Control device, control method, and program

Abstract

The present invention provides a control device, control method, and program that prevent congestion at base stations when the number of people increases due to a sudden event. [Solution] In a system in which each of a plurality of base stations 100 forms a plurality of cells 10 constituting a mobile network 90 and provides wireless communication services to a user terminal 72, the control device comprises: an acquisition unit that acquires event-related information; a prediction unit that predicts at least one congestion cell from the plurality of cells constituting the mobile network where sudden congestion will occur based on the event-related information acquired by the acquisition unit; and a control unit that controls the mobile parameters of at least one of the congestion cell and surrounding cells so that a user terminal located in the congestion cell can easily be located in the surrounding cells around the congestion cell.

Description

Technical Field

[0001] The present invention relates to a control device, a control method, and a program.

Background Art

[0002] Patent Document 1 describes that it contributes to the improvement of throughput by visualizing the influence of burst traffic on a multiplexed transmission path, and making it possible to easily recognize the occurrence status of burst traffic in a wireless communication system. [Prior Art Documents] [Patent Documents] [Patent Document 1] Japanese Patent Laid-Open No. 2018-67844

Summary of Invention

Means for Solving the Problems

[0003] According to one embodiment of the present invention, a control device is provided. The control device may include an acquisition unit that acquires event-related information. The control device may include a prediction unit that predicts at least one congested cell where sudden congestion occurs from a plurality of cells constituting a mobile network, based on the event-related information acquired by the acquisition unit. The control device may include a control unit that controls mobile parameters of at least one of the congested cell and the peripheral cells surrounding the congested cell, so that user terminals located in the congested cell are more likely to camp on the peripheral cells around the congested cell.

[0004] In the control device, the prediction unit may predict a congestion time at which the sudden congestion occurs. In the control device, the control unit may control the mobile parameters of at least one of the congested cell and the peripheral cells before the congestion time.

[0005] In any of the control devices, the event-related information may include information on social media.

[0006] In any of the control devices, the mobile parameters may include at least one of the parameters related to handover and the parameters related to cell reselection.

[0007] In any of the control devices, the prediction unit may predict the traffic volume of the congested cell. In any of the control devices, the control unit may control the mobile parameters of at least one of the congested cell and the surrounding cell based on the traffic volume predicted by the prediction unit.

[0008] In any of the control devices, the acquisition unit may acquire information regarding the communication of the congested cell after the control unit has controlled the mobile parameters of at least one of the congested cell and the surrounding cell. In any of the control devices, the control unit may control the mobile parameters of at least one of the congested cell and the surrounding cell based on the information regarding the communication of the congested cell acquired by the acquisition unit.

[0009] In any of the control devices, the control unit may, after controlling the mobile parameters of at least one of the congested cell and the surrounding cells before the sudden congestion actually occurs, and if it determines that the sudden congestion did not actually occur in the congested cell, return the mobile parameters of at least one of the congested cell and the surrounding cells to their values ​​before control.

[0010] In any of the control devices, the acquisition unit may acquire the latest event-related information after the control unit has controlled the mobile parameters of at least one of the congested cells and the surrounding cells. In any of the control devices, the prediction unit may update the prediction of the congested cells based on the latest event-related information acquired by the acquisition unit. In any of the control devices, the control unit may control the mobile parameters of at least one of the congested cells and the surrounding cells based on the prediction of the congested cells updated by the prediction unit.

[0011] In any of the control devices, the prediction unit may predict the traffic volume of the surrounding cells. In any of the control devices, the control unit may control the mobile parameters of at least one of the congested cells and the surrounding cells based on the traffic volume of the surrounding cells predicted by the prediction unit.

[0012] In any of the control devices, the control unit may control the mobile parameters of at least one of the congested cells and the surrounding cells such that, among the plurality of surrounding cells, the traffic amount predicted by the prediction unit exceeds a predetermined threshold, making it difficult for the user terminal located within the congested cell to be present in the surrounding cell.

[0013] According to one embodiment of the present invention, a control method is provided. The control method may include an information acquisition step of acquiring event-related information. The control method may include a prediction step of predicting at least one congestion cell from a plurality of cells constituting a mobile network where sudden congestion will occur, based on the event-related information acquired in the information acquisition step. The control method may include a control step of controlling the mobile parameters of at least one of the congestion cell and the surrounding cells so that a user terminal located in the congestion cell is more likely to be in the surrounding cells around the congestion cell.

[0014] According to one embodiment of the present invention, a program is provided for causing a computer to execute any of the control methods.

[0015] It should be noted that the above summary of the invention does not enumerate all the necessary features of the present invention. Furthermore, subcombinations of these features may also constitute an invention. [Brief explanation of the drawing]

[0016] [Figure 1] An example of System 20 is shown in general terms. [Figure 2]Schematically illustrates an example of event-related information 30. [Figure 3] Schematically illustrates an example of event-related information 30. [Figure 4] Schematically illustrates an example of event-related information 30. [Figure 5] Schematically illustrates an example of the system 20. [Figure 6] Schematically illustrates an example of the system 20. [Figure 7] Schematically illustrates an example of the system 20. [Figure 8] Schematically illustrates an example of the system 20. [Figure 9] Schematically illustrates an example of the system 20. [Figure 10] Schematically illustrates an example of the system 20. [Figure 11] Schematically illustrates an example of the system 20. [Figure 12] Schematically illustrates an example of the system 20. [Figure 13] Schematically illustrates an example of the system 20. [Figure 14] Schematically illustrates an example of the system 20. [Figure 15] Schematically illustrates an example of the system 20. [Figure 16] Schematically illustrates an example of the system 20. [Figure 17] Schematically illustrates an example of the functional configuration of the control device 200. [Figure 18] Schematically illustrates an example of the flow of processing by the control device 200. [Figure 19] Schematically illustrates an example of the hardware configuration of a computer 1200 that functions as the control device 200. [Mode for Carrying Out the Invention]

[0017] Hereinafter, the present invention will be described through embodiments of the invention, but the following embodiments do not limit the invention according to the claims. Furthermore, not all combinations of features described in the embodiments are necessarily essential to the solving means of the invention.

[0018] Unexpected events such as traffic disruptions can cause a sudden increase in the number of people in places that are not normally crowded. In such cases, base stations may suddenly become congested. Even under these circumstances, it is necessary to prevent base station congestion from occurring in the first place.

[0019] The control device 200 according to this embodiment has a configuration that contributes to solving such problems. For example, the control device 200 analyzes information on social media using AI (Artificial Intelligence) for text analysis and image analysis to identify the time and place of events where people are likely to gather. For example, the control device 200 identifies a base station located at the location where the event is likely to occur as a congestion cell and modifies the parameters of the base station so that the traffic of the congestion cell is distributed to surrounding base stations located around it before congestion actually occurs. These processes by the control device 200 may be performed automatically.

[0020] Figure 1 schematically shows an example of system 20. In the example shown in Figure 1, system 20 comprises a control device 200 and a plurality of base stations 100. Each of the plurality of base stations 100 may form a cell 10 and provide wireless communication services to a user terminal 72. In the example shown in Figure 1, the user terminal 72 is located within the cell 10 formed by the base station 100.

[0021] Being present in a cell may include being connected to the base station forming the cell (connected state), or being in an idle state where the user terminal has registered its location with the base station forming the cell but is not connected. In the drawings of this embodiment, the presence of a user terminal in a cell is represented by drawing a solid line connecting the base station forming the cell and the user terminal. For example, in the example shown in Figure 1, the presence of user terminal 72 in cell 10 is represented by drawing a solid line connecting base station 100 and user terminal 72.

