CN109525426B

CN109525426B - FV-based service control system and method for open MEC platform

Info

Publication number: CN109525426B
Application number: CN201811339403.3A
Authority: CN
Inventors: 赵力强; 卢晓迪; 王勇; 梁凯; 李婷
Original assignee: Xidian University
Current assignee: Xidian University
Priority date: 2018-11-12
Filing date: 2018-11-12
Publication date: 2021-07-30
Anticipated expiration: 2038-11-12
Also published as: CN109525426A

Abstract

The invention belongs to the technical field of mobile communication, and discloses a service control system and a service control method of an FV-based open MEC platform; the open MEC server for computing, storing and network full-function virtualization is connected with the BBU resource pool through an optical fiber, is connected with the Internet through a switch and is further connected to a service provider; the open MEC server is provided with a data plane virtual network element vSGW and a vPGW which are separated from a core network. The invention provides a deployment scheme of a calculation, storage and network function virtualization unit by combining FV and MEC, can realize an MEC integrated realization platform of software and hardware decoupling based on general hardware equipment, can reduce service time delay, provides an open interface, flexibly and rapidly deploys network calculation service, has high resource utilization rate, high service quality and perfect profit scheme.

Description

FV-based service control system and method for open MEC platform

Technical Field

The invention belongs to the technical field of mobile communication, and particularly relates to a service control system and method of an FV-based open MEC platform.

Background

Currently, the current state of the art commonly used in the industry is such that: on one hand, the user has higher and higher requirements on service experience, and particularly, the network delay requirement is higher and higher due to the appearance of new experience technologies such as video enhancement and virtual reality. However, the current network application service is generally deployed in a centralized data center, is far away from the user, has a large network delay, and cannot meet the low-delay requirement of the service, and in addition, the network bandwidth required by the new service is high, which inevitably requires that the network bandwidth between the user and the data center is also high enough, which increases the cost of network deployment. Meanwhile, the new service updating iteration speed is high, the existing network depends on hardware equipment, hardware needs to be replaced for replacement service, the cost is high, the network is not opened, and the flexibility is low;

in summary, the problems of the prior art are as follows:

(1) the flow required by the high-rate service is increased rapidly, and the network load is large;

(2) the emerging technology has high requirement on network delay, and the network delay of centralized service is larger;

(3) the deployment cost of the new service is high, and the flexibility is low.

The difficulty and significance for solving the technical problems are as follows: the requirements of specific industries and emerging services on a localized and flexible open network platform are increasingly strong, but the current network system cannot provide guarantee of corresponding index requirements, and the technical problem to be solved is innovation of a network technology, and the network technology can be used as a carrier to enable the emerging services to play their own functions in a larger way, so that users have better experience.

Function Virtualization (FV) includes Network Function Virtualization (NFV), Computing Function Virtualization (CFV), and Storage Function Virtualization (SFV). The NFV technology migrates the functions of each network element used in the telecommunication network from the current dedicated hardware platform to a general commercial server, and virtualizes the functions into Virtualized Network Functions (VNF). Meanwhile, by means of a virtualization technology, resources of infrastructure hardware equipment are pooled, virtual resources are provided for upper-layer applications, application and hardware decoupling is achieved, each application can rapidly increase the virtual resources to achieve the purpose of rapidly expanding the system capacity, or the virtual resources can be rapidly reduced to achieve the purpose of shrinking the system capacity, and network elasticity is greatly improved. And a shared resource pool is formed by adopting uniform hardware servers, and hardware equipment does not need to be separately deployed for newly developed services, so that the online time of the new services is greatly shortened. By allocating the virtual computing and storage resources required by the VNF, flexible and open MEC services can be provided. Mobile Edge Computing (MEC) is a key technology for improving user experience in the future 5G, meeting the new service requirements of ultra-low time delay, ultra-low power consumption, ultra-high reliability and ultra-high density connection.

The invention provides a deployment scheme of a calculation, storage and network function virtualization unit by combining FV and MEC, provides an open interface, reduces service time delay, deploys network service rapidly, has high service quality and perfect profit scheme. The method comprises the steps of calculation, storage, network function virtualization, open interface, flexible addition of customized services, resource management optimization, service delay reduction, rapid deployment of network services, service quality improvement and perfect profit scheme.

