Service function chain calling method and system based on equipment-free edge computing environment

Abstract

The invention discloses a service function chain calling method and system based on a device-free edge computing environment. The method comprises the following steps: deploying a service function chain corresponding to a user; the service function chain is sent to a plurality of corresponding working nodes, and the working nodes comprise devices bearing virtual functions; obtaining a request service of the user, and obtaining input data of the user according to the request service; and controlling the plurality of working nodes to process the input data to obtain a processing result. According to the application, the service function chain is deployed for the user, and the lightweight virtualization technology is used to manage the resources, so that the service delay is reduced, and the resource utilization rate of the edge device is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a service function chain calling method and system based on a device-free edge computing environment. Background Art

[0002] In the device-free edge computing environment, various devices with different functions are introduced to meet the growing and diverse needs of end users. However, there are many challenges in deploying and managing these heterogeneous devices in the edge computing environment. These edge devices may come from different vendors and have different characteristics and attributes. When making connections and task scheduling, developers must consider the capabilities and location of each device.

[0003] In device-free edge computing, lightweight virtualization technologies such as containers are used to deploy applications and services along with required configuration files. These applications and services can be deployed with a unified experience on different types of devices. Device-free edge computing enables function developers to utilize edge device resources without having to consider the capabilities of specific devices, the connections between devices, and the deployment location. This approach provides developers and users with a transparent resource allocation and deployment process, thereby increasing function elasticity, efficiency, and higher quality services.

[0004] In order to further utilize various heterogeneous devices in device-free edge computing, a service function chain (SFC) is introduced to divide tasks onto different devices. SFC links related functions in sequence to provide services and provides a framework for coordinating different devices in edge computing to manage various service functions. SFC manages multiple virtual functions located on different devices. First, it can increase data traffic throughput by deploying specific functions on the most suitable devices. This approach can make full use of the device's ability to process data and reduce processing time. Second, it can increase the number of users served simultaneously. Because SFC can be organized as a pipeline process, multiple users can be served at the same time.

[0005] However, in the prior art, the dynamic migration of embedded services in 5G core networks and software-defined networks has been studied, and algorithms have been designed to meet the end-to-end latency requirements of services in 5G networks. The solutions proposed in the prior art may require more computing and communication resources to achieve dynamic flow migration, which may increase the complexity and overhead of the network. In addition, the method has not been tested in real scenarios, and the feasibility and efficiency of the method in actual systems and real edge applications cannot be guaranteed.

[0006] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0007] The main purpose of this application is to provide a service function chain calling method and system based on a device-free edge computing environment, aiming to solve the problem in the prior art that device-free edge computing requires more computing and communication resources to achieve dynamic flow migration, and the network is relatively complex, resulting in high service delays.

[0008] A first aspect of an embodiment of the present application provides a service function chain calling method based on a device-free edge computing environment, and the service function chain calling method based on a device-free edge computing environment includes the following steps: deploying a service function chain corresponding to a user; sending the service function chain to a corresponding plurality of working nodes, wherein the working nodes include devices that carry virtual functions; obtaining the user's request service, and obtaining the user's input data based on the request service; and controlling the plurality of working nodes to process the input data to obtain processing results.

[0009] Optionally, in one embodiment of the present application, the service function chain corresponding to the deployed user specifically includes: obtaining user needs and network information for the user; evaluating multiple virtual functions based on the user needs and the network information to obtain evaluation results of each of the virtual functions; and determining the service function chain corresponding to the user based on the evaluation results of each of the virtual functions.

[0010] Optionally, in one embodiment of the present application, the multiple virtual functions are evaluated according to the user needs and the network information to obtain evaluation results of each of the virtual functions, specifically including: obtaining the performance of each of the multiple virtual functions on each device; according to the user needs and the network information, the performance of each of the virtual functions is evaluated to obtain evaluation results of each of the virtual functions.

[0011] Optionally, in one embodiment of the present application, determining the service function chain corresponding to the user based on the evaluation results of each of the virtual functions specifically includes: constructing a quasi-convex binary optimization model based on the evaluation results of each of the virtual functions; solving the quasi-convex binary optimization model using a convex optimization method to obtain the deployment probability of each of the virtual functions on each device; for each of the virtual functions, determining the target device with the highest deployment probability from a plurality of devices; and respectively deploying the plurality of virtual functions on the corresponding target devices to obtain the service function chain.