[0022] If the user terminal 72 is located inside the circle of cell 10, but the base station 100 and the user terminal 72 are not connected by a solid line, this may represent a state where the user terminal 72 is located within the coverage area of ​​base station 100, but the user terminal 72 is not present in cell 10. For example, this state includes a state where the user terminal 72 has not registered its location with base station 100, or a state where the user terminal 72 is powered off.

[0023] Multiple cells 10 constitute a mobile network 90. ​​In the example shown in Figure 1, the control device 200 and multiple base stations 100 are connected in a communicative manner. In the example shown in Figure 1, the control device 200 and each of the multiple base stations 100 are connected via the mobile network 90. ​​The control device 200 may be located in the core network of the mobile network 90. ​​The control device 200 may be located on the internet and connected to each of the multiple base stations 100 via the internet and the mobile network 90. ​​The control device 200 may be located on a cloud network and connected to each of the multiple base stations 100 via the cloud network and the mobile network 90. ​​The control device 200 may be located below the mobile network 90. ​​For example, the control device 200 may be located on any of the multiple base stations 100. Multiple control devices 200 may be located.

[0024] The user terminal 72 can be any device as long as it is capable of using wireless communication services. Examples of user terminals include, but are not limited to, smartphones, tablet devices, PCs (Personal Computers), mobile Wi-Fi (registered trademark), wearable devices such as smartwatches and smart glasses, IoT (Internet of Things) terminals such as sensors, smart home appliances, and smart meters, in-vehicle equipment, robots, and game consoles. User terminals can include any device that falls under the category of IoE (Internet of Everything). In the example shown in Figure 1, the user terminal 72 is a smartphone.

[0025] The control device 200 acquires event-related information. Event-related information may include any information related to the occurrence of an event. Event-related information may include information on social media. Event-related information may include big data related to human movement. Event-related information may include information announcing the holding of an event. The control device 200 may acquire event-related information from servers located on the internet, servers located on a cloud network, servers located on the core network of the mobile network 90, and servers located below the mobile network 90, etc. For example, the control device 200 acquires information on social media from a server that provides social media services located on the internet, a cloud network, or the mobile network 90. ​​For example, the control device 200 acquires big data related to human movement from a server that manages big data related to human movement located within the internet, a cloud network, or the core network of the mobile network 90. ​​For example, the control device 200 acquires information announcing the holding of an event from a server that provides event-related information located on the internet, a cloud network, or the core network of the mobile network 90.

[0026] The control device 200 predicts at least one congested cell from among the multiple cells 10 where sudden congestion will occur, based on event-related information. In the example shown in Figure 1, we will continue the explanation assuming that the control device 200 predicts the central cell 10 as the congested cell based on the event-related information.

[0027] The control device 200 controls the mobile parameters of at least one of the congested cell and surrounding cells so that a user terminal 72 located within the congested cell can easily reside in the surrounding cells. In the example shown in Figure 1, the control device 200 controls the mobile parameters of the central cell 10, which is predicted to be a congested cell, and the other surrounding cells 10 so that a user terminal 72 located within the central cell 10, which is predicted to be a congested cell, can easily reside in the other surrounding cells 10. The control device 200 may control the mobile parameters of only the congested cell. The control device 200 may control the mobile parameters of the congested cell and some of the surrounding cells. The control device 200 may control the mobile parameters of the congested cell and all of the surrounding cells. The control device 200 may control the mobile parameters of only the surrounding cells.

[0028] Controlling the mobile parameters of a congested cell may include changing the mobile parameters of the base station 100 that forms the congested cell. Controlling the mobile parameters of a congested cell may include changing the mobile parameters of a user terminal 72 located within the congested cell. Controlling the mobile parameters of a peripheral cell may include changing the mobile parameters of the base station 100 that forms the peripheral cell.

[0029] Mobile parameters may include at least one of the parameters related to handover and the parameters related to cell reselection.

[0030] The following describes a specific example of controlling parameters related to handover by the control device 200. This example is merely illustrative, and the control of parameters related to handover by the control device 200 may be carried out by methods other than those described herein.

[0031] For example, the control device 200 may change the threshold of an event trigger or the offset value for sending a measurement report to a user terminal 72 located in a congested cell.

[0032] The user terminal 72 transmits a measurement report to the base station 100 based on a measurement configuration specified in advance by the base station 100. This measurement configuration may be the Measurement Configuration notified via RRC Connection Reconfiguration. The base station 100 notifies the user terminal 72 of the measurement configuration, and the base station 100 receives the measurement report from the user terminal 72, allowing the base station to collect data for network optimization and handover. The measurement configuration may include information on the measurement target such as frequency band and cell, conditions for starting the measurement, and conditions for reporting the measurement results.

[0033] The user terminal 72 sends a measurement report to the base station 100 if the measurement results of the radio wave measurement meet the conditions specified in the measurement settings. For example, the measurement settings include information indicating the frequency to be measured, information indicating the cell to be measured, information indicating the beam to be measured, the measurement period, and the threshold of the event trigger for sending the measurement report.

[0034] For example, base station 100 determines whether or not to hand over user terminal 72 based on the received measurement report. Specifically, base station 100 determines whether or not to hand over based on measured values ​​such as RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), and SINR (Signal-to-Interference-plus-Noise Ratio) included in the measurement report.

[0035] Therefore, by changing the threshold of the event trigger that causes the user terminal 72 located in the congested cell to send a measurement report, or by changing the offset value, the base station 100 in the congested cell has more opportunities to receive a measurement report from the user terminal 72 located in the congested cell.

[0036] The control device 200 may change the threshold for determining whether or not the base station 100 will hand over the user terminal 72. Specifically, it may change the threshold for at least one of the base stations 100 in a congested cell and the base stations 100 in a peripheral cell. As a result, the opportunities for the base station 100 to determine whether or not to hand over the user terminal 72 increase, making it easier for the user terminal 72 to be handed over. Hereafter, this situation may be referred to as "making handover easier."

[0037] For example, if the event trigger is an A1 trigger, the control unit 200 changes the threshold value of the A1 trigger to a smaller value. For example, the control unit 200 changes the threshold value of RSRP to a smaller value. For example, the control unit 200 changes the threshold value of RSRQ to a smaller value. This makes it easier for RSRP and other signals from congested cells to exceed the threshold, making it easier for the user terminal 72 to send a measurement report.

[0038] For example, if the event trigger is an A2 trigger, the control unit 200 changes the threshold value of the A2 trigger to be higher. For example, the control unit 200 changes the threshold value of RSRP to be higher. For example, the control unit 200 changes the threshold value of RSRQ to be higher. This makes it easier for RSRP etc. from congested cells to fall below the threshold, making it easier for the user terminal 72 to send a measurement report.

[0039] For example, if the event trigger is an A3 trigger, the control unit 200 modifies the offset values ​​of the congested cell and the surrounding cell to be smaller. For example, the control unit 200 modifies the RSRP offset value to be smaller. For example, the control unit 200 modifies the RSRQ offset value to be smaller. This makes it easier for the A3 trigger to be activated even if the amount by which the RSRP of the surrounding cell exceeds the RSRP of the congested cell is small, and makes it easier for the user terminal 72 to send a measurement report.

[0040] In addition to changing the offset value, the control device 200 may also be modified to reduce the hysteresis value. This reduces the delay between when the offset trigger condition is met and when the handover actually occurs, making the handover easier.

