COMMUNICATION CONTROL DEVICE AND COMMUNICATION CONTROL METHOD

Abstract

The object is to suppress communication delays among multiple user terminals with a simpler configuration. [Solution] The communication control device 1 includes a calculation unit 13 that provides information about multiple base stations 3 in which each of the multiple user terminals 2 is located as unknown input to a trained machine learning model, performs calculations on the trained machine learning model, and outputs network setting information for a destination cloud 5 among multiple clouds 5 that are final data processing nodes to which the multiple user terminals 2 can connect, which suppresses delays in communication with the multiple user terminals 2, and a communication control unit 14 that instructs the core network 4 to set up a data communication path between each of the multiple user terminals 2 and the destination cloud 5 based on the network setting information output by the calculation unit 13.

Description

[Technical field]

[0001] The present invention relates to a communication control device and a communication control method. [Background technology]

[0002] Conventionally, in a mobile communication network, MEC (Multi-access Edge Computing) is known as a method for providing cloud computing functions at a location physically close to a user terminal (see Patent Document 1).

[0003] In the technology described in Patent Document 1, a user plane function (UPF) of the core network for suppressing delays in data communication is set for each user terminal. Therefore, even when multiple user terminals connect to a cloud that provides the same website or when multiple user terminals communicate with each other, edge computing that takes into account the overall transmission time delay of multiple user terminals has not been performed. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2018-160813 A Summary of the Invention [Problem to be solved by the invention]

[0005] Conventional techniques have been unable to reduce communication delays among multiple user terminals using a simpler configuration.

[0006] The present invention has been made to solve the above-mentioned problems, and has an object to suppress delays in communications between multiple user terminals with a simpler configuration. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, the communication control device of the present invention comprises a calculation unit configured to provide information of a plurality of base stations in which each of a plurality of user terminals is located as unknown input to a trained machine learning model, perform calculations on the trained machine learning model, and output network setting information regarding a destination data processing device among a plurality of data processing devices that are final data processing nodes to which the plurality of user terminals can be connected, which suppresses delays in communication with the plurality of user terminals, and a communication control unit configured to instruct a core network to set up a data communication path between each of the plurality of user terminals and the destination data processing device based on the network setting information output by the calculation unit.

[0008] In addition, the communication control device of the present invention further includes a learning unit configured to learn, using a machine learning model, the relationship between a combination of the multiple base stations in which each of the multiple user terminals is located and the network setting information for the data processing device to which the multiple user terminals can be connected, which suppresses delays in communication with the multiple user terminals, and a memory unit configured to store the learned machine learning model constructed by the learning unit, and the calculation unit may read out the learned machine learning model stored in the memory unit and perform calculations.

[0009] In addition, the communication control device of the present invention further includes an acquisition unit configured to acquire information of the multiple base stations in which each of the multiple user terminals is located, based on a location registration request signal transmitted by each of the multiple user terminals when it is located at one of the multiple base stations, and the calculation unit may use the information of the multiple base stations acquired by the acquisition unit as the unknown input.

[0010] In addition, in the communication control device of the present invention, the location registration request signal is associated with a group identifier of a group to which the multiple user terminals belong, the acquisition unit acquires the group identifier associated with the location registration request signal in association with information of the multiple base stations, the memory unit associates the group identifier with the learned machine learning model and stores it, and the communication control unit designates the multiple user terminals having the group identifier, and instructs the core network to set up the data communication path between each of the multiple user terminals and the data processing device to which it is connected.

[0011] In addition, in the communication control device of the present invention, the network setting information may include information of a data processing device to which each of the multiple user terminals is connected that is located at a position among the multiple data processing devices that is a shorter physical distance from the multiple base stations, and a common user plane function for data communication of each of the multiple user terminals may be set by the information of the data processing device to which each of the multiple user terminals is connected.

[0012] In order to solve the above-mentioned problems, the communication control method of the present invention includes a calculation step of providing information on a plurality of base stations in which each of a plurality of user terminals is located as unknown input to a trained machine learning model, calculating the trained machine learning model, and outputting network setting information regarding a destination data processing device among a plurality of data processing devices that are final data processing nodes to which the plurality of user terminals can be connected, which suppresses delays in communication with the plurality of user terminals, and a communication control step of instructing a core network to set up a data communication path between each of the plurality of user terminals and the destination data processing device based on the network setting information output in the calculation step.

[0013] In addition, the communication control method of the present invention further includes a learning step of using a machine learning model to learn the relationship between a combination of the multiple base stations in which each of the multiple user terminals is located and the network setting information for the data processing device to which the multiple user terminals can be connected, which suppresses delays in communication with the multiple user terminals, and a storage step of storing the trained machine learning model constructed in the learning step in a memory unit, and the calculation step may read out the trained machine learning model stored in the memory unit and perform calculations.

[0014] In addition, the communication control method of the present invention further includes an acquisition step of acquiring information of the multiple base stations in which each of the multiple user terminals is located, based on a location registration request signal transmitted by each of the multiple user terminals when it is located in the range of the multiple base stations, and the calculation step may use the information of the multiple base stations acquired in the acquisition step as the unknown input.

