] The allocation process is based on pre-assessed response performance level data. The system automatically identifies and selects the highest-level center as the deployment location by comparing the communication efficiency indicators between each cloud phone allocation center and the target business server. This dynamic allocation mechanism ensures that cloud phone instances can adapt to changes in network conditions in real time, prioritizing deployment in data center environments with close physical proximity, low network latency, and sufficient bandwidth resources, thereby minimizing user response time to the business server. The response performance level reflects the overall connection quality between the cloud phone allocation center and the target business server, including but not limited to factors such as network routing optimization, data transmission speed, and link stability.

[0034] The allocation decision requires no manual user intervention. The system quickly retrieves the associated level information based on the target business server identifier and executes resource scheduling logic to map cloud phone resources to the optimal center. This method improves the overall performance of cloud phone services through automated scheduling, making it particularly suitable for business scenarios with high real-time requirements and ensuring users receive a smooth and efficient access experience. The entire process focuses on dynamic resource allocation based on level data, avoiding the introduction of specific implementation details and ensuring the method's universality and scalability.

[0035] In some embodiments, collecting the characteristic information of the target business server and constructing the business server status database includes: Collect geographic location information, network path information, and cross-data center association information; The business server status database is constructed based on the server basic data provided by the operator's resource management system.

[0036] The process of collecting characteristic information of target service servers and constructing a service server status database specifically includes collecting geographical location information, network path information, and cross-data center association information, and building this database based on server basic data provided by the operator's resource management system. Geographical location information involves the physical region where the service server is located, the specific location of the data center, and rack deployment details, used to identify the spatial distribution of servers. Network path information includes network connection routes between servers, backbone network participation status, and the topology of data transmission paths, reflecting the efficiency and stability of network communication. Cross-data center association information describes whether the service server is deployed across multiple data centers and the interconnection relationships between them, used to assess communication latency in a multi-data center environment.

[0037] This feature information is automatically collected by the system or obtained from the operator's resource management system. The operator's resource management system typically provides basic server configuration data, network architecture information, and real-time status indicators. After integrating this data, the system constructs a structured business server status database. This database is stored in a queryable and updatable format, ensuring the accuracy and timeliness of the information and providing a reliable data foundation for subsequent response performance evaluation. The entire process emphasizes efficient data integration and standardized storage, avoiding the introduction of specific implementation details. It only describes the feature information collection and database construction mechanisms at the methodological level, thereby supporting the optimized scheduling of cloud phone resources.

[0038] In some embodiments, evaluating the response performance level between each cloud mobile phone distribution center and the target business server based on the business server status database includes: The response performance level between each cloud mobile phone distribution center and the target business server is evaluated based on physical distance, number of cross-data center visits, and network bandwidth utilization.

[0039] The process of evaluating the response performance level between each cloud phone distribution center and the target business server based on the business server status database includes a comprehensive assessment based on physical distance, number of hops across data centers, and network bandwidth utilization. Physical distance refers to the geographical distance between the cloud phone distribution center and the target business server, usually measured as a straight line distance or network routing distance. A shorter physical distance helps reduce signal transmission latency, thereby improving response speed. The number of hops across data centers indicates the number of data center hops a data packet needs to pass through to travel from the cloud phone distribution center to the target business server. Each hop across a data center may introduce additional network processing overhead and latency; therefore, fewer hops across data centers mean a more direct communication path and generally better response performance.

[0040] Network bandwidth utilization reflects the available network bandwidth capacity and occupancy rate between the cloud phone distribution center and the target business server. Higher bandwidth capacity and lower occupancy rate can support faster data transmission rates and reduce congestion risks. During evaluation, the system obtains real-time or historical data of the above parameters from the business server status database and performs quantitative analysis using predefined algorithms or rules. For example, physical distance, cross-data center frequency, and network bandwidth utilization are mapped to standardized indicators, and then a comprehensive response performance level is generated through weighted summation or priority comparison. This level is expressed in numerical or categorical form to identify the communication efficiency of different cloud phone distribution centers relative to the target business server.

[0041] The entire process relies on continuous database updates to ensure assessment accuracy and dynamically adjusts the rating results through automated mechanisms, thereby providing a reliable basis for cloud phone resource allocation and optimizing the user experience. This method focuses on the integrated assessment of key parameters, avoiding the introduction of specific implementation details and ensuring the universality and scalability of the assessment mechanism.

[0042] In some embodiments, identifying the service type selected by the user, and if the service type is a preset high-response-demand service, then obtaining the corresponding target service server identifier includes: The front-end interaction module displays business options to users, and automatically associates the corresponding target business server identifier after the user selects a business.