Disclosure of Invention

Aiming at the problems in the prior art, the invention provides an FV-based open MEC platform service control system and method which combine the advantages of FV and MEC.

The invention is realized in such a way that an FV-based open MEC platform service control system comprises a MEC server with calculation, storage and network full-function virtualization;

the FV-based open MEC server is connected with the BBU resource pool through an optical fiber, is connected with the Internet through a switch and is further connected to a server of a service provider;

the core network is connected to the internet through a switch, the BBU resource pool is connected with a plurality of RRUs through optical fibers, and devices such as mobile phones serving as users are connected to the network through the RRUs in a wireless mode;

the open MEC server connected with the BBU resource pool is provided with virtual network elements vSGW and vPGW converted from data plane SGW and PGW network elements separated and sunk from a core network, so that a user can connect to the Internet from the MEC server.

Further, the FV-based service control system of the open MEC platform implements network function virtualization, i.e., NFV, by deploying a conventional network element in a Docker container.

Further, the service control system of the FV-based open MEC platform deploys different computing service units in the Docker container, thereby implementing functional virtualization of computing and storage, namely CFV and SFV.

Further, the service control system of the FV-based open MEC platform designs resources and a service database for the MEC service, and manages and maintains corresponding data in real time.

Further, the open MEC server of the FV-based open MEC platform service control system opens an interface for adding and changing services to a service provider, so that the FV-based open MEC platform is an open platform and can flexibly provide services.

Another object of the present invention is to provide a service control method of an FV-based open MEC platform that operates the FV-based open MEC platform service control system, the FV-based open MEC platform service control method including the steps of:

step one, configuring an open MEC server;

secondly, connecting the user to the network through 4G and connecting the user to the open MEC platform;

step three, according to the sending parameter requirements of the corresponding computing services, the user collects corresponding parameter data and sends the parameter data to a controller in the open MEC server, after the controller receives the parameter data, the controller schedules a signed container of the user, the signed container is transmitted into the computing parameters for computing, and after the computing is finished, the result is returned to the user as the original way or sent to a superior cloud data center for processing;

step four, when each container executes a calculation task for a user, the controller monitors the calculation of each container in real time, stores the resource usage amount, calculates the cost according to the condition of the resource usage amount, updates the resource usage amount detail and the cost of each user in a corresponding table in a database at regular time, generates a bill, provides a bill settlement function, then clears the resource usage amount and the cost, and updates the bill;

step five, adjusting the resource allocation condition of each container according to the required resource usage of each container;

step six, when the MEC is applied to a scene that a fixed user requests the same task for a long time, calculating by using the corresponding container, and repeatedly executing the step three to the step five;

seventhly, when the user does not need to request a calculation task or leave the coverage range of the current MEC server, the corresponding container and the user carry out contract-making, information in a corresponding table of the database is updated, and the contracted container can be signed with a new user;

step eight, when the used container number of a certain service reaches 3/4 of the existing container number, a new container is generated by the mirror image, and 1/4 of the existing container number is increased;

step nine, entering the step two, and executing the step two-eight to access the next user;

step ten, when the service needs to be changed and added, replacing or adding the service mirror image according to the new compiled Docker mirror images of various computing services provided by the service provider, executing the step one, after generating a new container, migrating the service running in the original old container to the new container, destroying the old container, and updating the database.

Further, the first step specifically includes:

(1) accessing various computing service Docker mirror images compiled by a service provider through an open interface, numbering the mirror images, and storing mirror image names, the numbering and specific service information in corresponding tables of a database;

(2) and according to the target user numbers N1 and N2 … N3 of each service, generating the number of Docker containers of each specific service as N1+1/4N1 and N2+1/4N2 … N3+1/4N3, and storing the numbers of the containers and the numbers of the corresponding mirror images into corresponding tables of a database.

Further, the second step specifically includes:

(1) a user is connected with the RRU through wireless connection and further connected to the BBU; a control plane connected to the core network, registering information; data access is carried out through a sunk core network data surface vSGW and vPGW in the open MEC server, and then the data access is connected to the Internet;

(2) when a user requests the service for the first time, a generated container of the service which is not signed by the user is selected for signing, and the unique number, the container number and the signed marker bit of the user are recorded in a corresponding table of a database.

Another object of the present invention is to provide a mobile communication system applying the FV-based open MEC platform service control method.