[0015] Furthermore, in the communication control method of the present invention, the location registration request signal is associated with a group identifier of a group to which the multiple user terminals belong, the acquisition step associates and acquires the group identifier associated with the location registration request signal with information of the multiple base stations, the storage step associates the group identifier with the trained machine learning model and stores it in the memory unit, and the communication control step may specify the multiple user terminals having the group identifier, and instruct the core network to set up the data communication path between each of the multiple user terminals and the data processing device to which it is connected.

[0016] In addition, in the communication control method of the present invention, the network setting information may include information of a data processing device to which each of the multiple user terminals is connected that is located at a position among the multiple data processing devices that is a shorter physical distance from the multiple base stations, and a common user plane function for data communication of each of the multiple user terminals may be set by the information of the data processing device to which each of the multiple user terminals is connected. Effect of the Invention

[0017] According to the present invention, information on a plurality of base stations in which each of a plurality of user terminals is located is provided as an unknown input to a trained machine learning model, and the trained machine learning model is operated to output network setting information related to a destination data processing device that suppresses communication delays with the plurality of user terminals among a plurality of data processing devices that are data final processing nodes to which the plurality of user terminals can be connected. Therefore, communication delays between a plurality of user terminals can be suppressed with a simpler configuration. [Brief description of the drawings]

[0018] [Figure 1] FIG. 1 is a block diagram showing a configuration of a communication control system including a communication control device according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram for explaining the configuration of the first storage unit of the communication control device according to the present embodiment. [Diagram 3] FIG. 3 is a diagram for explaining the learning process performed by the learning unit included in the communication control device according to the present embodiment. [Figure 4] FIG. 4 is a block diagram showing a hardware configuration of the communication control device according to the present embodiment. [Diagram 5] FIG. 5 is a sequence diagram for explaining the operation of a communication control system including a communication control device according to the present embodiment. [Figure 6] FIG. 6 is a flowchart for explaining the operation of the communication control device according to the present embodiment. [Figure 7]FIG. 7 is a flowchart for explaining the operation of the communication control device according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will now be described in detail with reference to FIGS.

[0020] [Communication control system configuration] First, with reference to FIG. 1, an overview of a communication control system including a communication control device 1 according to an embodiment of the present invention will be described.

[0021] The communication control system according to the present embodiment includes a communication control device 1, a user terminal 2, a base station 3, a core network 4, and a cloud (data processing device) 5. The communication control system is provided in a 5G mobile communication network. The communication control system predicts a specific cloud 5 that further suppresses communication delays among multiple clouds 5 to which each of multiple user terminals 2 can connect via a base station 3 in which the user terminals 2 are located. Furthermore, the communication control system sets an optimal UPF 44 for connecting to the specific cloud 5 for each of the multiple user terminals 2. The communication control device 1 is connected to the core network 4 via a network NW.

[0022] The user terminal 2 is realized as a mobile communication terminal such as a smartphone, a tablet computer, a laptop computer, etc. The user terminal 2 is equipped with a SIM, and the contract profile of the SIM stores the subscriber identification information of the user, and includes identifier information such as a subscriber identification number (IMSI: International Mobile Subscriber Identity) assigned to a mobile phone line contract, a telephone number of the subscriber user (MSISDN: Mobile Subscriber International Subscriber Directory Number), and a SIM card number (ICCID: Integrated Circuit Card Identifier). The user terminal 2 is uniquely identified by the IMSI.

[0023] The user terminal 2 is also assigned a terminal IP address that uniquely identifies the terminal. The IP address is assigned to the user terminal 2 through the SMF 42 after the session is established. In this embodiment, there are N user terminals 2 (N is a positive integer equal to or greater than 2). The user terminals 2-1, 2-2, . . . , 2-N are each present in the communication area of ​​a different base station 3. The user terminals 2 access a specific cloud 5 from a designated UPF 44 via the base station 3 in which they are each present. In this embodiment, the multiple user terminals 2 are grouped in advance based on a predetermined attribute, and a group ID (group identifier) ​​is assigned. The predetermined attribute can be determined based on any criteria, such as multiple user terminals 2 managed by the same organization or QoS requirements.

[0024] When moving within a communication area, as a periodic location update, and when the power is turned on, the user terminal 2 transmits a location registration request signal to the core network 4 via the base station 3. The location registration request signal transmitted by the user terminal 2 includes the IMSI.

[0025] The base station 3 is composed of a wireless base station compatible with the 5G system, and relays communication between the user terminal 2 present in the communication area and the core network 4. The base station 3 is connected to the core network 4 via a network such as a backhaul link. N base stations 3 (N is an integer equal to or greater than 2) are provided. Hereinafter, when the base stations 3-1, 3-2, . . . , 3-N are not distinguished from one another, they are collectively referred to as "base station 3". The base station 3 is uniquely identified by a base station ID. In addition, the geographical location of the base station 3 can also be ascertained by the base station ID. That is, the base station ID and location information consisting of the latitude, longitude, and altitude of the location where the base station 3 is located are associated with each other and stored in the auxiliary storage device 105 of the communication control device 1 described later.