[0012] Optionally, in one embodiment of the present application, the quasi-convex binary optimization model is expressed as:

[0013]

[0014] Among them, u represents the user, d and e represent the server, f represents the virtual function, and xfdu Indicates whether user u requests virtual function f to run on server d. If x fdu =1 means yes, if x fdu =0 means no, c fdu Indicates processing delay, g fedu represents the transmission delay, s d represents the capacity limit of device d, D represents the set of devices, F represents the set of virtual functions, and U represents the set of users; x (f-1)eu Indicates that virtual function f-1 is deployed to device e.

[0015] Optionally, in an embodiment of the present application, obtaining the input data of the user according to the request service is specifically: generating corresponding input data according to the request service; or performing data query according to the request service to obtain the input data entered by the user.

[0016] Optionally, in one embodiment of the present application, the multiple working nodes include a first node, a second node and a third node; controlling the multiple working nodes to process the input data to obtain a processing result specifically includes: controlling the first node to preprocess the input data to obtain first data; controlling the second node to infer or transcode the first data to obtain second data; and controlling the third node to perform final processing on the second data to obtain a processing result.

[0017] The second aspect of the embodiment of the present application further provides a service function chain calling system based on a device-free edge computing environment, wherein the service function chain calling system based on a device-free edge computing environment includes:

[0018] The service chain deployment module is used to deploy the service function chain corresponding to the user;

[0019] A node notification module, used to send the service function chain to a corresponding plurality of working nodes, wherein the working nodes include devices that carry virtual functions;

[0020] A data acquisition module, used to acquire the requested service of the user and obtain the input data of the user according to the requested service;

[0021] The data processing module is used to control the plurality of working nodes to process the input data to obtain processing results.

[0022] The third aspect of an embodiment of the present application also provides a terminal, wherein the terminal includes: a memory, a processor, and a service function chain calling program based on a device-free edge computing environment stored in the memory and executable on the processor, wherein the service function chain calling program based on the device-free edge computing environment implements the steps of the service function chain calling method based on the device-free edge computing environment as described above when executed by the processor.

[0023] The fourth aspect of an embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a service function chain calling program based on a device-free edge computing environment, and when the service function chain calling program based on the device-free edge computing environment is executed by a processor, the steps of the service function chain calling method based on the device-free edge computing environment as described above are implemented.

[0024] Beneficial effects: The present application provides a service function chain calling method and system based on a device-free edge computing environment. The present application deploys service function chains for users and uses lightweight virtualization technology to manage resources to reduce service delays and improve resource utilization of edge devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 It is the main system design diagram adopted in the preferred embodiment of the service function chain calling method based on the device-free edge computing environment of the present application;

[0027] Figure 2 It is a flowchart of a preferred embodiment of the service function chain calling method based on the device-free edge computing environment of the present application;

[0028] Figure 3 It is a schematic diagram of the data packet sending and receiving flow in the service process in a preferred embodiment of the service function chain calling method based on the device-free edge computing environment of the present application;

[0029] Figure 4 It is a structural diagram of a preferred embodiment of the service function chain calling system based on a device-free edge computing environment of the present application;

[0030] Figure 5 This is a structural diagram of a preferred embodiment of the terminal of this application.

[0031] Description of reference numerals:

[0032] 10. Service function chain calling system based on device-free edge computing environment; 100. Service chain deployment module; 200. Node notification module; 300. Data acquisition module; 400. Data processing module.

[0033] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and effect of the present application clearer and more specific, the technical scheme in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. The described embodiments are only possible technical implementations of the present application, not all possible implementations. Based on the embodiments in the present application, those skilled in the art can completely combine the embodiments of the present application to obtain other embodiments without creative work, and these embodiments are also within the scope of protection of the present application.