In summary, the advantages and positive effects of the invention are: the platform is mainly composed of general hardware equipment and a software platform. Based on the virtualization technology, the universal hardware equipment resources are virtualized, then the network function and the computing function are virtualized into a unit, flexible deployment and change of software can be completed on the universal hardware equipment, the computing service requirement of the specific application scene of the Internet of things is met, meanwhile, the service content can be dynamically changed according to the change of the service without increasing extra overhead, the equipment maintenance cost is reduced, and the utilization rate of the resources is improved.

The system according to the invention, based on network function virtualization, provides services fully compatible with current and future communication systems, and the service objects basically cover all parts from network operators to common users, i.e. communication and related industries. The open MEC service platform can well fill the gap of the increasing requirements of the industry, and has strong competitiveness.

The invention provides a deployment scheme of a calculation, storage and network function virtualization unit by combining FV and MEC, provides an open interface, reduces service time delay, deploys network service rapidly, has high service quality and perfect profit scheme. The method comprises network, network and storage function virtualization, open type interface, flexible addition of customized services, resource management optimization, service delay reduction, rapid network service deployment, service quality improvement and perfect profit scheme.

Since mobile networks support data services, various generations of mobile technologies have been dedicated to improving network throughput to improve user experience, and actually, as the throughput of emerging services is exponentially improved, time delay becomes a key factor affecting experience. The application side shows that the high-quality video service has a very strict requirement on the time delay, for example, the AR/VR service requires the highest time delay to be 20ms, otherwise, the user may feel dizzy and experience may be seriously affected. And 5G even puts forward a business target of 1ms end-to-end time delay so as to support the requirements of businesses such as Internet of vehicles, industrial control and the like. However, the current mobile technology is not sufficiently optimized for delay, for example, the LTE technology can improve the throughput rate of an air interface by 10 times, but can only optimize the end-to-end delay by 3 times. The reason is that when the air interface efficiency is greatly improved, the network architecture is not fully optimized to become a bottleneck of service delay. Although the LTE network implements a flat 2-hop architecture, the distance from the base station to the core network is often hundreds of kilometers, multiple convergence and forwarding devices are used, and unpredictable congestion and jitter are added, so that the guarantee of low delay cannot be implemented at all. Therefore, in order to support these services with high requirements on delay, the network function and the service processing function must be moved down to the edge near the access network to reduce the middle hierarchy and implement low-delay service processing.

Meanwhile, a mobile broadband network becomes a basic platform for enterprise office and industry marketing, more and more segments are expected to be customized based on the network, for example, for the safety of mobile office, some enterprises are expected to complete data access to private cloud in an enterprise campus intranet, so that network functions are required to be deployed in the campus and local service distribution can be supported; for example, a korean operator has proposed an intelligent billboard, which can perform intelligent human flow analysis based on network data and dynamically adjust local advertisement content, thereby improving advertisement conversion rate, and thus needs to be based on a localized and open network platform. By using the MEC technology, a Mobile Network Operator (MNO) can rapidly deploy new services for customers and enterprise service departments, which can help them to distinguish service product combinations, provide innovative services from a position closer to a user, increase new revenue channels, and improve QoE (Quality of experience) of the user while improving MNO revenue. The service for sensing the local information can start a brand new service type, and relevant applications are loaded to the base station or a position close to the base station, so that benefits are brought to common users and enterprises, meanwhile, the signaling quantity of a core network is reduced, the operation cost of an MNO is reduced, and the industry is greatly eager for the appearance of a reliable and good-compatibility MEC service platform.

Drawings

Fig. 1 is a schematic structural diagram of a service control system of an FV-based open MEC platform according to an embodiment of the present invention.

Fig. 2 is a flowchart illustrating implementation steps of a service control method for an FV-based open MEC platform according to an embodiment of the present invention.

Fig. 3 is a flowchart of a service control method for an FV-based open MEC platform according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

The invention can provide an open interface for a service provider so as to carry out specific network service, and provides a profit scheme for the service provider while providing low-delay high-data-volume service for a user according to flow charging.

The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.