[0041] For example, if the event trigger is an A4 trigger, the control device 200 changes the threshold value of the A4 trigger to a smaller value. For example, the control device 200 changes the threshold value of RSRP to a smaller value. For example, the control device 200 changes the threshold value of RSRQ to a smaller value. This makes it easier for RSRP and other signals from surrounding cells to exceed the threshold, making it easier for the user terminal 72 to send a measurement report.

[0042] For example, if the event trigger is an A5 trigger, the control device 200 changes the RSRP threshold value from the congested cell to an increased value. The control device 200 may also change the RSRP threshold value from the surrounding cell to a decreased value. The control device 200 may change the RSRP threshold value of the congested cell to an increased value and the RSRP threshold value of the surrounding cell to a decreased value. This makes it easier for the user terminal 72 to send measurement reports.

[0043] The control device 200 may change the RSRQ threshold value from congested cells to be higher. The control device 200 may change the RSRQ threshold value from surrounding cells to be lower. The control device 200 may change the RSRQ threshold value from congested cells to be higher and the RSRQ threshold value from surrounding cells to be lower. This makes it easier for the user terminal 72 to send measurement reports.

[0044] In addition to changing the threshold value, the control device 200 may also change the hysteresis value to be smaller. This reduces the delay between when the offset trigger condition is met and when the handover actually occurs, making the handover easier.

[0045] The control device 200 may change the level of the cell's RSRP, etc. For example, the control device 200 may change the value of CIO (Cell Individual Offset). In this case, the frequency band of the cell where the user terminal is located and the surrounding cells may be the same. The control device 200 may change the CIO value of the surrounding cells to a large amount. The control device 200 may change the CIO value of the congested cell to a small amount. This makes it easier for the user terminal 72 to send a measurement report.

[0046] By the control device 200 making the above-mentioned changes to the handover-related parameters, the user terminal 72 becomes more likely to hand over from a congested cell to a surrounding cell compared to doing nothing.

[0047] The control device 200 may instruct the user terminal 72 to specify the surrounding cell to which the handover should take place, in order to facilitate handover from a congested cell to a surrounding cell.

[0048] The following describes a specific example of controlling parameters related to cell reselection by the control device 200. This example is merely illustrative, and the control of parameters related to cell reselection by the control device 200 may be carried out by methods other than those described herein.

[0049] Within a congested cell, there may also be user terminals 72 that are in an idle state. If such user terminals 72 connect to a congested cell during cell reselection, the congestion in the congested cell may worsen. The control device 200 may notify idle user terminals 72 in a congested cell of cell reselection parameters that prioritize surrounding cells over the congested cell. This can suppress the worsening of congestion caused by idle user terminals 72 connecting to a congested cell. Notification of cell reselection parameters may be publicly announced. Notification of cell reselection parameters may be included in the system information. If the cell in which the idle user terminal 72 is located and the surrounding cells are in the same frequency band, notification of cell reselection parameters may be included in the SIB (System Information Block) 3 and publicly announced.

[0050] For example, the control device 200 may control the base station 100 of the congested cell to change the threshold value for re-selecting the same cell that the user terminal 72 was connected to immediately before it became idle. For example, the control device 200 may control the base station 100 of the congested cell to notify it to reduce the value of sIntraSearchP. This makes it less likely for the value of sIntraSearchP to fall below the threshold, making it less likely for the user terminal 72 to start searching for a congested cell.

[0051] For example, the control device 200 may control the base station 100 to change the value of the threshold for re-selecting a cell different from the one the user terminal 72 was connected to immediately before it entered an idle state. For example, the control device 200 may control the base station 100 of a congested cell to notify it to increase the value of sNonIntraSearchP. This makes it easier for the value of sNonIntraSearchP to fall below the threshold, making it easier for the user terminal 72 to start searching for a surrounding cell. In this case, the frequency band of the cell where the user terminal is located and the surrounding cells may be different. The threshold for re-selecting a cell different from the one the user terminal 72 was connected to immediately before it entered an idle state may be announced. This threshold may be included in the system information and announced. This threshold may be included in the SIB5 and announced.

[0052] For example, the control device 200 may control the base station 100 of the congested cell to change a parameter indicating the priority of cell reselection. For example, the control device 200 may control the base station 100 of the congested cell to notify it to reselect a cell different from the congested cell as a priority. For example, the control device 200 may control the base station 100 of the congested cell to notify it to reselect a cell with a lower priority.

[0053] For example, the control device 200 may be modified to reduce the hysteresis value. For example, the control device 200 may be modified to reduce the value of qHyst.

[0054] Figure 2 schematically shows an example of event-related information 30. The example shown in Figure 2 is event-related information 30 disseminated regarding a train accident involving a person. In the example shown in Figure 2, the event-related information 30 is information on social media. The event-related information 30 may include image information. The event-related information 30 may include text information. The event-related information 30 may include audio information.

[0055] Event-related information 30 may include information about the type of social media used. Examples of social media types include Facebook®, X (formerly Twitter®), etc.

[0056] The control device 200 may acquire multiple event-related pieces of information 30. The control device 200 may predict congestion cells based on the multiple event-related pieces of information 30. For example, the control device 200 may use the multiple event-related pieces of information 30 to determine the credibility of the content and use the result of the credibility determination to predict congestion cells. This reduces the risk of making incorrect predictions due to, for example, misinformation.

[0057] The control device 200 may predict congested cells based on the time-series trend of multiple event-related information 30 transmissions. For example, it may predict congested cells based on the number of similar event-related information 30 transmissions per unit time. This allows, for example, the reliability of the truthfulness of the event-related information 30 to be determined, and congested cells to be predicted based on reliable event-related information 30. In this case, the control device 200 may predict the time when congestion occurs in the congested cell. This allows for effective distribution of user terminals 72 from the congested cell to surrounding cells, taking into account the time when congestion occurs.

[0058] In the example shown in Figure 2, the event-related information 30 includes image information 32 and text information 34. In the example shown in Figure 2, the image information 32 is an image of a train car stopped at a station. In the example shown in Figure 2, the text information 34 is "A person was hit by a train on the ABC line between CDE stations and FGH stations. I'm going to be late for my interview. What should I do?" and "February 14, 2025, 12:21". The text information 34 may include information indicating the time when the event-related information 30 was transmitted. For example, the text information 34 may be information showing the relationship between the current time and the time when the event-related information 30 was transmitted. For example, the text information 34 may be "5 minutes ago".

[0059] The control device 200 may estimate the content of the event, the target of the event, the location where the event occurred, the time of the event, etc., based on the event-related information 30. In the example shown in Figure 2, the control device 200 may estimate that the event-related information 30 is information related to the ABC line, based on the image information 32. For example, the control device 200 estimates that the image information 32 contains images of train cars on the ABC line by analyzing the image information 32. For example, the control device 200 obtains features such as the arrangement of windows and doors of the train cars and the patterns and colors of the paint applied to the cars by analyzing the image information 32, and estimates that the image information 32 contains images of train cars on the ABC line based on these features.

[0060] In the example shown in Figure 2, the control device 200 may estimate, based on the character information 34, that the event-related information 30 is information relating to the ABC line, that the event location is a place between CDE station and FGH station, that the type of event is a personal injury accident, and that the time of the event is a time related to 12:21 on February 14, 2025.

[0061] For example, by using information from social media as event-related information 30, the control device 200 can proactively control the area around the congested cell even if congestion occurs due to a sudden event that was not announced in advance.

[0062] If a train accident or other incident involving a person occurs on a particular train line, train service will be temporarily suspended for the duration required to restore service. As a result, stations on that line may experience a sudden influx of people, exceeding normal traffic volume and causing congestion.