[0026] The core network 4 is connected to the communication control device 1 via a network NW such as a LAN, a WAN, or the Internet. The core network 4 includes an AMF (Access and Mobility Management Function) 40, a UDM (Unified Data Management) / UDR (Unified Data Repository) 41, a SMF (Session Management Function) 42, and a PCF (Policy Control Function) 43, which are nodes in the C-plane. The core network 4 also includes a plurality of UPFs (User Plane Functions) 44 in the U-plane. Functional nodes in the U-plane and C-plane other than those described above that the core network 4 includes are omitted from the illustration.

[0027] The AMF 40 is an access and mobility management device, and manages the registration and wireless connection of the user terminal 2 that moves to each communication area.

[0028] The UDM / UDR 41 manages subscriber profiles, performs authentication, and manages mobility. In this embodiment, the UDM / UDR 41 stores a group ID assigned to each IMSI in the subscriber profile. The UDM / UDR 41 includes a communication interface 41a for communicating with the communication control device 1.

[0029] Furthermore, in response to an instruction from the communication control device 1, the UDM / UDR 41 creates and stores a setting information table T1 in which the IMSIs of multiple user terminals 2, group IDs, base station IDs, communication paths of the UPF 44 set in data communication of the user terminals 2, and the connection destination cloud 5 are associated with one another, as shown in Fig. 2. The instruction from the communication control device 1 includes grouping information in which multiple IMSIs of control targets that are specified in advance are associated with group IDs. The value of the IP address of the UPF 44 in the setting information table T1 is registered after a communication path is set by the SMF 42 and PCF 43 described later. The IP address of the cloud 5 is registered when a predicted value is obtained by a calculation unit 13 of the communication control device 1 described later.

[0030] The UDM / UDR 41 can configure the setting information table T1 by adding a group ID field to the subscriber profile. The setting information table T1 managed by the UDM / UDR 41 is also synchronized with the communication control device 1, and the same contents are stored (second storage unit 15). Note that, although the present embodiment illustrates a case in which the UDM / UDR 41 is configured as a single device, the UDM / UDR 41 may also be a device in which the UDM and UDR are arranged separately.

[0031] The SMF 42 is a session management function that performs the establishment, modification, release, etc. of PDU (Packet Data Unit) sessions between the user terminal 2 and a data network such as the Internet. The SMF 42 sets an appropriate communication path for data communication between the user terminal 2 and the UPF 44 based on a PCC (Policy and Charging Control) policy from the PCF 43.

[0032] The PCF 43 determines QoS and policies and provides them to the SMF 42. The PCF 43 applies PCC rules according to the 3GPP (registered trademark) specifications, and in response to an instruction from the communication control device 1, creates a PCC policy for setting a communication path of the UPF 44 through which the user terminal 2 communicates.

[0033] The UPF 44 is a user plane function, and processes packets between the base station 3 and a data network such as the Internet. The UPF 44 functions as a gateway between the core network 4 and an external data network. A plurality of UPFs 44 are provided in the core network 4. As shown in FIG. 1, each of the UPFs 44 is directly connected to each of the base stations 3-1, 3-2, . . . , 3-N, that is, a so-called full mesh connection. In this embodiment, each UPF 44 transmits a packet from the user terminal 2 to the cloud 5 via a data network such as the Internet. Also, each UPF 44 forwards a packet transmitted from the cloud 5 to the user terminal 2. As shown in FIG. 1, each UPF 44 has one cloud 5 as a connection destination. In this embodiment, a plurality of user terminals 2 belonging to the same group ID communicate with any of the optimal UPFs 44 among the UPFs 1 to UPF_N, which is specified according to the cloud 5 related to the specific base of the connection destination. The UPF 44 has an IP address, which allows the UPF 44 to be uniquely identified.

[0034] The cloud 5 provides a predetermined website, web application, etc. The cloud 5 is a cloud base that is a geographical location or area where physical devices constituting a website, etc. are located. The cloud 5 can be an edge server such as a server, a data center, or an MEC server. In this embodiment, multiple user terminals 2 having the same group ID can be connected to multiple clouds 5 that are data final processing nodes that provide the same website, etc.

[0035] The multiple clouds 5 are distributed and located at positions geographically distant from each other. The distance from each base station 3 to each of the multiple clouds 5 is different for each cloud 5. For example, the cloud 5 physically closest to the base station 3-1 is "cloud 1-1", and the cloud 5 farthest from the base station 3-1 is "cloud 1-N". The multiple user terminals 2 access the same cloud 5 from the base station 3 in which they are located via the same designated UPF 44. The clouds 5 can be uniquely identified by their IP addresses, and location information is associated with the IP addresses and stored in an auxiliary storage device 105 of the communication control device 1 described later.