[0043] The process of identifying the user's selected service type and obtaining the corresponding target service server identifier when the service type is a preset high-response-demand service specifically includes displaying service options to the user through the front-end interaction module, and automatically associating the corresponding target service server identifier after the user selects a service. The front-end interaction module refers to the interface component for user-system information interaction, usually presented in the form of a graphical user interface or web page, used to dynamically display a list of selectable service types. Service options include various Internet application scenarios such as online transactions or instant services, among which preset high-response-demand services are specially marked or categorized to prompt the user to select.

[0044] When a user selects a service type through the front-end interaction module, the system automatically triggers an association mechanism. This mechanism, based on a predefined mapping relationship between service types and target service server identifiers, instantly matches the user's selected service type with a unique server identifier. The target service server identifier uniquely identifies the backend server instance providing that service. The automatic association process requires no manual intervention and is completed in real-time through queries to the internal database or configuration table, ensuring fast and accurate retrieval of the server identifier.

[0045] The entire process aims to efficiently identify user business intent and locate the corresponding server, providing accurate input for subsequent cloud phone resource scheduling, thereby optimizing access performance under high-response demand. This method focuses on the integrated implementation of front-end interaction and automatic association, avoiding the introduction of specific interface design details and maintaining the universality and operability of the technical solution.

[0046] In some embodiments, dynamically allocating a user's cloud phone to the cloud phone allocation center with the best response performance includes: Prioritize matching the cloud phone allocation center with the highest response performance level; when multiple allocation centers with the same highest level exist, the final allocation object is determined based on link transmission efficiency.

[0047] The process of dynamically assigning a user's cloud phone to the cloud phone allocation center with the best response performance specifically includes prioritizing the matching of the cloud phone allocation center with the highest response performance level, and determining the final allocation object based on link transmission efficiency when multiple allocation centers with the same highest level exist.

[0048] Prioritizing the matching of cloud phone allocation centers with the highest response performance level means that when scheduling resources, the system first retrieves the response performance level data of all available cloud phone allocation centers and selects the center with the highest level value as the preferred deployment location. The response performance level reflects the overall communication quality between the cloud phone allocation center and the target business server, including parameters such as network latency, bandwidth availability, and connection stability, ensuring that the user's cloud phone is allocated to the center with the optimal network environment to maximize access speed.

[0049] When multiple cloud phone allocation centers have the same highest response performance level, the system further filters based on link transmission efficiency. Link transmission efficiency refers to the actual efficiency of data transmission between the cloud phone allocation center and the target business server, involving factors such as data transmission rate, throughput, packet loss rate, and latency fluctuations. The system compares the link performance of these centers through real-time monitoring or historical data analysis, selecting the center with the highest link transmission efficiency as the final allocation target. This optimizes network resource utilization and reduces potential congestion risks even when the performance levels are the same. The entire dynamic allocation mechanism relies on automated decision-making logic, requiring no manual intervention. Through multi-level filtering, it ensures that cloud phones are always deployed in the environment with the fastest response and most stable transmission, improving user experience efficiency in high-demand services. This method focuses on a priority-based allocation strategy with link efficiency as an auxiliary factor, avoiding the introduction of specific algorithmic details and maintaining the adaptability and robustness of the solution.

[0050] In some embodiments, the method further includes: The feature information is continuously updated using a timed detection method to ensure the validity of the data in the business server status database.

[0051] A timed detection method is employed to continuously update characteristic information, ensuring the validity of the business server status database. This timed detection involves the system automatically performing data collection and verification at preset time intervals. It obtains the latest characteristic information of the business servers by periodically testing or querying external data sources, such as the operator's resource management system. This characteristic information includes key parameters such as geographical location, network path status, cross-data center association, and bandwidth utilization. This continuous update mechanism ensures that the records in the business server status database reflect real-time changes in the network environment and server configuration, avoiding scheduling decision biases caused by outdated data.

[0052] Data validity refers to the accuracy, completeness, and timeliness of database information. The system periodically detects and promptly captures dynamic factors such as network topology changes, server load fluctuations, or data center maintenance events, integrating the updated feature information into the database to maintain its reference value. The entire update process requires no manual intervention, employing automated scripts or background services. The detection frequency can be adjusted according to business needs, such as by minute, hour, or day, ensuring that the data relied upon for cloud phone resource allocation remains reliable. This method enhances the system's adaptability through periodic data refresh, providing a solid data foundation for response performance evaluation and cloud phone scheduling, ultimately improving the speed and stability of user access to business servers.