As shown in fig. 1, a service control system of an FV-based open MEC platform according to an embodiment of the present invention includes: the system comprises a core network, a plurality of Radio Remote Units (RRUs) and a plurality of MEC servers, wherein the core network is connected to the Internet through an exchanger; the open MEC server connected with the BBU resource pool is provided with virtual network elements vSGW and vPGW converted from a data plane SGW and a PGW network element separated and sunk from a core network, and after the open MEC server is directly connected with the Internet through an exchanger, a user can directly surf the Internet through the open MEC server without passing through the core network, so that the time delay is greatly reduced; the open MEC server also has the functions of calculating and storing virtualization, calculating functions for providing required services and caching functions of other hot files such as videos and the like. The open MEC server is provided with a customized database for providing services, and corresponding data are managed and maintained in real time. On one hand, according to the computing function of the edge service platform, the database completes the management and real-time update of the charging information of different services, and on the other hand, aiming at the information created or modified by different services, the database can also maintain and manage various service information signed. The Docker container technology is a lightweight virtualization technology, and compared with a traditional virtual machine, the Docker container technology has relatively low resource consumption on a host machine, and can be flexibly and transplantably established and released. In order to realize a plurality of edge services, including the functions of multimedia caching, edge calculation, charging, resource monitoring and the like, the method reduces the resource consumption of the server and simultaneously provides quick establishment and release of the services; different services and traditional network elements are deployed in a Docker container, so that the virtualization function is realized, the rapid creation and release of the Docker container can be met, and the requirement of low service delay of edge calculation is met; meanwhile, the virtualization technology can be used for virtualizing network, computing and storage resources, the virtualization technology is adopted to share special resources in the traditional cellular network, and corresponding resources can be efficiently and flexibly allocated to edge computing services. The virtualization technology solves the problem of resource idling in the traditional network and a fixed resource allocation scheme, so that resources can be flexibly allocated and released along with the change of service requirements of users, and inherent physical resources of an infrastructure layer are virtualized into virtual resources such as computing, storage and network required by edge computing services. In the aspect of resource management, the NFV supports resource sharing to form a logical virtual resource pool, thereby ensuring the utilization rate of resources and user experience. The open MEC server opens an interface to a service provider, new services can be deployed rapidly, service product combinations can be distinguished, innovative services are provided from a position closer to a user, a new income channel can be increased, and quality experience of the user is improved. The service for sensing the local information can start a brand new service type, and the related application is loaded to the base station or a position close to the base station, so that benefits are brought to common users and enterprises, meanwhile, the signaling quantity of a core network is reduced, and the operation cost of an MNO is reduced. Since the present invention involves the flexible creation, modification and release of a large number of services according to the needs of the user, the data information of the large number of services needs to be maintained. The open MEC platform supports flexible service creation and modification, and thus data is managed and maintained mainly in real time through a database. On one hand, according to the calculation function of the edge service platform, the database completes the management and real-time update of different service charging information; on the other hand, the database can also maintain and manage various service information signed for aiming at the information created or modified by different services.

As shown in fig. 2, a service control method for an FV-based open MEC platform according to an embodiment of the present invention includes the following steps:

s201: the open MEC server is firstly configured to prepare for providing service;

s202: the user is connected to the network through the 4G and is connected to the open MEC platform;

s203: according to the parameter sending requirements of corresponding computing services, a user acquires corresponding parameter data and sends the parameter data to a controller in an open MEC server, the controller dispatches a signed container of the user after receiving the parameter data, the signed container is transmitted into computing parameters for computing, and after computing is completed, a result is returned to the user as the original way or sent to a superior cloud data center for processing;

s204: when each container executes a calculation task for a user, the controller monitors the calculation of each container in real time, stores the resource usage amount, calculates the cost, updates the resource usage amount detail and the cost of each user in the database at regular time, generates a bill and provides a bill settlement function;

s205: while monitoring the resources, adjusting the resource allocation condition of each container according to the required resource usage of each container, and simultaneously, because the resources are virtualized, the resources can be maximally used;

s206: when the MEC is applied to a scene that the fixed equipment requests the same task for a long time, a user does not request a calculation task request once, the request is continuously carried out, the signing of the container is kept all the time, the corresponding container is used for calculation all the time, and the steps S203 to S205 are repeatedly executed;

s207: when the user does not need to request a calculation task or leave the coverage range of the current MEC server, the corresponding container and the user carry out contract, the information in the corresponding table of the database is updated, and the contracted container can be signed with a new user;

s208: when the used container number of a certain service reaches 3/4 of the existing container number, in order to provide a new user with containers more quickly, the new container is regenerated by the mirror image, and 1/4 of the existing container number is increased;

s209: step S202 is entered, and the next user performs access again after steps S202-S208 are executed;

s210: when the service needs to be changed and added, the service mirror image is replaced or added according to the new compiled Docker mirror images of various computing services provided by the service provider, step S201 is executed, after a new container is generated, the service running in the original old container is migrated to the new container, the old container is destroyed, and the database is updated.