[0035] In the related technologies, resource utilization is low: because the heterogeneity of devices is not fully considered, existing solutions may cause some devices to be overloaded while other devices are idle, thereby reducing overall resource utilization. High latency: There is no optimized service function chain placement strategy, which will lead to too long data transmission paths and increase service latency. High complexity and overhead: Some solutions require more computing and communication resources to achieve dynamic flow migration, which increases the complexity and overhead of the network. Lack of real-world scenario verification: Many methods have not been tested in actual systems and real edge applications, and their feasibility and efficiency cannot be guaranteed.

[0036] First, the nouns involved in the embodiments of the present application are introduced:

[0037] Raspberry Pi is a microcomputer motherboard developed by the Raspberry Pi Foundation. It is widely used in education, electronic prototyping and small-scale production projects due to its high cost performance and flexibility.

[0038] The edge computing platform (Jetson Xavier NX) is a high-performance edge computing platform launched by NVIDIA, designed for applications that require real-time processing and artificial intelligence reasoning.

[0039] SFC, or Service Function Chain, refers to a set of virtual functions that provide services by sequentially linking related functions in a device-free edge computing environment.

[0040] SFCs is the plural form of service function chains, which means multiple service function chains.

[0041] Secondly, the following will be combined with the attached Figure 1 , the system architecture of the embodiments of the present application is introduced.

[0042] Figure 1 It is the main system design of the technical solution of the present invention. The system aims to provide users with a platform for running and organizing different functions, thereby providing services to users. The system manages devices and functions without the participation of developers and users. Different devices have different computing and communication capabilities due to their heterogeneity, and therefore may be suitable for different functions and tasks in edge scenarios. The system is deployed as follows Figure 1 As shown. There are multiple users requesting services in the system, and each service is composed of different virtual functions deployed on different devices in an orderly manner. For example, the SFC serving user 1 calls multiple virtual functions in sequence, which are deployed on different devices. Virtual functions serving different users or different virtual functions serving the same user are independent of each other. For different devices, the capabilities and running times of virtual functions are different due to the differences in hardware between devices. For the same device, the capabilities and running times of different virtual functions are also different.

[0043] The following describes the service function chain calling method and system based on the device-free edge computing environment of the embodiment of the present application with reference to the accompanying drawings. In view of the problem that the device-free edge computing in the above-mentioned related technology requires more computing and communication resources to realize dynamic flow migration, and the network is relatively complex, resulting in high service delays, the present application provides a service function chain calling method based on the device-free edge computing environment. In this method, by deploying service function chains for users, lightweight virtualization technology is used to manage resources to reduce service delays and improve the resource utilization of edge devices. As a result, the technical problem that the device-free edge computing in the related technology requires more computing and communication resources to realize dynamic flow migration, and the network is relatively complex, resulting in high service delays, is solved.

[0044] This application proposes a service function chain placement strategy that takes into account device heterogeneity in device-free edge computing to reduce service latency and improve resource utilization of edge devices. The method proposes a system that uses a service function chain, uses lightweight virtualization technology to manage resources, and provides low-latency services for user requests. The system takes into account the heterogeneity of devices and supports various complex tasks. For this purpose, an optimal service function chain placement problem is proposed and formulated as a quasi-convex problem. Finally, in order to verify the effect of the invention, three edge applications with different functions are implemented on six Raspberry Pis and one Jetson XavierNX, which can be served by function chains. Therefore, this paper aims to solve the challenges brought by device heterogeneity and provide an effective solution to support complex tasks and low-latency services, so as to prove the practicality and robustness of the invention.

[0045] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0046] The service function chain calling method based on the device-free edge computing environment described in the preferred embodiment of the present application is as follows: Figure 1 As shown, the service function chain calling method based on the device-free edge computing environment includes the following steps:

[0047] In step S101, the service function chain corresponding to the user is deployed.

[0048] In one possible implementation, user needs and network information are obtained for the user; multiple virtual functions are evaluated based on the user needs and the network information to obtain evaluation results of each of the virtual functions; and a service function chain corresponding to the user is determined based on the evaluation results of each of the virtual functions.