[0036] [Function block of communication control device] 1, the communication control device 1 includes an acquisition unit 10, a learning unit 11, a first storage unit 12 (storage unit), a calculation unit 13, a communication control unit 14, and a second storage unit 15. The communication control device 1 learns the relationship between a combination of a plurality of base stations 3 in which a plurality of user terminals 2 are present, and network setting information related to a connection destination cloud 5 that suppresses delays in data communication with the plurality of user terminals 2.

[0037] The acquisition unit 10 acquires information on the multiple base stations 3 in which each of the multiple user terminals 2 is located, based on a location registration request signal transmitted by each of the multiple user terminals 2 when it is within the range of the multiple base stations 3. The acquisition unit 10 also acquires a group ID associated with the location registration request signal transmitted by the multiple user terminals 2 and information on the multiple base stations 3 in association with each other. A base station ID is used as the information on the base station 3. When the location registration request signal transmitted by the user terminal 2 passes through the core network 4, the base station ID is added to the location registration request signal in the core network 4. As described above, the location registration request signal is transmitted when the user terminal 2 crosses the communication area of ​​each base station 3 or at regular intervals.

[0038] The base station ID acquired by the acquisition unit 10 indicates information on the base station 3 in which multiple user terminals 2 with the same group ID are present during the same time period. The base station ID for each user terminal 2 acquired by the acquisition unit 10 is used as an unknown input when the calculation unit 13 described below performs calculations for a trained machine learning model. In addition, the base station ID acquired by the acquisition unit 10 can be used as part of the teacher data when the learning unit 11 learns the machine learning model.

[0039] The learning unit 11 uses a machine learning model to learn the relationship between a combination of a plurality of base stations 3 in which each of the plurality of user terminals 2 is located and network setting information related to a connection destination cloud 5 that suppresses delays in communication with the plurality of user terminals 2, among a plurality of clouds 5 that are data final processing nodes to which the plurality of user terminals 2 can be connected. The learning unit 11 can learn the machine learning model by supervised learning.

[0040] The communication delay is particularly the transmission delay of the entire plurality of user terminals 2 in data communication among the plurality of user terminals 2. In other words, the transmission delay of data communication on a group ID basis is the target of suppression. The transmission delay includes delay caused by the endpoint being physically far away when viewed from the plurality of base stations 3 in which the plurality of user terminals 2 are located. Specifically, the transmission delay in data transfer in the user plane from the plurality of base stations 3 to the cloud 5 can be the target of suppression. In this case, the transmission delay of data communication for the entire group is suppressed by using the cloud 5 that is the shortest or optimal physical distance overall from each of the base stations 3 in which the plurality of user terminals 2 are located as the connection destination.

[0041] The network setting information includes information on a cloud 5 that is located at a location closer physically to the base stations 3 than the clouds 5 that are located at different geographical locations for each of the user terminals 2. That is, the network setting information identifies the cloud 5 to connect to, and the information on the identified cloud 5 makes it possible to set an optimal UPF 44 for data communication of each of the user terminals 2. For example, by identifying cloud 1 as the connection destination among clouds 1 to N, an optimal UPF_1 for connecting to cloud 1 is identified.

[0042] Specifically, the network setting information may be a DNN (Data Network Name) identifier that can identify information on the cloud 5 to which the connection is made and information on the UPF 44 to which the routing is made. When optimizing the physical distance from multiple base stations 3 to a specific cloud 5, the distance from a certain user terminal 2 is not necessarily the shortest distance. A cloud 5 that is closer to the multiple base stations 3, that is, that is, that is at an optimal distance, is identified by the network setting information.

[0043] FIG. 3 shows the structure of a neural network model employed as an example of a machine learning model used by the learning unit 11. The neural network model includes an input layer x, a hidden layer h, and an output layer y. The learning unit 11 provides the base station IDs of the base stations 3 in which the multiple user terminals 2 (IMSI) having the same group ID are located to the input layer of the neural network model, applies an activation function to the weighted sum of the inputs, and passes the output determined by threshold processing to the output layer. The output node of the output layer outputs a predicted output of a model of network setting information related to the cloud 5 to which the multiple user terminals 2 are connected for a combination of the base station IDs of the base stations 3 in which the multiple user terminals 2 are located.

[0044] The learning unit 11 introduces an objective function to learn parameters of the neural network model so that a predicted value of network setting information from the neural network model for a combination of base stations 3 in which a plurality of user terminals 2 are located becomes a value of network setting information of a correct answer label. The learning unit 11 adjusts weight parameters of the neural network related to the machine learning model so that the objective function is minimized, that is, becomes 0. The learning unit 11 can optimize the objective function using backpropagation or the like.

[0045] Specifically, the learning unit 11 can train the neural network to predict the cloud 5 to be connected to as a class classification, and output the cloud 5 with the correct label with a high probability by treating the optimal cloud 5 as the correct answer. In this case, cross entropy loss is used as the objective function. Alternatively, the learning unit 11 can introduce an objective function that minimizes the squared error, which is the distance error between the multiple base station IDs and the corresponding cloud 5, as a regression problem. When treating it as a regression problem, learning is performed to minimize the squared error between the actual distance between the positions of the multiple base stations 3 and the position of the cloud 5 as the correct answer label and the predicted value of the distance output by the model.