[0063] For example, the control device 200 predicts that cells covering stations along the ABC line will be congested cells based on the event-related information 30 shown in Figure 2. The control device 200 may further predict congested cells based on past traffic log data. The control device 200 may also predict congested cells based on the time-series transmission status of multiple event-related information 30. The control device 200 may further predict the time of congestion when it occurs.

[0064] For example, the control device 200 predicts congestion cells based on traffic log data from past accidents involving people on the ABC line. This allows the control device 200 to predict which stations will experience congestion if an accident involving a person occurs on the ABC line. This also allows the control device 200 to predict how long after an accident involving a person occurs on the ABC line congestion will occur.

[0065] For example, the control device 200 estimates the transmission time of the earliest event-related information 30 transmitted among multiple event-related information 30 related to the personal injury accident as the transmission time of the personal injury accident. The control device 200 may also estimate the transmission time of the personal injury accident based on the time-series change in the transmission quantity of multiple event-related information 30 related to the personal injury accident. For example, the control device 200 uses the relationship between the occurrence time of a personal injury accident that occurred in the past and the time-series change in the transmission quantity of event-related information 30 transmitted after the occurrence of the personal injury accident, and applies the time-series change in the transmission quantity of multiple event-related information 30 related to the personal injury accident of interest to this relationship to estimate the occurrence time of the personal injury accident of interest.

[0066] As a result, for example, the control device 200 can estimate the time of an accident involving injuries and how long after the accident the congestion will occur, so it can predict the time when congestion will occur.

[0067] The control device 200 may control the mobile parameters of at least one of the congested cells and surrounding cells before the congestion time. This increases the likelihood of preventing the occurrence of congested cells, and even if congestion does occur, it can delay its occurrence.

[0068] Figure 3 schematically shows an example of event-related information 30. The example shown in Figure 3 is event-related information 30 disseminated about a street speech. In the example shown in Figure 3, the event-related information 30 is information from social media. The main points to be explained in the example shown in Figure 3 are the differences from the example shown in Figure 2.

[0069] In the example shown in Figure 3, image information 32 is an image of a street speech. In the example shown in Figure 3, text information 34 is "The ABC Party is giving a street speech at X Station," and "February 15, 2025, 14:16."

[0070] In the example shown in Figure 3, the control device 200 may estimate that the event-related information 30 is information targeting the ABC Party based on the image information 32. For example, the control device 200 may estimate that the event-related information 30 is information targeting the ABC Party based on image analysis of the image information 32, specifically on the portion of the ABC Party flag included in the image information 32.

[0071] In the example shown in Figure 3, the control device 200 may estimate that the location of the street speech is the plaza in front of X Station by analyzing the image information 32. For example, the control device 200 estimates the location of the street speech based on the arrangement of images of the signs of companies DE, F, G, and H included in the image information 32. In this case, the control device 200 may also perform character analysis on the image information 32.

[0072] Figure 4 schematically shows an example of event-related information 30. The example shown in Figure 4 is event-related information 30 disseminated regarding a festival that is scheduled to be held. In the example shown in Figure 4, the event-related information 30 is information on social media. The main points to be explained about the example shown in Figure 4 are the differences from the examples shown in Figures 2 and 3. In the example shown in Figure 4, the event-related information 30 does not have to be information on social media; it may be other types of information. For example, the event-related information 30 may include information from websites that post information about the event, information provided by companies that provide information about the event, etc.

[0073] The festival in the example shown in Figure 4 does not have to be a large-scale festival; it can be a small to medium-sized festival. In the case of large-scale festivals and other events, measures such as deploying mobile radio vehicles are often taken in advance, but in the case of small to medium-sized festivals, such measures may not be taken. Even in small to medium-sized festivals, congestion can occur suddenly depending on the number of people who gather.

[0074] In the example shown in Figure 4, the image information 32 is an image of information announcing the holding of a festival. In the example shown in Figure 4, the text information 34 is "The ABC Festival is tomorrow, is everyone going?" and "July 26, 2025, 19:36".

[0075] In the example shown in Figure 4, the control device 200 may estimate, based on the image information 32, that the event-related information 30 is information related to the ABC Festival. For example, the control device 200 estimates, based on the portion of the image information 32 that includes the ABC Festival, that the event-related information 30 is information related to the ABC Festival through image analysis of the image information 32.

[0076] In the example shown in Figure 4, the control device 200 may estimate that the festival is held in the central area around ABC Station by analyzing the image information 32. The control device 200 may also estimate that the festival is held on July 27th and July 28th, 2025, by analyzing the image information 32. The control device 200 may obtain this information based on the link destination information identified by the URL (Uniform Resource Locator) contained in the image information 32.

[0077] For example, based on event-related information 30, the control device 200 predicts that congestion will occur in cells covering the central area of ​​ABC Station on July 27th and July 28th, 2025, and predicts these cells as congested cells. The control device 200 may also predict the traffic volume of congested cells. For example, the control device 200 predicts the traffic volume of upcoming ABC Festivals based on log data of traffic volume from past ABC Festivals. For example, the control device 200 predicts the traffic volume of upcoming ABC Festivals based on the amount of event-related information 30 on social media and the amount of reactions to the event-related information 30. Based on the predicted traffic volume, the control device 200 may control the mobile parameters of at least one of the congested cells and surrounding cells.

[0078] The control device 200 may predict the occurrence of congestion cells based, for example, on social media reactions to the event-related information 30 shown in Figure 4. For example, the control device 200 may predict the occurrence of congestion cells based on engagement with the event-related information 30 shown in Figure 4. The control device 200 may predict congestion cells based on at least one of the event-related information 30: reach, impressions, clicks, comments, shares, saves, and followers.

[0079] Reach may be the number of unique users who viewed the event-related information 30. Impressions may be the total number of times the event-related information 30 was displayed. Clicks may be the number of times elements within the event-related information 30, such as links or images, were clicked. Comments may be the number of comments left by users on the event-related information 30. Shares may be the number of times the event-related information 30 was shared by other users. Saves may be the number of times users saved the event-related information 30. Followers may be the number of users who follow the account that posted the event-related information 30.

[0080] Figures 5 to 8 schematically show an example of system 20. In the example shown in Figures 5 to 8, the control device 200 is not described, but in Figures 5 to 8, system 20 is equipped with the same control device 200 as in the example shown in Figure 1. In the example shown in Figures 5 to 8, base stations 102, 104, and 106 are arranged around a railway station, forming cells 12, 14, and 16, respectively. In the example shown in Figures 5 to 8, system 20 includes base stations 102, 104, and 106.

[0081] The example shown in Figure 5 represents the initial state before congestion occurs due to a sudden event. In the example shown in Figure 5, user terminal 72 is located in cell 12, user terminal 74 is located in cell 14, and user terminal 76 is located in cell 16. In the example shown in Figure 5, no congestion is occurring in any of the cells.

[0082] In the drawings of this embodiment, the more user terminal symbols shown, the more user terminals are located at the location of that symbol. In the drawings of this embodiment, due to space limitations, one user terminal symbol may represent multiple user terminals located at the location of that symbol.

[0083] In the example shown in Figure 6, for comparison, we will explain the case where control by the control device 200 is not performed. The example shown in Figure 6 shows the state after the state in Figure 5, in which a group of user terminals 78 is located in cell 12 due to an event that occurred at the position marked with a star in cell 12. For example, the sudden event may be a street speech. As people gather for the event, the group of user terminals 78 is located at the position marked with a star, and the group of user terminals 78 is located in cell 12. In this case, in addition to the user terminals 72 that were already located in cell 12 before the group of user terminals 78 was located in cell 12, the group of user terminals 78 is now located in cell 12, causing congestion in cell 12. In this case, the group of user terminals 78 that was located in cell 12 due to the event is added to the user terminals 72 that were already located in cell 12 before the event occurred, causing congestion in cell 12.