[0049] It should be noted that the present application can support device heterogeneity in a device-free edge computing environment. The service function chain (SFC) deploys tasks separately on different devices. The SFC system links related functions in sequence to provide services and provides a framework for coordinating different devices in edge computing to manage various service functions. SFC manages different virtual functions between different devices, thereby improving service quality and resource utilization. First, it can increase data traffic throughput by splitting and placing specific functions on the most suitable devices. Such placement can reduce processing time and increase data processing capabilities within a time interval. Secondly, it can increase the number of services provided to multiple users at the same time. Since SFC can be organized into a pipeline process, different functions can be provided to multiple users through different stages in the same time period, resulting in a larger total number of users.

[0050] In a possible implementation, the performance of each of the plurality of virtual functions on each device is obtained; and the performance of each of the virtual functions is evaluated according to the user demand and the network information to obtain an evaluation result of each of the virtual functions.

[0051] In a possible implementation, a quasi-convex binary optimization model is constructed according to the evaluation results of each of the virtual functions; a convex optimization method is used to solve the quasi-convex binary optimization model to obtain the deployment probability of each virtual function on each device; for each virtual function, a target device with the highest deployment probability is determined from a plurality of devices; and a plurality of virtual functions are respectively deployed on the corresponding target devices to obtain the service function chain.

[0052] The specific logical steps for calculating the best service function link flow are as follows: Collect network information: The manager collects current network information from the working nodes, including the connection status, bandwidth, latency, etc. between devices. This information can help the manager understand the current network status and resource allocation. Analyze user needs: The manager also needs to understand the user's needs, including the required service type, data volume, processing time requirements, etc. This can be obtained through user requests or historical data. Determine available virtual functions: The manager needs to know which virtual functions are available, as well as their capabilities and running time on each device. This can be obtained through communication with the working nodes. Evaluate virtual function performance: Based on the collected network information and user needs, the manager needs to evaluate the performance of each virtual function on different devices. This may include factors such as computing processing speed, resource consumption, latency, etc. Construct candidate link flows: Based on the evaluation results of the virtual functions, the manager can construct multiple candidate service function link flows. Each link flow contains a series of virtual functions and their order to meet user needs. Optimize link flows: The manager can use some optimization algorithms to select the best service function link flow. These algorithms can evaluate and compare different link flows based on specific objective functions (such as minimizing latency, maximizing throughput, etc.). Return the best link flow: Once the best service function link flow is found, the manager returns it to the user who initiated the request. At the same time, the manager also notifies the relevant working nodes so that they can operate according to the instructions of the link flow.

[0053] It is understandable that the process of determining the best service function link flow is usually determined before the user requests the service. This is because the manager needs to know the current state of the network and the resource allocation in advance so that the deployment and operation order of the virtual functions can be optimized based on this information. When the user requests a service, the manager will guide the transmission and processing of the data based on the calculated service function link flow. This can avoid complex calculations and decisions when processing user requests in real time, thereby improving the response speed and efficiency of the system. Of course, in actual applications, since the network conditions may change, the manager may need to update the service function link flow regularly to adapt to the new network environment. However, this update is usually performed in the background and will not directly affect the user requests being processed.

[0054] Specifically, Initialization: Collect all necessary input data, including the processing power of each server (i.e., device), the resource requirements of each virtual function, and the topology of the network. Construct an optimization model: Based on the above information, construct a quasi-convex binary optimization model, where the objective function is to minimize the total service delay, and the constraints ensure that all virtual functions can be reasonably deployed on the server. Solve the optimization problem: Use a convex optimization algorithm to solve the model and obtain the deployment probability of each virtual function on each server. Deployment decision: Based on the solution results, deploy the three virtual functions of each user on the server with the highest probability to form service function chains (SFCs). Execution and monitoring: Implement deployment strategies, continuously monitor system performance and service delay, and adjust strategies when necessary to cope with changes in network or server status.

[0055] This application can effectively manage and optimize the service function chain in the device-free edge environment to ensure high efficiency and low latency of the service.

[0056] Furthermore, in order to solve the service function chain placement problem, it is formulated as a quasi-convex binary problem, the goal of which is to minimize the total service delay.