[0046] The first storage unit 12 stores the trained machine learning model constructed by the learning unit 11. The first storage unit 12 stores the trained machine learning model in association with a group ID.

[0047] The calculation unit 13 provides information about the multiple base stations 3 in which each of the multiple user terminals 2 is located as unknown input to the trained machine learning model, performs calculations on the trained machine learning model, and outputs network setting information regarding a destination cloud 5 that reduces communication delays with the multiple user terminals 2, among the multiple clouds 5 that are data final processing nodes to which the multiple user terminals 2 can connect.

[0048] The calculation unit 13 uses the base station IDs of the multiple base stations 3 added to the location registration request signals transmitted by the multiple user terminals 2, acquired by the acquisition unit 10, as unknown inputs. That is, the base station IDs for each IMSI of the same group ID are provided as unknown inputs to the trained machine learning model corresponding to the group ID stored in the first storage unit 12. The calculation unit 13 can output the identifier of the DNN as the network setting information. The IP address of the cloud 5 to be connected, which is indicated by the network setting information output by the calculation unit 13, is registered in the setting information table T1.

[0049] The communication control unit 14 instructs the core network 4 to set a data communication path between each of the multiple user terminals 2 and the destination cloud 5 based on the network setting information output by the calculation unit 13. More specifically, the communication control unit 14 designates the IMSIs of the multiple user terminals 2 having the same group ID, and instructs the core network 4 to set a UPF 44 common to each of the multiple user terminals 2. When the calculation unit 13 outputs the identifier of the DNN as the network setting information, it can acquire the identification information of the destination cloud 5 associated with the identifier of the output DNN by referring to the information stored in the auxiliary storage device 105.

[0050] The communication control unit 14 designates a destination cloud 5 identified by a DNN identifier for the IMSI of each user terminal 2 of the same group ID, and instructs the setting of the UPF 44 of each user terminal 2. In detail, the communication control unit 14 refers to the table T1 shown in Fig. 2 in response to receiving a location registration request signal from the user terminal 2 via the core network 4. Note that the location registration request signal includes the IMSI of the user terminal 2 as described above.

[0051] The communication control unit 14 requests the PCF 43 in the core network 4 to create a PCC policy by specifying the group ID, IMSI, IP address of the communication control device 1, and the cloud 5 to which the connection is to be made. In response to the creation request, the PCF 43, SMF 42, and UDM / UDR 41 in the core network 4 work together to set an appropriate communication path of the UPF 44 for data communication of the user terminal 2. When the communication path of the UPF 44 is set for data communication of the user terminal 2, the IP address of the UPF 44 related to the setting of the communication path is stored for each IMSI in table T1 in the second storage unit 15, as described in FIG. 2 .

[0052] The second storage unit 15 stores a setting information table T1 that associates the IMSIs, group IDs, base station IDs, communication paths of the UPF 44 set in data communication of the user terminals 2, and the destination cloud 5 with each other for the multiple user terminals 2. In the setting information table T1, the identification information of the destination cloud 5 ("cloud IP address") is information that is specified and stored by the identifier of the DNN output from the calculation unit 13. Also, the identification information of the UPF 44 ("UPF IP address") is information that is stored in response to the UPF 44 being set in response to an instruction from the core network 4 of the communication control unit 14.

[0053] [Hardware configuration of communication control device] Next, an example of a hardware configuration for implementing the communication control device 1 having the above-mentioned functions will be described with reference to FIG.

[0054] 4, the communication control device 1 can be realized by, for example, a computer including a processor 102, a main memory device 103, a communication interface 104, an auxiliary memory device 105, and an input / output (I / O) 106, which are connected via a bus 101, and a program that controls these hardware resources. Furthermore, the communication control device 1 can include a display device 107 connected via the bus 101.

[0055] The processor 102 is realized by a CPU, a GPU, an FPGA, an ASIC, or the like.

[0056] Programs for the processor 102 to perform various controls and calculations are stored in advance in the main memory device 103. The processor 102 and the main memory device 103 realize the various functions of the communication control device 1, such as the acquisition unit 10, the learning unit 11, the calculation unit 13, and the communication control unit 14 shown in FIG.

[0057] The communication interface 104 is an interface circuit for network connection between the communication control device 1 and various external electronic devices.

[0058] The auxiliary storage device 105 is composed of a readable / writable storage medium and a drive for reading and writing various information such as programs and data from and to the storage medium. The auxiliary storage device 105 can use a semiconductor memory such as a hard disk or a flash memory as the storage medium.

