Traffic prediction device, traffic prediction program, and traffic prediction method

Abstract

In a communication system that connects user devices to a network, the accuracy of predicting traffic expected to occur in each area in which user devices exist is improved. [Solution] The present invention relates to a traffic prediction device for predicting traffic generated in a communication system that connects user devices to a network. The traffic prediction device of the present invention is characterized by having an information collection means for collecting information including attribute-specific population information, attribute-specific service usage ratio information, and service bandwidth information in a target area, an information storage means for storing information including population transition information at a target time in the target area, and a calculation processing means for calculating a total bandwidth of traffic generated in the target area based on the information collected by the information collection means and the information stored by the information storage means.

Description

[Technical field]

[0001] The present invention relates to a traffic prediction device, a traffic prediction program, and a traffic prediction method, and can be applied to, for example, traffic prediction in a communication carrier network (for example, a mobile communication network). [Background technology]

[0002] Conventionally, in a mobile communication network (a communication carrier's network), a wireless base station is generally divided into a slave station communication device that communicates with a user device and a master station communication device that controls the slave station communication device. The master station communication device and the slave station communication device are connected by a transmission path such as an optical fiber, and multiple wireless devices are arranged in the wireless base station. The number of wireless devices per wireless base station is determined by the number of mobile terminals that the wireless base station should handle and the amount of traffic that is set by predicting the frequency of use. And since the mobile terminals must be usable even during times of high traffic, the number of wireless devices becomes quite large.

[0003] On the other hand, traffic fluctuates depending on the time of day, with low traffic late at night and early in the morning, and high traffic from daytime to night. In recent years, 5G services have been launched, and high-definition image transmission services and services aimed at advancing cities using digital twin technology have become widespread. In recent years, services have become large-capacity and diverse, and the difference in traffic depending on the time of day, etc. is becoming increasingly large.

[0004] Conventional wireless devices in mobile communication networks are installed assuming high traffic times, and they operate even during low traffic times, resulting in unnecessary power consumption. Therefore, wireless devices in mobile communication networks need to be operated efficiently while satisfying QoS (Quality of Service) and reducing power consumption as much as possible.

[0005] In order to achieve the above-mentioned goal of efficient operation, there are conventional techniques disclosed in Patent Documents 1 and 2 that observe traffic in a communication network, calculate future traffic volume based on the observed data, and determine the communication bandwidth of the network.

[0006] Patent Document 1 describes a method and device for calculating the required bandwidth for mobile communication services. The technology described in Patent Document 1 calculates normalized observed traffic volume for each hour, normalized by the 24-hour average value of the total traffic volume on weekdays or holidays in a certain area, calculates the monthly average, and calculates the maximum traffic volume for a future month, thereby improving the calculation accuracy of the bandwidth facility volume required to achieve QoS.

[0007] Patent Document 2 describes how the accuracy of future traffic predictions can be improved by making predictions taking into account not only traffic information obtained within a communication network but also external factors (weather information and calendar information) as input data. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] JP 2018-037960 A [Patent Document 2] JP 2012-253445 A Summary of the Invention [Problem to be solved by the invention]

[0009] However, in general, in a mobile communication network, the amount of traffic generated by a user device may differ even when compared on a daily basis. In addition, when traffic prediction is performed using the average value of past traffic as in the conventional technology, there is a problem that accurate traffic prediction is difficult when a sudden event or disaster occurs. Furthermore, in general, in a mobile communication network, there is a problem that the amount of traffic generated in each area differs depending on the age composition in the area, but the conventional technology cannot solve such a problem.