[0084] Therefore, in the state shown in Figure 5, the control device 200 predicts a congested cell from among multiple cells based on the event-related information 30. The control device 200 predicts cell 12 as a congested cell based on the event-related information 30 of the street speech shown in Figure 3. The control device 200 may predict cell 12 as a congested cell based on the event-related information 30 of the street speech predicting that a street speech will be held at the location of the star on cell 12.

[0085] The control device 200 controls the mobile parameters of at least one of cells 12, 14, and 16 so that a user terminal 72 located within cell 12 can more easily reside in surrounding cells 14 and 16, which are the surrounding cells of the congested cell. This makes it easier for a user terminal 72 located in cell 12 to reside in cell 14 or cell 16.

[0086] The example shown in Figure 7 illustrates the state after the state in Figure 5, where the control device 200 has performed the aforementioned control. In the example shown in Figure 7, some of the user terminals 72 that were located in cell 12 are now located in cell 14, and the remaining portion are located in cell 16.

[0087] The control device 200 may predict the traffic volume of a congested cell. Based on the predicted traffic volume, the control device 200 may control the mobile parameters of at least one of the congested cell and surrounding cells. For example, the control device 200 may control the mobile parameters of at least one of the congested cell and surrounding cells so that the more traffic a congested cell has, the easier it is for user terminals located in the congested cell to be located in surrounding cells.

[0088] The example shown in Figure 8 illustrates the state after the state in Figure 7, where a group of user terminals 78 is located in cell 12 following an event that occurred at the location marked with a star within cell 12. In this case, the user terminals 72 that were already located in cell 12 before the group of user terminals 78 arrived in cell 12 have dispersed to surrounding cells before the group of user terminals 78 arrived in cell 12. Therefore, congestion caused by the group of user terminals 78 arriving in cell 12 can be prevented or mitigated.

[0089] In the example shown in Figure 8, the user terminal cluster 78 itself can also be subject to distribution to surrounding cells. For example, a portion of the user terminal cluster 78 may reside in cell 14 or cell 16. For instance, some user terminals from the user terminal cluster 78 that are relatively close to the base station 106 forming cell 16 may reside in cell 16.

[0090] The control device 200 may acquire information regarding the communication of the congested cell. For example, the control device 200 acquires information regarding the communication of the congested cell after controlling the mobile parameters of at least one of the congested cell and surrounding cells. The communication information may be an indicator representing the degree of communication congestion. For example, the communication information may be various KPIs (Key Performance Indicators) that represent communication quality. For example, KPIs may be packet loss rate, latency, throughput, bandwidth utilization rate, and queue length.

[0091] The control device 200 may continuously acquire information regarding the communication of the congested cell and monitor the degree of congestion in the congested cell. The control device 200 may determine the degree of congestion in the congested cell. For example, the control device 200 may determine that the greater the packet loss rate, the greater the degree of congestion. For example, the control device 200 may determine that the greater the latency, the greater the degree of congestion. For example, the control device 200 may determine that the lower the throughput, the greater the degree of congestion. For example, the control device 200 may determine that the greater the bandwidth utilization rate, the greater the degree of congestion. For example, the control device 200 may determine that the greater the queue length, the greater the degree of congestion.

[0092] The control device 200 may control the mobile parameters of at least one of the congested cell and surrounding cells based on the acquired information regarding the communication of the congested cell. For example, if the degree of congestion is increasing, the control device 200 may control the mobile parameters of at least one of the congested cell and surrounding cells to enhance the degree to which user terminals located in the congested cell can easily move to surrounding cells. The control device 200 can acquire KPIs even after starting control, check the distribution status, and further adjust the mobile parameters if congestion is not sufficiently suppressed, thereby enabling more effective congestion suppression.

[0093] For example, if the degree of congestion decreases, the control device 200 controls the mobile parameters of at least one of the congested cells and surrounding cells to mitigate the degree to which user terminals located in a congested cell are more likely to be located in a surrounding cell. For example, if the degree of congestion is below a predetermined threshold, the control device 200 may return at least one of the mobile parameters of the congested cell and surrounding cells to their values ​​before control. The control device 200 continues to acquire KPIs after starting control, checks the distribution status, and further adjusts the mobile parameters if congestion has been sufficiently suppressed, thereby providing a more appropriate communication environment to user terminals.

[0094] Normally, when a user terminal is located within the coverage area of ​​a cell, it can use communication services with higher communication quality by being located within that cell than by being located within a surrounding cell. However, if congestion occurs in that cell, even if there is a certain degree of degradation in communication quality, the user terminal can use services with relatively better communication quality by being located within a surrounding cell than by being located within the congested cell.

[0095] Therefore, as described above, by performing control based on information regarding the communication of congested cells, congestion can be suppressed preventively while adjusting the degree of control according to the actual degree of congestion. This allows, for example, user terminals to be returned from surrounding cells to the congested cells where they should be located, depending on the actual degree of congestion.

[0096] The control device 200 may, after controlling the mobile parameters of at least one of the congested cell and surrounding cells before sudden congestion actually occurs, and if it determines that sudden congestion did not actually occur in the congested cell, return the mobile parameters of at least one of the congested cell and surrounding cells to their pre-control values. This allows the control device to quickly return the user terminal to the cell it should be in by stopping control, for example, if it has mistakenly predicted a congested cell, in accordance with the fact that congestion has not actually occurred.

[0097] The control device 200 may further acquire the latest event-related information 30 after controlling the mobile parameters of at least one of the congested cell and surrounding cells. Based on the acquired latest event-related information 30, the control device 200 may update the congestion cell forecast. Based on the updated congestion cell forecast, the control device 200 may control the mobile parameters of at least one of the congested cell and surrounding cells.

[0098] The control device 200 may determine the accuracy of its congestion cell prediction based, for example, on the amount of similar event-related information 30 transmitted on social media. As the center of an event moves, the group of user terminals 78 causing congestion may also move. In such cases, the control device 200 can predict congestion cells with greater accuracy by updating its prediction based on the latest acquired event-related information 30.

[0099] Figures 9 to 12 schematically show an example of system 20. The examples shown in Figures 9 to 12 will primarily be explained in terms of differences from the examples shown in Figures 5 to 8.

[0100] The example shown in Figure 9 represents the initial state before congestion occurs due to a sudden event. In the example shown in Figure 9, many user terminals 74 are located in cell 14, and cell 14 is already congested. Therefore, if the control device 200 predicts cell 12 as a congested cell and simply controls the system so that user terminals 72 located in cell 12 are more likely to be located in surrounding cells around the congested cell, user terminals 72 may end up in the already congested cell 14. In this case, as shown in the example in Figure 10, cell 14 becomes congested, which is problematic.

[0101] Therefore, the control device 200 predicts the traffic volume of surrounding cells and controls the mobile parameters of at least one of the congested cells and surrounding cells based on the predicted traffic volume of the surrounding cells. The control device 200 may control the mobile parameters of at least one of the congested cells and surrounding cells in a plurality of surrounding cells such that it becomes difficult for user terminals located within the congested cell to be present in the surrounding cell where the predicted traffic volume exceeds a predetermined threshold.