As shown in fig. 3, the service control method for the FV-based open MEC platform according to the embodiment of the present invention includes the following steps:

(1) system configuration: the open MEC server is firstly configured to prepare for providing the service, and the step (1) comprises the following steps:

(1-1) configuring a service image: accessing various computing service Docker mirror images edited by a service provider through an open interface, numbering the mirror images, and storing mirror image names, the numbers and specific service information in corresponding tables of a database;

(1-2) configuring a service container: since the Docker image generation container has the delay of the second level, in order to provide the computing service more quickly, the target user number N1 and N2 … N3 of each service are predicted according to analysis, the number of the Docker containers of each specific service is generated to be N1+1/4N1 and N2+1/4N2 … N3+1/4N3, and the numbers of the containers and the numbers of the corresponding images are stored in corresponding tables of a database.

(2) User access: the user is connected to the network through the 4G, and then is connected to the open MEC platform, and step (2) includes the following steps:

(2-1) network connection: the user is connected with the RRU through wireless connection, further connected with the BBU, then connected with the control plane and the registration information of the core network, and then connected with the open MEC server through the data access of the sinking core network data plane vSGW and vPGW in the open MEC server.

(2-2) contracting container: when a user requests the service for the first time, a generated container of the service which is not signed by the user is selected for signing, and the unique number, the container number and the signed marker bit of the user are recorded in a corresponding table of a database.

(3) And (3) executing a computing task: and according to the parameter sending requirements of the corresponding computing services, the user acquires corresponding parameter data and sends the parameter data to a controller in the open MEC server, the controller schedules the signed container of the user after receiving the parameter data, the computing parameters are transmitted for computing, and after the computing is finished, the result is returned to the user as the original way or sent to a superior cloud data center for processing.

(4) Monitoring the resource usage: when each container executes calculation tasks for users, the controller monitors the calculation of each container in real time, stores the resource usage amount, calculates the cost according to the condition of the resource usage amount, updates the resource usage amount detail and the cost of each user in a corresponding table in the database at regular time, generates a bill, provides a bill settlement function, and then clears the resource usage amount and the cost to update the bill.

(5) And (3) adjusting resource allocation: because the resources of the server are limited and the resources used in the calculation of each container are different, the resource allocation condition of each container is adjusted according to the required resource usage of each container while monitoring the resources, and the resources can be maximally used because of the virtualization of the resources.

(6) And (3) continuously executing the task: when the MEC is applied to a scene that the fixed equipment requests the same task for a long time, a user does not request a calculation task request once, the request is continuously carried out, the container is signed and kept all the time, the corresponding container is used for calculation all the time, and the steps (3), (4) and (5) are repeatedly executed.

(7) The user leaves: when the user does not need to request a calculation task or leave the coverage range of the current MEC server, the corresponding container and the user carry out contract, the information in the corresponding table of the database is updated, and the contracted container can be signed with a new user.

(8) Adjusting the number of containers: when the number of used containers of a service reaches 3/4 of the number of existing containers, in order to provide the new user with containers more quickly, the new containers are regenerated from the mirror image, and 1/4 of the number of existing containers is increased.

(9) And (4) entering the step (2), and executing the step (2-8) to access the next user again.

(10) When the service needs to be changed and added, replacing or adding the service mirror image according to the new compiled Docker mirror images of various computing services provided by the service provider, executing the step (1), after generating a new container, migrating the service running in the original old container to the new container, destroying the old container, and updating the database.

The european telecommunications standardization institute ETSI established an MEC working group in 2014 9 months, combined with companies such as hua shi, intel, nokia published MEC white papers, and conducted intensive research on service scenarios, technical requirements, frameworks, reference frameworks, and the like of the MEC technology. The definition of ETSI over MEC is: the method for providing the IT service environment and the cloud computing capability at the edge of the mobile network emphasizes the approach to the mobile user so as to reduce the time delay of network operation and service delivery and improve the user experience.