[0010] In view of the above problems, there is a demand for a traffic prediction device, a traffic prediction program, and a traffic prediction method that can improve the accuracy of predicting traffic that is expected to occur for each area in which user devices are located in a communication system that connects user devices to a network. [Means for solving the problem]

[0011] The first invention of the present invention is a traffic prediction device that predicts traffic generated in a communication system that connects user devices used by users to a network, characterized in having an information collection means that collects information including attribute-specific population information on the population for each user attribute in a target area, attribute-specific service usage rate information indicating the network service usage rate for each user attribute in the target area, and service bandwidth information on the bandwidth used by the user for each network service, an information holding means that holds information including population trend information on population trends in the target area at a future target time, and a calculation processing means that calculates a total bandwidth of traffic generated in the user devices accessing the network from the target area at the target time based on the information collected by the information collection means and the information held by the information holding means.

[0012] A second traffic prediction program of the present invention is characterized in that it causes a computer mounted on a traffic prediction device that predicts traffic generated in a communication system that connects user devices used by users to a network to function as an information collection means that collects information including attribute-specific population information on the population for each user attribute in a target area, attribute-specific service usage rate information indicating the network service usage rate for each user attribute in the target area, and service bandwidth information on the bandwidth used by the user for each network service, an information storage means that stores information including population trend information on population trends in the target area at a future target time, and a calculation processing means that calculates the total bandwidth of traffic generated in the user devices accessing the network from the target area at the target time based on the information collected by the information collection means and the information stored by the information storage means.

[0013] A third aspect of the present invention is a traffic prediction method performed by a traffic prediction device which predicts traffic generated in a communication system which connects user devices used by users to a network, the traffic prediction device having an information collection means, an information holding means, and a calculation processing means, the information collection means collecting information including attribute-specific population information on the population for each user attribute in a target area, attribute-specific service usage rate information indicating the network service usage rate for each user attribute in the target area, and service bandwidth information on the bandwidth used by the user for each network service, the information holding means holding information including population trend information on population trends in the target area at a future target time, and the calculation processing means calculating a total bandwidth of traffic generated in the user devices accessing the network from the target area at the target time based on the information collected by the information collection means and the information held by the information holding means. Effect of the Invention

[0014] According to the present invention, in a communication system for connecting user devices to a network, it is possible to improve the accuracy of predicting traffic expected to occur for each area in which user devices exist. [Brief description of the drawings]

[0015] [Figure 1] FIG. 2 is a block diagram showing a functional configuration of a traffic prediction unit (traffic prediction device) according to the embodiment. [Diagram 2] FIG. 1 is a diagram illustrating a configuration of a communication system according to an embodiment. [Diagram 3] 11 is a diagram showing an example of information regarding an area of ​​interest that an area / service information collection unit according to the embodiment acquires. FIG. [Figure 4] 1 is a diagram (part 1) showing an example of information acquired about an area of ​​interest by a population transition information collecting unit according to the embodiment. FIG. [Diagram 5] 11 is a flowchart showing an operation of a traffic prediction unit according to the embodiment when performing a traffic prediction process. [Figure 6] FIG. 11 is a diagram (part 1) illustrating a process when a traffic prediction unit according to an embodiment performs a traffic prediction process. [Figure 7] FIG. 2 is a diagram (part 2) showing an example of information acquired about an area of ​​interest by a population transition information collecting unit according to the embodiment. [Figure 8] FIG. 2 is a diagram (part 2) illustrating a process when the traffic prediction unit according to the embodiment performs a traffic prediction process. [Figure 9] FIG. 13 is a diagram showing a configuration of a communication system according to a modified embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] (A) Main embodiment Hereinafter, an embodiment of the traffic prediction device, the traffic prediction program, and the traffic prediction method of the present invention will be described in detail with reference to the drawings. In this embodiment, an example in which the traffic prediction device, the traffic prediction program, and the traffic prediction method of the present invention are applied to a traffic prediction unit will be described.

[0017] (A-1) Configuration of the embodiment FIG. 2 is a block diagram showing the overall configuration of a communication system 1 according to this embodiment.