[0059] The auxiliary storage device 105 has a program storage area for storing a communication control program executed by the communication control device 1. The auxiliary storage device 105 also has a program storage area for storing a machine learning program executed by the communication control device 1. The auxiliary storage device 105 also has an area for storing information in which a DNN identifier is associated with identification information of the cloud 5 and identification information of the UPF 44. The auxiliary storage device 105 also has an area for storing grouping information in which the IMSI of a plurality of user terminals 2 is associated with a group ID. The auxiliary storage device 105 also has an area for storing the base station ID, the identification information of the UPF 44, and the identification information of the cloud 5 in association with their respective location information. The auxiliary storage device 105 realizes the first storage unit 12 and the second storage unit 15 described in FIG. 1. Furthermore, for example, the auxiliary storage device 105 may have a backup area for backing up the above-mentioned data, programs, and the like.

[0060] The input / output I / O 106 is an input / output device that inputs signals from an external device and outputs signals to an external device.

[0061] The display device 107 is configured with an organic EL display, a liquid crystal display, etc. The display device 107 can display the setting information of the cloud 5 and the UPF 44 to which the connection is to be made for each group ID.

[0062] [Operation of communication control system] Next, the operation of the communication control system including the communication control device 1 having the above-mentioned configuration will be described with reference to the sequence of Fig. 5. Fig. 5 shows the processing of the communication control system related to inference after the learning unit 11 of the communication control device 1 has constructed a trained machine learning model.

[0063] First, the communication control device 1 transmits grouping information associated with a group ID and an IMSI to the UDM / UDR 41 (step S100). The grouping information is stored in advance in the communication control device 1. Next, the UDM / UDR 41 creates a setting information table T1 (FIG. 2) based on the received grouping information (step S101). In step S101, the values ​​of "group ID" and "IMSI" in the setting information table T1 are registered, and there are no entries for the values ​​of the other items. The setting information table T1 is also stored in the second storage unit 15 of the communication control device 1.

[0064] Thereafter, the multiple user terminals 2 of group ID "1" transmit location registration request signals to the core network 4 via the base stations 3 in which they are located (step S102). The location registration request signal includes the IMSI of the user terminal 2 and the base station ID of the base station 3 in which they are located. When the location registration request signal is received by the UDM / UDR 41 via the AMF 40, the UDM / UDR 41 refers to the grouping information in the setting information table T1 (FIG. 2) created in step S101, associates the group ID with the base station ID and IMSI included in the received location registration request signal, and further transfers the location registration request signal to the communication control device 1 (step S103). Note that in step S103, the value of the base station ID in the setting information table T1 is set.

[0065] Next, the calculation unit 13 of the communication control device 1 reads out the trained machine learning model associated with the group ID received in step S103 from the first storage unit 12, and performs calculation processing (step S104). In step S104, the base station ID of the IMSI of the same group ID acquired by the acquisition unit 10 of the communication control device 1 in step S103 is used as an unknown input to perform calculations on the trained machine learning model. The calculation processing in step S104 outputs optimal network setting information, that is, the identifier of the DNN. The IP address of the destination cloud 5 identified by the identifier of the DNN is registered in the setting information table T1 (FIG. 2).

[0066] Thereafter, the communication control unit 14 of the communication control device 1 requests the PCF 43 to create a PCC policy by specifying the IP address of the cloud 5 associated with the identifier of the DNN output in step S104, and further the group ID, IMSI, and IP address of the communication control device 1 (step S105). In the example of FIG. 5, cloud_2 is specified. Then, the PCF 43 creates a PCC policy based on the specified requirements (step S106). The PCF 43 creates a PCC policy including information on which UPF 44 the data communication of the user terminal 2 will pass through. The PCC policy specifies the optimal UPF 44 as a communication path for data communication from the user terminal 2 of the same group ID to cloud_2.

[0067] Next, the PCF 43 transmits the created PCC policy to the SMF 42 (step S107). After that, the SMF 42 transmits setting information of a data communication path related to a user plane function, such as setting of a communication path specified by the PCC policy, to the UPF 44 designated by the PCC policy (step S108). In the example of Fig. 5, UPF_2 is set. Next, the UPF 44 (UPF_2) registers the received setting information of the data communication path in a memory (step S109).

[0068] Next, the UPF 44 (UPF_2) transmits an ACK to the SMF 42 to notify it of the IP address of UPF_2 (step S110). Furthermore, the SMF 42 transmits an ACK to the communication control device 1 to notify it of the IP address of UPF_2 (step S111). After that, the communication control device 1 notifies the UDM / UDR 41 of the IP address of UPF_2, and transmits an ACK to the user terminal 2 (step S112). At that time, the IP address of UPF_2 that communicates with the user terminal 2 is set in the setting information table T1 (FIG. 2). Moreover, the setting information table T1 updated by the UDM / UDR 41 is also stored in the second storage unit 15 of the communication control device 1. Further, after that, a communication path for data communication between the user terminal 2, the UPF 44 (UPF_2), and the cloud 5 (cloud_2) is established (step S113). The processes from step S102 to step S113 are also performed for other user terminals 2 in the same group ID "1."

[0069] Through the above process, multiple user terminals 2 with the same group ID can connect to the same cloud_2 and perform data communication via a transfer route that minimizes overall delays in data communication.