[0057]

[0058] Among them, x fdu is a binary variable indicating whether virtual function f is requested by user u to run on server d. If x fdu =1, it means yes; if x fdu =0, it means no. (f-1)eu Indicates whether virtual function f-1 is deployed on device e and data is transferred to the next server d for further processing, which involves the transmission delay from server e to server d. fdu represents the processing delay of virtual function f for user u on server d. The processing delay refers to the time required for data to be processed on the server.fedu represents the transmission delay between the transfer functions f-1 and f from server e to server d. The transmission delay refers to the time required for data to move from one server to another in the network. In other words, the service delay mainly considers two parts: the processing delay of virtual function f for user u on server d and the transmission delay between the transfer functions f-1 and f from server e to d, which are denoted as c fdu and g fedu . st This is the abbreviation of "subject to" and is used to introduce constraints.

[0059] The objective function consists of three parts. The first part is the processing delay. Since the deterministic variable represents the processing delay time when a virtual function f is running on server s, the second and third parts are the transmission delay, in this case g fedu is the transmission delay from function f running on d to e and d, then the previous function is placed on server e, denoted as f-1. Therefore, in this case x (f-1)eu will be 1. Before the first virtual function, there is no transmission delay, so the sum must start from f = 2. The third part is the same as the second part, the only difference is the transmission target. x fdu represents the function f currently running on server d and its corresponding transfer. Since the last step has no successor, the summation is limited to |F|-1.

[0060] Constraints Indicates that any function must be deployed on one and only one server. Constraint It means that all functions of all users must be deployed on a server whose capacity must be less than the capacity of the server when the server's resources are limited. The constant x∈{0,1} is the variable domain, which indicates whether user u calls function f provided by server d.

[0061] We use a convex optimization algorithm to solve the problem and obtain the optimal probability of each function for each user being deployed on each server. Then, we deploy the three functions of each user on the server with the highest probability respectively and organize them into per-user SFCs in sequence.

[0062] In step S102, the service function chain is sent to a corresponding plurality of working nodes, wherein the working nodes include devices that carry virtual functions.

[0063] Specifically, the manager sends the calculated optimal service function link flow to all relevant working nodes, including servers that host virtual functions and user devices that execute tasks.

[0064] When a user initiates a service request, the request is routed to the first worker node, which preprocesses the data according to the instructions of the link flow. After the preprocessing is completed, the data is passed to the next worker node, which is responsible for further processing, such as machine learning inference or video clip transcoding. After the second worker node completes the processing, the data is passed to the third worker node, which performs the final processing, such as cropping or indexing the video. After the third worker node completes the processing, the results are automatically sent back to the user. The user can send a request to the corresponding node to get the results. After each worker node completes its task, they send the processing results back to the manager so that the network information can be updated. When a new user request arrives, the whole process starts again, that is, returning to the first step. Throughout the process, the manager recalculates and optimizes the service function link flow according to the changes in network conditions and the continuous emergence of new user needs. This ensures that the virtual functions in the service chain can be deployed and operated efficiently to meet the service needs of users.

[0065] In step S103, the requested service of the user is acquired, and the input data of the user is obtained according to the requested service.

[0066] In a possible implementation manner, corresponding input data is generated according to the request service.

[0067] Specifically, directly generate data: When a user initiates a service request, the system can directly generate the required data based on the content of the request. For example, if a user requests a web page, the server can generate the corresponding HTML page based on the requested URL. In this case, the service request directly triggers the data generation process.

[0068] In another possible implementation, data query is performed according to the request service to obtain input data input by the user.

[0069] Specifically, obtaining and processing existing data: In other cases, service requests may involve processing existing data. For example, a user may request to query, filter, or analyze data in a database. In this case, the service request triggers the system to obtain data from a database or other data source, and then processes it to generate a result.

[0070] In step S104, the plurality of working nodes are controlled to process the input data to obtain processing results.

[0071] In a possible implementation, the first node is controlled to preprocess the input data to obtain first data; the second node is controlled to infer or transcode the first data to obtain second data; and the third node is controlled to perform final processing on the second data to obtain a processing result.