[0018] The communication system 1 includes N (N is an integer equal to or greater than 1) substation communication devices 20 (20-1 to 20-N) as antenna devices constituting a wireless access network in a mobile communication network (for example, a so-called 5G mobile communication network, etc.), and a master station communication device 10 as a signal processing device that controls each substation communication device 20 to form a wireless access network. The substation communication device 20 transmits and receives wireless signals to and from a mobile terminal TE as a user device used by a user who subscribes to the communication system 1 (mobile communication network). Furthermore, the master station communication device 10 is connected to a core network CN (for example, a core network of a communication carrier). That is, the communication system 1 is configured to connect the mobile terminal TE to the core network CN via the substation communication device 20 and the master station communication device 10. The substation communication devices 20-1 to 20-N are assigned areas (hereinafter, simply referred to as "areas" or "mesh areas") corresponding to a predetermined mesh code, and the communication system 1 performs roaming processing or the like so as to connect (accommodate) a mobile terminal TE present in each assigned area. In this embodiment, the slave station communication devices 20-1 to 20-N are assigned areas A-1 to AN, respectively. In this embodiment, each area corresponds to a 500m mesh code, but the mesh code to which each area corresponds is not limited. In this embodiment, one area (mesh area) is assigned to one slave station communication device 20, but multiple areas (mesh areas) may be assigned to one slave station communication device 20.

[0019] In the following, communication in the direction from the master station communication device 10 side (core network CN side) to the slave station communication device 20 side (mobile terminal TE side) is referred to as "downstream communication," and communication in the direction from the slave station communication device 20 side (mobile terminal TE side) to the master station communication device 10 side (core network CN side) is referred to as "upstream communication."

[0020] As shown in FIG. 1, the master station communication device 10 includes a communication control unit 11 that controls each slave station communication device 20 to perform communication control for forming a wireless access network.

[0021] The communication control unit 11 includes a traffic prediction unit 12 that performs a process (hereinafter referred to as "traffic prediction process") of predicting traffic occurring in each area (each child station communication device 20). In this embodiment, the communication control unit 11 performs communication control (e.g., allocation of bandwidth for upstream communication / downstream communication, etc.) for each area (each child station communication device 20) based on the result of the traffic prediction process by the traffic prediction unit 12. The traffic prediction process performed by the communication control unit 11 will be described later. In addition, the communication process based on the result of the traffic prediction process performed by the communication control unit 11 is not limited, and various traffic controls (e.g., bandwidth control, etc.) may be performed.

[0022] Next, the detailed configuration of the traffic prediction unit 12 will be described.

[0023] The traffic prediction unit 12 performs a process (traffic prediction process) of predicting traffic that will occur in an arbitrary area (hereinafter referred to as an "area of ​​interest") at an arbitrary future time (hereinafter referred to as a "time of interest") based on information that can be collected at the current time t0. Note that in this embodiment, the traffic prediction unit 12 is described as predicting downstream communication traffic, but it may also predict upstream communication traffic. In the following, the times of interest are represented in chronological order as t1, t2, t3, etc.

[0024] Incidentally, the amount of traffic generated in each area differs depending on the population staying there, and the services (network services) that are frequently used also differ depending on the age group of the population staying there. For example, people in their 20s tend to use video viewing and SNS services a lot, while people in their 50s and 60s tend to use email and web browsing services a lot, so external factors such as weather information and calendar information alone are insufficient to accurately predict traffic, making it difficult. In other words, to improve the accuracy of traffic forecasts for a certain area, it is desirable to make traffic forecasts that take into account the population by attributes, such as age, staying in the area.

[0025] Therefore, the traffic prediction unit 12 performs traffic prediction processing taking into consideration the visiting population for each user attribute (e.g., user age or generation) in the area of ​​interest. The "visiting population" is statistical data represented by various values, such as the monthly average value (by weekday / holiday) of the number of people sampled staying at each specified time (e.g., 4:00, 10:00, 14:00, 20:00) and daily values ​​(e.g., the number of people sampled on a specified day corresponding to the date and time when the traffic prediction processing is performed).