[0102] In the example shown in Figure 9, for example, the control device 200 predicts the traffic volume of cells 14 and 16, and if the traffic volume of cell 14 exceeds a predetermined threshold, it controls the mobile parameters of any of cells 12, 14, and 16 so that the user terminal 72 located in cell 12, which is a congested cell, is less likely to be in cell 14. The control device 200 may also control the mobile parameters of any of cells 12, 14, and 16 so that the user terminal is more likely to be in a surrounding cell other than cell 14.

[0103] In the example shown in Figure 9, for example, the control device 200 predicts the traffic volume of cell 14, and if the traffic volume of cell 14 is greater than a predetermined threshold, it controls the mobile parameters of one of cells 12, 14, and 16 so that the user terminal 72 located in cell 12, which is a congested cell, is more likely to be located in a surrounding cell other than cell 14.

[0104] For example, the control device 200 predicts the traffic volume of cell 16, and if the traffic volume of cell 16 is smaller than a predetermined threshold, it controls the mobile parameters of cell 12, cell 14, and cell 16 so that user terminals 72 located in cell 12, which is a congested cell, are more likely to be located in cell 16. The example shown in Figure 11 shows the state after the state in Figure 9, where the control device 200 has performed the aforementioned control. In the example shown in Figure 11, multiple user terminals 72 that were located in cell 12 are now located in cell 16, rather than cell 14, among multiple surrounding cells.

[0105] For example, the control device 200 may control the mobile parameters of at least one of the congested cells and the surrounding cells based on the traffic amount corresponding to the difference between the traffic amount of the surrounding cells and the traffic amount of the surrounding cells where the surrounding cells are congested.

[0106] The control device 200 may control the mobile parameters of at least one of cells 12 and 14 so that it can accept a number of user terminals 72 corresponding to the difference between the traffic volume at which cell 14 becomes congested and the current traffic volume of cell 14. For example, the control device 200 controls the mobile parameters of at least one of cells 12 and 16 so that it can accept a number of user terminals 72 corresponding to the difference between the traffic volume at which cell 16 becomes congested and the current traffic volume of cell 16. This makes it possible to prevent or suppress congestion in congested cells while suppressing congestion in surrounding cells.

[0107] The example shown in Figure 12 illustrates the state after the state in Figure 11, where a group of user terminals 78 is located in cell 12 following an event that occurred at the location marked with a star within cell 12. In this case, user terminal 72, which was already located in cell 12 before the group of user terminals 78 arrived in cell 12, is located in cell 16 before the group of user terminals 78 arrived in cell 12. Therefore, congestion in cell 14, which was already crowded, can be suppressed, while the congestion caused by the group of user terminals 78 arriving in cell 12 can be prevented or mitigated.

[0108] Figures 13 to 16 schematically show an example of system 20. The examples shown in Figures 13 to 16 will mainly be explained in terms of differences from the examples shown in Figures 5 to 8. The examples shown in Figures 13 to 16 will explain the case in which congestion occurs in an area spanning multiple cells. In the examples shown in Figures 13 to 16, events occurring at the starred locations cause cells 12, 14, and 16 to become congested cells. In the examples shown in Figures 13 to 16, system 20 includes a base station 107 that forms cell 17 outside of cell 12 relative to the starred locations, a base station 108 that forms cell 18 outside of cell 14, and a base station 109 that forms cell 19 outside of cell 16.

[0109] The example shown in Figure 13 represents the initial state before congestion occurs due to a sudden event. In the example shown in Figure 13, congestion occurs across multiple cells: cells 12, 14, and 16. Therefore, distributing user terminals among these multiple cells does not prevent the occurrence of congestion.

[0110] For example, the control device 200 controls the system so that some of the user terminals 72 from cell 12 are located in cell 14, and other parts are located in cell 16. In this case, if a group of user terminals 78 is located in a cell due to people gathering around an event occurring at the star-marked location, even if congestion in cell 12 can be suppressed or prevented, as shown in the example in Figure 14, it may not be possible to suppress or prevent congestion in cells 14 and 16.

[0111] Therefore, the control device 200 controls the mobile parameters of at least one of the congested cells and surrounding cells, for example, to make it easier for user terminals located within a congested cell to reside in surrounding cells located around a congested cell group that includes multiple congested cells. In the example shown in Figure 13, the control device 200 controls the mobile parameters of at least one of cells 12, 14, 16, 17, 18, and 19, which are located around a congested cell group that includes cells 12, 14, and 16, to make it easier for user terminals 72, 74, and 76 to reside in those cells. This makes it easier for user terminals located within a congested cell group to reside in cells other than the congested cells, and if a group of user terminals 78 subsequently resides in a congested cell group, it is possible to prevent or mitigate congestion.

[0112] The example shown in Figure 15 illustrates the state after the state in Figure 13, where the control device 200 has performed the aforementioned control. In the example shown in Figure 15, user terminal 72, which was located in cell 12, is now located in cells 17 and 19; user terminal 74, which was located in cell 14, is now located in cell 18; and user terminal 76, which was located in cell 16, is now located in cell 19.

[0113] The example shown in Figure 16 illustrates the state after the conditions in Figure 15, where, following an event occurring at the asterisked location within cell 12, a group of user terminals 78 resides in cells 12, 14, and 16. In this case, the user terminals that were previously located in a congested cell group are now located in surrounding cells further outside the group, thus preventing or mitigating congestion in the cells within the congested group.

[0114] Figure 17 schematically shows an example of the functional configuration of the control device 200. In Figure 17, the control device 200 includes an acquisition unit 210, a storage unit 220, a prediction unit 230, and a control unit 240. It is not necessarily required that the control device 200 include all of these components.

[0115] The acquisition unit 210 acquires various types of information. For example, the acquisition unit 210 acquires event-related information 30. For example, the acquisition unit 210 acquires the latest event-related information 30. For example, the acquisition unit 210 acquires past event-related information 30. For example, the acquisition unit 210 acquires information regarding the communication of congested cells. The acquisition unit 210 may acquire information regarding the communication of congested cells.

[0116] After the control unit 240 controls the mobile parameters of at least one of the congested cell and surrounding cells, it may acquire information regarding the communication of the congested cell. After the control unit 240 controls the mobile parameters of at least one of the congested cell and surrounding cells, the acquisition unit 210 may further acquire the latest event-related information 30.

[0117] The memory unit 220 stores various types of information. For example, the memory unit 220 stores various types of information acquired by the acquisition unit 210. For example, the memory unit 220 stores event-related information 30 and information related to congestion cell communication. For example, the memory unit 220 stores the latest event information and past event information.

[0118] The prediction unit 230 predicts at least one congested cell from among multiple cells constituting the mobile network 90 that will experience sudden congestion, based on the event-related information 30 acquired by the acquisition unit 210. The prediction unit 230 may predict the congestion time at which the sudden congestion will occur. The prediction unit 230 may predict the traffic volume of the congested cell. The prediction unit 230 may update the prediction of the congested cell based on the latest event-related information 30 acquired by the acquisition unit 210. The prediction unit 230 may predict the traffic volume of surrounding cells.

[0119] The control unit 240 controls the mobile parameters of at least one of the congested cells and surrounding cells so that user terminals located within the congested cell are more likely to be located within the surrounding cells. The control unit 240 may control the mobile parameters of at least one of the congested cells and surrounding cells before the congestion time. The control unit 240 may control the mobile parameters of at least one of the congested cells and surrounding cells based on the traffic volume predicted by the prediction unit 230. The control unit 240 may control the mobile parameters of at least one of the congested cells and surrounding cells so that the greater the traffic volume in the congested cell, the more likely user terminals located within the congested cell are to be located within the surrounding cells.