[0072] Specifically, the present application integrates several application scenarios and simplifies the process of the service function chain into three virtual functions. First, the first virtual function is responsible for collecting data users and preprocessing. Then, the data is transferred to the second virtual function responsible for further processing, such as machine learning reasoning or transcoding of demand-based video clips. The second virtual function is responsible for performing specified processing on the data. After that, the third virtual function receives the data and performs final processing, such as cropping or indexing video. Finally, the third virtual function sends the results to the user upon request. Note that the present application allows the service function chain to be composed of an indefinite number of virtual functions according to the needs of different scenarios.

[0073] This application implements a real edge service that uses a service function chain to provide services to users, proving the applicability of the system in an edge environment. This application deploys different virtual functions according to device capabilities and task characteristics. The connections between these different functions and between devices will improve the quality of user services, reduce overall service latency, and reduce device power consumption. Using a lightweight virtualization solution, these functions are deployed on different heterogeneous devices in an edge environment. Three applications of positioning services, font recognition, and video transcoding were implemented using multiple Raspberry Pis and Jetson XavierNX, and run in an edge environment using a service function chain solution. The solution divides the entire service into different stages and links them together to provide users with a complete service. Experiments with different applications and different SFC placement schemes show that the proposed system can efficiently support different services, reducing the overall user latency by 86.1% and reducing device power consumption by 33.3%.

[0074] like Figure 3 As shown, the service function chain calling method based on the device-free edge computing environment of the present application is further described below through a specific embodiment:

[0075] The application includes a manager and several worker nodes and users. The manager collects network information from the worker nodes, calculates the best service function link flow, and organizes it into different function chains. Then, it sends the SFC, which is considered as a flow, to all worker nodes that provide the service. When a worker node receives the service flow, it can obtain the following information: 1) the service request to which the user belongs, 2) what operation it should perform, and 3) which node the processed data should be sent to next. Users also receive information about which node their data should be sent to and from which node to get the results. Users ask the system to provide services by sending requests and collecting results.

[0076] The detailed service flow is as follows:

[0077] 1) First, when a user requests a service, the manager calculates the best solution based on the current network conditions and returns the best service function link flow. At the same time, the manager notifies all working nodes in the service flow.

[0078] 2) After receiving the notification from the manager, the user sends the data to the first working node according to the service flow. The working node pre-processes the data and passes it to the next node in sequence.

[0079] 3) After preprocessing, the worker node needs to perform inference or transcoding. When inference or transcoding is completed, the node passes the data to the third worker node for post-processing. When the third worker node finishes post-processing, the user sends a request to the node and obtains the result.

[0080] 4) The results are automatically sent to the administrator to update the network information.

[0081] 5) Finally, return to the first step when a new user request arrives.

[0082] Secondly, the service function chain calling system based on the device-free edge computing environment proposed according to the embodiment of the present application is described with reference to the accompanying drawings.

[0083] Figure 4 It is a block diagram of a service function chain calling system based on a device-free edge computing environment according to an embodiment of the present application.

[0084] like Figure 4 As shown, the service function chain calling system 10 based on the device-free edge computing environment includes: a service chain deployment module 100, a node notification module 200, a data acquisition module 300 and a data processing module 400.

[0085] Specifically, the service chain deployment module 100 is used to deploy the service function chain corresponding to the user;

[0086] A node notification module 200, configured to send the service function chain to a corresponding plurality of working nodes, wherein the working nodes include devices that carry virtual functions;

[0087] The data acquisition module 300 is used to acquire the requested service of the user and obtain the input data of the user according to the requested service;

[0088] The data processing module 400 is used to control the plurality of working nodes to process the input data to obtain processing results.

[0089] Figure 5 A schematic diagram of the structure of a terminal provided in an embodiment of the present application. The terminal may include:

[0090] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0091] When the processor 502 executes the program, the service function chain calling method based on the device-free edge computing environment provided in the above embodiment is implemented.

[0092] Furthermore, the terminal further includes:

[0093] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0094] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0095] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0096] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EIS) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0097] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0098] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0099] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the service function chain calling method based on a device-free edge computing environment is implemented as described above.

[0100] One embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the present application Figure 1 A service function chain calling method based on a device-free edge computing environment is provided in any of the corresponding embodiments.