[0053] Corresponding to the aforementioned dynamic allocation method for cloud phones, this invention also proposes a dynamic allocation device for cloud phones. Since the device embodiments of this invention correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to the method embodiments described above, and will not be repeated here.

[0054] Figure 2 This is a schematic diagram of the structure of a cloud phone dynamic allocation device provided in an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: The acquisition unit 21 is used to acquire the characteristic information of the target business server and build a business server status database. Evaluation unit 22 is used to evaluate the response performance level between each cloud mobile phone distribution center and the target business server based on the business server status database. The identification unit 23 is used to identify the service type selected by the user. If the service type is a preset high-response demand service, the corresponding target service server identifier is obtained. The allocation unit 24 is used to dynamically allocate the user's cloud phone to the cloud phone allocation center with the best response performance according to the response performance level corresponding to the target business server identifier.

[0055] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the acquisition unit 21 is also used for: Collect geographic location information, network path information, and cross-data center association information; The business server status database is constructed based on the server basic data provided by the operator's resource management system.

[0056] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the evaluation unit 22 is also used for: The response performance level between each cloud mobile phone distribution center and the target business server is evaluated based on physical distance, number of cross-data center visits, and network bandwidth utilization.

[0057] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the identification unit 23 is further used for: The front-end interaction module displays business options to users, and automatically associates the corresponding target business server identifier after the user selects a business.

[0058] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the allocation unit 24 is further configured to: Prioritize matching the cloud phone allocation center with the highest response performance level; when multiple allocation centers with the same highest level exist, the final allocation object is determined based on link transmission efficiency.

[0059] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the device further includes: The update unit 25 is used to continuously update feature information using a timed detection method to ensure the data validity of the business server status database.

[0060] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0061] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0062] Figure 4A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0063] like Figure 4 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0064] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0065] The computing unit 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the cloud phone dynamic allocation method. For example, in some embodiments, the cloud phone dynamic allocation method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned cloud phone dynamic allocation method by any other suitable means (e.g., by means of firmware).

[0066] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations 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.

[0067] The program code used to implement the methods of this disclosure 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 apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be 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 server.

[0068] In the context of this disclosure, 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. A machine-readable medium 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, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0069] 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).

[0070] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0071] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0072] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0073] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0074] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for dynamically allocating cloud phones, characterized in that, include: Collect characteristic information of the target business server and build a business server status database; Based on the business server status database, evaluate the response performance level between each cloud mobile phone distribution center and the target business server; Identify the service type selected by the user; if the service type is a preset high-response-demand service, obtain the corresponding target service server identifier. Based on the response performance level corresponding to the target service server identifier, the user's cloud phone is dynamically assigned to the cloud phone allocation center with the best response performance.

2. The method according to claim 1, characterized in that, The process of collecting feature information of the target business server and constructing a business server status database includes: Collect geographic location information, network path information, and cross-data center association information; The business server status database is constructed based on the server basic data provided by the operator's resource management system.

3. The method according to claim 1, characterized in that, The evaluation of the response performance level between each cloud mobile phone distribution center and the target business server based on the business server status database includes: The response performance level between each cloud mobile phone distribution center and the target business server is evaluated based on physical distance, number of cross-data center visits, and network bandwidth utilization.

4. The method according to claim 1, characterized in that, The process of identifying the service type selected by the user, and if the service type is a preset high-response-demand service, then obtaining the corresponding target service server identifier includes: The front-end interactive module displays business options to users, and automatically associates the corresponding target business server identifier after the user selects a business.

5. The method according to claim 1, characterized in that, The process of dynamically allocating a user's cloud phone to a cloud phone allocation center with the best response performance includes: Prioritize matching the cloud phone allocation center with the highest response performance level; when multiple allocation centers with the same highest level exist, the final allocation object is determined based on link transmission efficiency.

6. The method according to claim 1, characterized in that, The method further includes: The feature information is continuously updated using a timed detection method to ensure the validity of the data in the business server status database.

7. A cloud phone dynamic allocation device, characterized in that, include: The acquisition unit is used to collect characteristic information of the target business server and build a business server status database. The evaluation unit is used to evaluate the response performance level between each cloud mobile phone distribution center and the target business server based on the business server status database. The identification unit is used to identify the service type selected by the user. If the service type is a preset high-response demand service, the corresponding target service server identifier is obtained. The allocation unit is used to dynamically allocate the user's cloud phone to the cloud phone allocation center with the best response performance according to the response performance level corresponding to the target business server identifier.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-6.

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