[0120] The control unit 240 may control the mobile parameters of at least one of the congested cell and surrounding cells based on the communication information of the congested cell acquired by the acquisition unit 210. If the control unit 240 controls the mobile parameters of at least one of the congested cell and surrounding cells before sudden congestion actually occurs, and then determines that sudden congestion did not actually occur in the congested cell, it may return the mobile parameters of at least one of the congested cell and surrounding cells to their values ​​before control.

[0121] The control unit 240 may control the mobile parameters of at least one of the congested cells and surrounding cells based on the congested cell prediction updated by the prediction unit 230. The control unit 240 may control the mobile parameters of at least one of the congested cells and surrounding cells based on the traffic volume of the surrounding cells predicted by the prediction unit 230. The control unit 240 may control the mobile parameters of at least one of the congested cells and surrounding cells in a plurality of surrounding cells such that it is difficult for user terminals located within the congested cell to be present in surrounding cells where the traffic volume predicted by the prediction unit 230 exceeds a predetermined threshold.

[0122] Figure 18 schematically shows an example of the processing flow by the control device 200. Here, we will explain the processing flow from when the control device 200 acquires event-related information 30, to when it uses the event-related information 30 to predict congested cells, and to when it controls the mobile parameters of at least one of the congested cells and surrounding cells.

[0123] In step 102 (sometimes abbreviated as S), the acquisition unit 210 acquires event-related information 30.

[0124] In S104, the storage unit 220 stores the event-related information 30 acquired by the acquisition unit 210 in S102. The storage unit 220 may store multiple event-related information items 30.

[0125] In S106, the prediction unit 230 predicts at least one congested cell from among the multiple cells constituting the mobile network 90 that will experience sudden congestion, based on the event-related information 30 stored in the storage unit 220 in S104. The prediction unit 230 may perform the above prediction at predetermined determination timings. For example, the prediction unit 230 may perform the above prediction at predetermined time intervals. The prediction unit 230 may perform the above prediction according to the amount of event-related information 30 stored in the storage unit 220. For example, the prediction unit 230 may perform the above prediction when a predetermined amount of event-related information 30 has been accumulated in the storage unit 220.

[0126] In S108, the control unit 240 controls the mobile parameters of at least one of the congested cell and surrounding cells so that user terminals located within the congested cell predicted by the prediction unit 230 in S106 are more likely to be located in the surrounding cells.

[0127] Figure 19 schematically shows an example of the hardware configuration of a computer 1200 that functions as a control device 200. A program installed on the computer 1200 can cause the computer 1200 to function as one or more "parts" of the apparatus according to this embodiment, or to cause the computer 1200 to execute operations associated with the apparatus according to this embodiment or such one or more "parts", and / or to cause the computer 1200 to execute a process or a stage of such process according to this embodiment. Such a program may be executed by the CPU 1212 to cause the computer 1200 to execute specific operations associated with some or all of the blocks in the flowcharts and block diagrams described herein.

[0128] The computer 1200 according to this embodiment includes a CPU 1212, RAM 1214, and a graphics controller 1216, which are interconnected by a host controller 1210. The computer 1200 also includes input / output units such as a communication interface 1222, a storage device 1224, a DVD drive, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The DVD drive may be a DVD-ROM drive and a DVD-RAM drive, etc. The storage device 1224 may be a hard disk drive and a solid-state drive, etc. The computer 1200 also includes legacy input / output units such as a ROM 1230 and a keyboard, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0129] The CPU 1212 operates according to the programs stored in the ROM 1230 and RAM 1214, thereby controlling each unit. The graphics controller 1216 acquires the image data generated by the CPU 1212 and stores it in the frame buffer provided in RAM 1214 or within itself, so that the image data is displayed on the display device 1218.

[0130] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive reads programs or data from a DVD-ROM or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0131] The ROM 1230 stores boot programs and / or hardware-dependent programs of the computer 1200, which are executed by the computer 1200 upon activation. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via USB ports, parallel ports, serial ports, keyboard ports, mouse ports, etc.

[0132] The program is provided on a computer-readable storage medium such as a DVD-ROM or IC card. The program is read from the computer-readable storage medium and installed on a storage device 1224, RAM 1214, or ROM 1230, which are examples of computer-readable storage media, and executed by the CPU 1212. The information processing described within these programs is read by the computer 1200, resulting in coordination between the program and the various types of hardware resources described above. The apparatus or method may be configured to realize the operation or processing of information in accordance with the use of the computer 1200.

[0133] For example, when communication is performed between a computer 1200 and an external device, the CPU 1212 may execute a communication program loaded into RAM 1214 and, based on the processing described in the communication program, instruct the communication interface 1222 to perform communication processing. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer area provided in a recording medium such as RAM 1214, storage device 1224, DVD-ROM, or IC card, transmits the read transmission data to the network, or writes received data received from the network to a reception buffer area provided on the recording medium.

[0134] Furthermore, the CPU 1212 may read all or necessary parts of a file or database stored on an external recording medium such as the storage device 1224, a DVD drive (DVD-ROM), or an IC card into the RAM 1214, and perform various types of processing on the data in the RAM 1214. The CPU 1212 may then write the processed data back to the external recording medium.

[0135] Various types of information, such as various types of programs, data, tables, and databases, may be stored on the recording medium and subjected to information processing. The CPU 1212 may perform various types of processing on the data read from RAM 1214, including various types of operations, information processing, conditional judgments, conditional branching, unconditional branching, information retrieval / replacement, etc., as described throughout this disclosure and specified by the program instruction sequence, and write the results back to RAM 1214. The CPU 1212 may also retrieve information in files, databases, etc., within the recording medium. For example, if multiple entries are stored in the recording medium, each having an attribute value of a first attribute associated with an attribute value of a second attribute, the CPU 1212 may search among the multiple entries for an entry that matches the specified condition for the attribute value of the first attribute, read the attribute value of the second attribute stored in that entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies the predetermined condition.

[0136] The program or software module described above may be stored on or near the computer 1200 in a computer-readable storage medium. Alternatively, a recording medium such as a hard disk or RAM provided within a server system connected to a dedicated communication network or the Internet can be used as a computer-readable storage medium, thereby providing the program to the computer 1200 via the network.

[0137] In this embodiment, blocks in the flowchart and block diagram may represent a stage in a process in which an operation is performed or a "part" of a device that has the role of performing an operation. A particular stage and "part" may be implemented by a dedicated circuit, a programmable circuit supplied with computer-readable instructions stored on a computer-readable storage medium, and / or a processor supplied with computer-readable instructions stored on a computer-readable storage medium. The dedicated circuit may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. The programmable circuit may include reconfigurable hardware circuits, such as field-programmable gate arrays (FPGAs) and programmable logic arrays (PLAs), which include logical AND, logical OR, exclusive OR, negated AND, negated OR, and other logical operations, flip-flops, registers, and memory elements.

[0138] A computer-readable storage medium may include any tangible device capable of storing instructions that can be executed by a suitable device, and as a result, a computer-readable storage medium having instructions stored therein will comprise a product that includes instructions that can be executed to create means for performing operations specified in a flowchart or block diagram. Examples of computer-readable storage media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), electrically erasable programmable read-only memory (EEPROM), static random access memory (SRAM), compact disk read-only memory (CD-ROM), digital multipurpose disc (DVD), Blu-ray® disc, memory stick, integrated circuit card, etc.

[0139] Computer-readable instructions may include assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, Java®, C++, and traditional procedural programming languages ​​such as the C programming language or similar programming languages.