[0101] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0102] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0103] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0104] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable storage medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable storage medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary, and then storing it in a computer memory.

[0105] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0106] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0107] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0108] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

[0109] It should be understood that the application of the present application is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to this application.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A service function chain calling method based on a device-free edge computing environment, characterized in that: The service function chain calling method based on the device-free edge computing environment includes: Deploy the service function chain corresponding to the user; Sending the service function chain to a corresponding plurality of working nodes, wherein the working nodes include devices that carry virtual functions; Acquire the requested service of the user, and obtain the input data of the user according to the requested service; Control the plurality of working nodes to process the input data to obtain processing results.

2. The service function chain calling method based on the device-free edge computing environment according to claim 1 is characterized in that: The service function chain corresponding to the deployed user specifically includes: For the user, obtaining user needs and network information; Evaluate multiple virtual functions according to the user requirements and the network information to obtain evaluation results of the virtual functions; According to the evaluation results of each of the virtual functions, a service function chain corresponding to the user is determined.

3. The service function chain calling method based on the device-free edge computing environment according to claim 2 is characterized in that: The step of evaluating the plurality of virtual functions according to the user requirements and the network information to obtain evaluation results of the virtual functions specifically includes: Obtaining the performance of each of the plurality of virtual functions on each device; The performance of each of the virtual functions is evaluated according to the user demand and the network information to obtain an evaluation result of each of the virtual functions.

4. The service function chain calling method based on the device-free edge computing environment according to claim 2 is characterized in that: Determining the service function chain corresponding to the user according to the evaluation results of each of the virtual functions specifically includes: Constructing a quasi-convex binary optimization model according to the evaluation results of each of the virtual functions; Using a convex optimization method to solve the quasi-convex binary optimization model, to obtain the deployment probability of each virtual function on each device; For each of the virtual functions, determining the target device with the highest deployment probability from the multiple devices; The plurality of virtual functions are respectively deployed on the corresponding target devices to obtain the service function chain.

5. The service function chain calling method based on the device-free edge computing environment according to claim 4 is characterized in that: The quasi-convex binary optimization model is expressed as: Among them, u represents the user, d and e represent the server, f represents the virtual function, and x fdu Indicates whether user u requests virtual function f to run on server d. If x fdu =1 means yes, if x fdu =0 means no, c fdu Indicates processing delay, g fedu represents the transmission delay, s d represents the capacity limit of device d, D represents the set of devices, F represents the set of virtual functions, and U represents the set of users; x (f-1)eu Indicates that virtual function f-1 is deployed on device e.

6. The service function chain calling method based on the device-free edge computing environment according to claim 2 is characterized in that: The obtaining of the user's input data according to the request service is specifically: Generate corresponding input data according to the request service; or Perform data query according to the request service to obtain input data input by the user.

7. The service function chain calling method based on the device-free edge computing environment according to claim 2 is characterized in that: The plurality of working nodes include a first node, a second node and a third node; The controlling the plurality of working nodes to process the input data to obtain a processing result specifically includes: Controlling the first node to preprocess the input data to obtain first data; Controlling the second node to perform inference or transcoding processing on the first data to obtain second data; The third node is controlled to perform final processing on the second data to obtain a processing result.

8. A service function chain calling system based on a device-free edge computing environment, characterized in that: The service function chain calling system based on the device-free edge computing environment includes: The service chain deployment module is used to deploy the service function chain corresponding to the user; A node notification module, used to send the service function chain to a corresponding plurality of working nodes, wherein the working nodes include devices that carry virtual functions; A data acquisition module, used to acquire the requested service of the user and obtain the input data of the user according to the requested service; The data processing module is used to control the plurality of working nodes to process the input data to obtain processing results.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a service function chain calling program based on a device-free edge computing environment stored in the memory and executable on the processor. When the service function chain calling program based on the device-free edge computing environment is executed by the processor, the steps of the service function chain calling method based on the device-free edge computing environment as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a service function chain calling program based on a device-free edge computing environment. When the service function chain calling program based on the device-free edge computing environment is executed by a processor, the steps of the service function chain calling method based on a device-free edge computing environment as described in any one of claims 1 to 7 are implemented.

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