[0070] Next, the operation of the communication control device 1 having the above-mentioned configuration will be described with reference to the flowcharts of Figures 6 and 7. Figure 6 is a flowchart showing the learning process by the communication control device 1. Figure 7 is a flowchart showing the calculation process by the communication control device 1.

[0071] As shown in Fig. 6, first, the learning unit 11 prepares teacher data (step S1). Specifically, the base station IDs of the base stations 3 in which the respective user terminals 2 having the same group ID are present, which are acquired by the acquisition unit 10, can be used as teacher data. A DNN identifier is given in advance as a correct label to a set of combinations of base station IDs for each IMSI. Alternatively, the identification information of the cloud 5 may be given as the correct label.

[0072] Next, the learning unit 11 uses the teacher data prepared in step S1 to learn the machine learning model (step S2). More specifically, the learning unit 11 uses the machine learning model to learn the relationship between the combination of base station IDs of the base stations 3 in which each of the user terminals 2 is located and the network setting information related to the cloud 5 of the connection destination that suppresses delays in data communication with the user terminals 2.

[0073] After that, the first storage unit 12 stores the trained machine learning model constructed in step S2 in association with the group ID (step S3).

[0074] Next, as shown in Fig. 7, the acquisition unit 10 acquires the base station IDs of the base stations 3 in the areas of the multiple user terminals 2 with a common group ID (step S10). Step S10 corresponds to step S103 described in Fig. 5. That is, in step S10, the base station IDs of the base stations 3 in the areas of the multiple user terminals 2 with the same group ID are acquired in response to location registration request signals transmitted by the multiple user terminals 2 with the same group ID.

[0075] Next, the calculation unit 13 reads out the trained machine learning model corresponding to the group ID acquired in step S10 from the first storage unit 12, performs calculations on the trained machine learning model using the combination of base station IDs acquired in step S10 as unknown inputs, and outputs network setting information on a destination cloud 5 that suppresses transmission delays in data communication for the entire group (step S11). In step S11, an identifier of a DNN indicating a cloud 5 that is closer in physical distance from the multiple base stations 3 is output. Step S11 corresponds to step S104 described in FIG. 5.

[0076] Thereafter, the communication control unit 14 designates each of the multiple user terminals 2 having the same group ID based on the network setting information output in step S11, and instructs the core network 4 to set the UPF 44 for the multiple user terminals 2 (step S12). Step S12 corresponds to step S105 described in FIG. 5.

[0077] As described above, the communication control device 1 according to the present embodiment uses a machine learning model to learn combinations of base stations 3 in which multiple user terminals 2 are located, and network setting information related to a connection destination cloud 5 that can reduce transmission delays in data communication with the multiple user terminals 2, and stores the learned network setting information in a database in advance. Therefore, communication delays between the multiple user terminals 2 can be reduced with a simpler configuration.

[0078] Furthermore, according to the communication control device 1 of this embodiment, a plurality of user terminals 2 are grouped, and an optimal connection destination cloud 5 is selected for each group. Therefore, by selecting a cloud 5 that is physically close as a connection destination for each group of a plurality of user terminals 2, it is possible to more efficiently suppress transmission delays in data communication for the entire group with a simpler configuration.

[0079] Furthermore, according to the communication control device 1 of this embodiment, acquisition of a base station ID, calculation of a trained machine learning model, and a request for creation of a PCC policy are performed in response to a location registration request signal transmitted from a base station 3 in which multiple user terminals 2 are located. Therefore, a delay in communication between multiple user terminals 2 can be suppressed with a simpler configuration.

[0080] In the embodiment described above, a multilayer neural network is used as the machine learning model used by the learning unit 11. However, the machine learning model may be a decision tree-based model such as a multilayer perceptron or a random forest, or a gradient boosting-based decision tree such as XGBoost or LightGBM, a k-nearest neighbor method, a support vector machine, or a linear regression.

[0081] Also, in the embodiment described above, a case has been described in which the base station IDs of base stations 3 in which multiple user terminals 2 with the same group ID are present are input to the input layer of the multilayer neural network used by the learning unit 11. However, if it is possible to construct a model that outputs information on the connected cloud 5 in order to suppress transmission delays in data communication across multiple user terminals 2, the feature amount input to the input layer can be not only the base station ID for each IMSI, but also values ​​such as the number of hops in a route taking into account logical distance, network delays such as the number of relay nodes and switching processing time, and QoS requirements such as bandwidth and reliability.

[0082] The above describes embodiments of the communication control device and communication control method of the present invention. However, the present invention is not limited to the described embodiments, and various modifications that a person skilled in the art can make within the scope of the invention described in the claims are possible. [Explanation of symbols]

[0083] 1...communication control device, 10...acquisition unit, 11...learning unit, 12...first memory unit, 13...calculation unit, 14...communication control unit, 15...second memory unit, 2...user terminal, 3...base station, 4...core network, 40...AMF, 41...UDM / UDR, 42...SMF, 43...PCF, 44...UPF, 5...cloud, 101...bus, 102...processor, 103...main memory device, 41a, 104...communication interface, 105...auxiliary memory device, 106...input / output I / O, 107...display device, NW...network.