The service of edge calculation in the MEC server realizes calculation service through a Docker virtualization platform. Docker is a lightweight container virtualization platform that can quickly deploy applications, allowing almost any program to run in a secure, isolated container environment. Instead of isolating hardware, a container environment is virtualized and isolated from the software level. Compared with the traditional virtual machine, the starting is very quick, and the occupancy rate of hardware is low. The Docker virtualization platform is used for realizing the edge computing service, so that the isolation of different computing tasks can be realized, appropriate resources are distributed to the edge computing service, and the service is efficiently provided for a plurality of computing tasks at the same time.

ETSI emphasizes the proximity of mobile users to MEC to reduce network operation and service delivery latency and improve user experience. For example: in intelligent monitoring, a camera is a user, an MEC server with high computing power is used for processing and analyzing a monitoring video, higher decision-making judgment is carried out based on real-time event monitoring, the cost of the camera is reduced, burden on a core network is avoided, and delay is low. The camera connected to the mobile edge computing network can provide stronger flexibility and lower time delay, the service of the camera is kept stable and privatized, and the camera has lower time delay and relieves the return pressure. Different user services have different requirements on calculated amount and time delay, the invention can provide different edge calculation service schemes according to the requirements on calculated amount and time delay of different services, and can provide mobile edge calculation service for different MEC application equipment.

The invention provides a deployment scheme of a computing, storing and network function virtualization unit by combining FV and MEC, can realize a computing, storing and network integration realization platform based on general hardware equipment, and mainly comprises general hardware equipment and a software platform. Based on the virtualization technology, the resources of the universal hardware equipment are virtualized, then the network function and the computing function are virtualized into a unit, an open interface is provided, flexible deployment and change of software can be completed on the universal hardware equipment, the computing service requirement of the specific application scene of the Internet of things is met, meanwhile, the service content can be dynamically changed according to the change of the service without increasing extra overhead, the equipment maintenance cost is reduced, and meanwhile, the utilization rate of the resources is improved. Therefore, the service delay is reduced, the network service is deployed quickly, the service quality is improved, and a perfect profit scheme is provided.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims

1. The FV-based open MEC platform service control method is characterized in that the FV-based open MEC platform service control method operates in an FV-based open MEC platform service control system, and the FV-based open MEC platform service control system comprises a computing, storage, and network full-function virtualized MEC server;

the core network is connected to the internet through a switch, the BBU resource pool is connected with a plurality of RRUs through optical fibers, and mobile phone equipment serving as a user is connected to the network through the RRUs in a wireless mode;

the open MEC server connected with the BBU resource pool is provided with virtual network elements vSGW and vPGW converted from data plane SGW and PGW network elements separated and sunk from a core network, so that a user can access the Internet from the MEC server;

the service control method of the FV-based open MEC platform comprises the following steps:

step one, configuring an open MEC server;

step ten, when the service needs to be changed and added, replacing or adding the service mirror image according to the new compiled Docker mirror images of various computing services provided by the service provider, executing the step one, after generating a new container, migrating the service running in the original old container to the new container, destroying the old container, and updating the database;

the first step specifically comprises:

(2) and according to the target user numbers N1, N2 and N3 of each service, generating the number of Docker containers of each specific service as N1+1/4N1, N2+1/4N2 and N3+1/4N3, and storing the numbers of the containers and the numbers of the corresponding images into corresponding tables of a database.

2. The service control method of an FV-based open MEC platform according to claim 1, wherein the service control system of the FV-based open MEC platform implements Network Function Virtualization (NFV) by deploying a legacy network element in a Docker container;

the service control system of the FV-based open MEC platform realizes the function virtualization of calculation and storage, namely CFV and SFV, by deploying different calculation service units in a Docker container.

3. The service control method of the FV-based open MEC platform according to claim 1, wherein the service control system of the FV-based open MEC platform designs resources and service databases for MEC services, and manages and maintains corresponding data in real time.

4. The service control method of the FV-based open MEC platform according to claim 1, wherein the open MEC server of the FV-based open MEC platform service control system opens an interface for adding and changing services to a service provider, thereby being an open platform that can flexibly provide services.

5. The FV-based service control method for an open MEC platform according to claim 1, wherein the second step specifically comprises:

6. A mobile communication system applying the FV-based open MEC platform service control method according to any one of claims 1 to 5.