[0140] Computer-readable instructions may be provided locally or via a wide area network (WAN) such as a local area network (LAN) or the internet to a processor or programmable circuit of a general-purpose computer, a special-purpose computer, or another programmable data processing device, so that the processor or programmable circuit of the programmable data processing device, such as a computer, may execute the instructions to generate means for performing operations specified in a flowchart or block diagram. Here, the computer may be a PC (personal computer), a tablet computer, a smartphone, a workstation, a server computer, a general-purpose computer, or a special-purpose computer, and may also be a computer system in which multiple computers are connected. Such a computer system in which multiple computers are connected is also called a distributed computing system and is a computer in a broad sense. In a distributed computing system, multiple computers execute a program collectively by each computer executing a part of the program and passing data during program execution between computers as needed.

[0141] Examples of processors include computer processors, central processing units, processing units, microprocessors, digital signal processors, controllers, and microcontrollers. A computer may have one or more processors. In a multiprocessor system with multiple processors, each processor executes a portion of the program, and the processors collectively execute the program by passing program execution data between them as needed. For example, in the execution of multitasks, each of the multiple processors may execute a portion of each task in small chunks by switching tasks at each time slice. In this case, which part of a program each processor executes changes dynamically. Which part of a program each of the multiple processors executes may also be statically determined by multiprocessor-aware programming.

[0142] The invention according to this embodiment makes it possible to prevent or mitigate congestion caused by, for example, the occurrence of sudden events. Consequently, it becomes possible to provide a more stable communication infrastructure. Therefore, it can contribute to achieving at least one of the Sustainable Development Goals (SDGs) Goal 9, "Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation," and Goal 11, "Make cities and human settlements inclusive, safe, resilient and sustainable."

[0143] Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various modifications or improvements can be made to the above embodiments. It will be clear from the claims that such modified or improved forms may also be included in the technical scope of the present invention.

[0144] It should be noted that the execution order of operations, procedures, steps, and stages in the apparatus, systems, programs, and methods shown in the claims, specifications, and drawings is not explicitly stated as "before" or "prior to," and that these can be implemented in any order unless the output of a previous process is used in a later process. Even if the operation flow in the claims, specifications, and drawings is described using phrases such as "first," and "next," for convenience, this does not mean that it is essential to perform the operations in that order. [Explanation of Symbols]

[0145] 10 Cell, 12 Cell, 14 Cell, 16 Cell, 17 Cell, 18 Cell, 19 Cell, 20 System, 30 Event-related information, 32 Image information, 34 Text information, 72 User terminal, 74 User terminal, 76 User terminal, 78 Cluster of user terminals, 90 Mobile network, 100 Base station, 102 Base station, 104 Base station, 106 Base station, 107 Base station, 108 Base station, 109 Base station, 200 Control unit, 210 Acquisition unit, 220 Storage unit, 230 Prediction unit, 240 Control unit, 1200 Computer, 1210 Host controller, 1212 CPU, 1214 RAM, 1216 Graphics controller, 1218 Display device, 1220 Input / Output controller, 1222 Communication interface, 1224 Storage device, 1230 ROM, 1240 Input / Output chip

Claims

1. An acquisition unit that acquires event-related information, including information from multiple social media platforms that were posted chronologically, Based on the information on multiple social media platforms transmitted in the time series acquired by the acquisition unit, the prediction unit determines the reliability of the occurrence of the event, and if the reliability is determined to be high, predicts at least one congestion cell from among multiple cells constituting the mobile network where sudden congestion will occur. A control unit controls the mobile parameters of at least one of the congested cell and the surrounding cells so that a user terminal located within the congested cell can easily be located in the surrounding cells. A control device equipped with the following features.

2. The event-related information includes information on social media that includes at least one of image information and text information relating to the event, The control device according to claim 1, wherein the prediction unit estimates a location related to the event based on at least one of the image information and the character information, and predicts a cell covering the estimated location as the at least one congestion cell.

3. The event-related information includes information on social media including image information, The control device according to claim 1, wherein the prediction unit predicts a cell covering the location where the event predicted based on the image information will occur as the congestion cell.

4. The prediction unit further predicts the congestion time at which the sudden congestion occurs, The control device according to claim 1, wherein the control unit controls the mobile parameters of at least one of the congested cell and the surrounding cell before the congestion time.

5. The prediction unit further predicts the congestion time at which congestion will occur in at least one congestion cell, based on the information transmitted on multiple social media platforms in the time series. The control device according to claim 1, wherein the control unit controls the mobile parameters of at least one of the congested cell and the surrounding cell before the congestion time.

6. The control device according to claim 1, wherein the mobile parameters include at least one of parameters related to handover and parameters related to cell reselection.

7. The prediction unit predicts the traffic volume of the congested cell, The control device according to claim 1, wherein the control unit controls the mobile parameters of at least one of the congested cell and the surrounding cell based on the amount of traffic predicted by the prediction unit.

8. The acquisition unit acquires information regarding the communication of the congested cell after the control unit has controlled the mobile parameters of at least one of the congested cell and the surrounding cell. Based on the information regarding the communication of the congestion cell acquired by the acquisition unit, the control unit The control device according to claim 1, which controls the mobile parameters of at least one of the congested cell and the peripheral cell.

9. The control device according to claim 8, wherein the control unit controls the mobile parameters of at least one of the congested cell and the surrounding cells before the sudden congestion actually occurs, and then, if it determines that the sudden congestion did not actually occur in the congested cell, it returns the mobile parameters of at least one of the congested cell and the surrounding cells to their values ​​before control.

10. The acquisition unit further acquires the latest event-related information after the control unit has controlled the mobile parameters of at least one of the congested cell and the surrounding cell. The prediction unit updates the congestion cell prediction based on the latest event-related information acquired by the acquisition unit. The control device according to claim 1, wherein the control unit controls the mobile parameters of at least one of the congested cell and the surrounding cell based on the prediction of the congested cell updated by the prediction unit.

11. The prediction unit further predicts the traffic volume of the surrounding cells, The control device according to any one of claims 1 to 10, wherein the control unit controls the mobile parameters of at least one of the congested cell and the surrounding cell based on the amount of traffic of the surrounding cell predicted by the prediction unit.

12. The control device according to claim 11, wherein the control unit controls the mobile parameters of at least one of the congested cells and the surrounding cells such that, among the plurality of surrounding cells, the amount of traffic predicted by the prediction unit exceeds a predetermined threshold, making it difficult for the user terminal located within the congested cell to be present in the surrounding cell.

13. A control method performed by a computer, The acquisition stage involves obtaining event-related information, including information disseminated chronologically from multiple social media platforms, and the acquisition of event-related information. Based on the information on multiple social media platforms transmitted in the time series acquired in the acquisition step, the reliability of the occurrence of the event is determined, and if the reliability is determined to be high, a prediction step is made in which at least one congestion cell is predicted from among multiple cells constituting the mobile network in which sudden congestion will occur. A control step of controlling the mobile parameters of at least one of the congested cell and the surrounding cells so that a user terminal located within the congested cell can easily be located in the surrounding cells around the congested cell. A control method comprising:

14. On the computer, The acquisition stage involves obtaining event-related information, including information disseminated chronologically from multiple social media platforms, and the acquisition of event-related information. Based on the information on multiple social media platforms transmitted in the time series acquired in the acquisition step, the reliability of the occurrence of the event is determined, and if the reliability is determined to be high, a prediction step is made in which at least one congestion cell is predicted from among multiple cells constituting the mobile network in which sudden congestion will occur. A control step of controlling the mobile parameters of at least one of the congested cell and the surrounding cells so that a user terminal located within the congested cell can easily be located in the surrounding cells around the congested cell. A program for causing a control method to be implemented.

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