Claims

1. a calculation unit configured to provide information on a plurality of base stations in which each of a plurality of user terminals is located as an unknown input to a trained machine learning model, perform calculations on the trained machine learning model, and output network setting information related to a destination data processing device that suppresses a delay in communication with the plurality of user terminals, among a plurality of data processing devices that are data final processing nodes to which the plurality of user terminals can be connected; a communication control unit configured to instruct a core network to set a data communication path between each of the plurality of user terminals and the destination data processing device based on the network setting information output by the calculation unit; A communication control device comprising:

2. 2. The communication control device according to claim 1, a learning unit configured to learn, using a machine learning model, a relationship between a combination of the plurality of base stations in which each of the plurality of user terminals is located and the network setting information related to a data processing device that is a connection destination among the plurality of data processing devices to which the plurality of user terminals can be connected, the data processing device suppressing a delay in the communication with the plurality of user terminals; A storage unit configured to store the trained machine learning model constructed by the learning unit; Equipped with The calculation unit reads out the trained machine learning model stored in the storage unit and performs calculations. A communication control device comprising:

3. 3. The communication control device according to claim 2, Further, an acquisition unit configured to acquire information of the plurality of base stations in which each of the plurality of user terminals is located, based on a location registration request signal transmitted by each of the plurality of user terminals when the each of the plurality of user terminals is located in the plurality of base stations, The calculation unit uses the information of the plurality of base stations acquired by the acquisition unit as the unknown input. A communication control device comprising:

4. 4. The communication control device according to claim 3, When the location registration request signal transmitted by each of the plurality of user terminals when the each of the plurality of user terminals is within the range of the plurality of base stations is transmitted to the communication control device via the core network, the core network associates a group identifier of a group to which the plurality of user terminals belong with a subscriber identification number included in the location registration request signal, the acquiring unit acquires the group identifier associated with the subscriber identification number included in the location registration request signal and information of the plurality of base stations in association with each other; The storage unit stores the trained machine learning model in association with the group identifier, The communication control unit designates the plurality of user terminals having the group identifier, and instructs the core network to set up the data communication path between each of the plurality of user terminals and the connection destination data processing device. A communication control device comprising:

5. 2. The communication control device according to claim 1, The network setting information includes information of a connection destination data processing device that is located at a position where a physical distance from the base stations is shorter among the plurality of data processing devices, for each of the plurality of user terminals, and A common user plane function for data communication of each of the plurality of user terminals can be set based on the information of the connected data processing device. A communication control device comprising:

6. a calculation step of providing information on a plurality of base stations in which each of a plurality of user terminals is located as an unknown input to a trained machine learning model, performing calculations on the trained machine learning model, and outputting network setting information related to a destination data processing device that suppresses a delay in communication with the plurality of user terminals, among a plurality of data processing devices that are data final processing nodes to which the plurality of user terminals can be connected; a communication control step of instructing a core network to set a data communication path between each of the plurality of user terminals and the destination data processing device based on the network setting information output in the calculation step; A communication control method comprising:

7. 7. The communication control method according to claim 6, Further, a learning step of learning, using a machine learning model, a relationship between a combination of the plurality of base stations in which each of the plurality of user terminals is located and the network setting information related to a data processing device that is a connection destination among the plurality of data processing devices to which the plurality of user terminals can be connected, the data processing device suppressing a delay in the communication with the plurality of user terminals; a storage step of storing the trained machine learning model constructed in the learning step in a storage unit; Equipped with The calculation step reads out the trained machine learning model stored in the storage unit and performs a calculation. A communication control method comprising:

8. 8. The communication control method according to claim 7, Further, the method includes the step of acquiring information on the plurality of base stations in which each of the plurality of user terminals is located, based on a location registration request signal transmitted by each of the plurality of user terminals when the each of the plurality of user terminals is located in the plurality of base stations, The calculation step uses the information of the plurality of base stations acquired in the acquisition step as the unknown input. A communication control method comprising:

9. 9. The communication control method according to claim 8, when the location registration request signal transmitted by each of the plurality of user terminals when it is within the range of the plurality of base stations is transmitted to a communication control device that executes the communication control method via the core network, a group identifier of a group to which the plurality of user terminals belong is associated by the core network with a subscriber identification number included in the location registration request signal; the acquiring step acquires the group identifier associated with the subscriber identification number included in the location registration request signal and information of the plurality of base stations in association with each other; The storing step includes storing the trained machine learning model in the storage unit in association with the group identifier; The communication control step includes specifying the plurality of user terminals having the group identifier, and instructing the core network to set up the data communication path between each of the plurality of user terminals and the data processing device to which the user terminals are connected. A communication control method comprising:

10. 7. The communication control method according to claim 6, The network setting information includes information of a connection destination data processing device that is located at a position where a physical distance from the base stations is shorter among the plurality of data processing devices, for each of the plurality of user terminals, and A common user plane function for data communication of each of the plurality of user terminals can be set based on the information of the connected data processing device. A communication control method comprising:

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