[0026] FIG. 1 is a block diagram showing the functional configuration of the traffic prediction unit 12. As shown in FIG.

[0027] The traffic prediction unit 12 has an area and service information collection unit 121 as an information collection means, a population transition information collection unit 122 as an information storage means, a population calculation unit 123, a service bandwidth calculation unit 124, a traffic calculation unit 125, and a traffic prediction output unit 126. Hereinafter, the population calculation unit 123, the service bandwidth calculation unit 124, and the traffic calculation unit 125 will be collectively referred to as the "calculation processing means."

[0028] The traffic prediction unit 12 may be configured, for example, by installing a program (including, for example, the traffic prediction program according to the embodiment) in a computer having a memory and a processor. The traffic prediction unit 12 may be configured using a dedicated computer, or may be configured using a computer in which other functions (programs) are also installed.

[0029] The area and service information collecting unit 121 has a function of collecting information including information on the visiting population by age group (by user attribute) and by time of day for each area (hereinafter referred to as "visiting population information by age group / time"), information on the service usage ratio by age group (hereinafter referred to as "service usage ratio information by age group"), and information on the bandwidth used for each service (hereinafter referred to as "service bandwidth information"). Details of each piece of information collected by the area and service information collecting unit 121 will be described later. The means by which the area and service information collecting unit 121 collects each piece of information is not limited, and may be, for example, obtained from open data (e.g., data that can be downloaded by accessing a specific URL on the Internet), or may be obtained from data from a specific provider (e.g., data transmitted from a server of a specific provider that handles data such as the visiting population for each area). The area and service information collecting unit 121 may also be configured to obtain information registered in advance by a system administrator or the like.

[0030] The population transition information collecting unit 122 performs a process of retaining information on the transition of the visiting population (for example, the rate of increase or decrease, etc.) at a future time of interest (hereinafter referred to as "population transition information"). The population transition information collecting unit 122 performs a process of estimating and retaining the transition of the total population (number of people ratio) for each area (hereinafter referred to as "total population transition information") and the transition of the population ratio by age group (hereinafter referred to as "age-based population ratio transition information") as population transition information through the population transition information retention process. The population transition information collecting unit 122 may retain the total population transition information and the age-based population ratio transition information from, for example, the current visiting population information by age group / time for each area. The population transition information retention process performed by the population transition information collecting unit 122 will be described in detail later.

[0031] The population calculation unit 123 performs a process of calculating the visiting population by age group at a future time of interest for each area (hereinafter referred to as "population calculation process"). The population calculation unit 123 performs the population calculation process based on the visiting population information by age group / time group collected by the area / service information collection unit 121, the result of the population transition information storage process by the population transition information collection unit 122, etc.

[0032] The service bandwidth calculation unit 124 performs a process of calculating the service utilization bandwidth by age group at a time of interest for each area (hereinafter referred to as the "service bandwidth calculation process"). The service bandwidth calculation unit 124 performs the service bandwidth calculation process based on the information acquired by the area and service information collection unit 121 (service utilization ratio information by age group and service bandwidth information) and the result of the population calculation process by the population calculation unit 123, etc.

[0033] The traffic calculation unit 125 performs a process of calculating a predicted value of the traffic volume (total bandwidth used) at a time of interest for each area (hereinafter referred to as a “traffic calculation process”). The traffic calculation unit 125 calculates the predicted value of the traffic volume (total bandwidth) from the result of the service bandwidth calculation unit 124.

[0034] The traffic prediction output unit 126 has a function of outputting the traffic calculation processing result performed by the traffic calculation unit 125. The form and the output destination of the traffic calculation processing result output by the traffic prediction output unit 126 are not limited. For example, when the traffic prediction unit 12 performs the traffic calculation processing for an arbitrary area based on the control from the communication control unit 11, the traffic prediction unit 12 may obtain the current traffic calculation processing result for the area and return it to the traffic prediction unit 12. In addition, the traffic prediction output unit 126 may transmit the traffic calculation processing result to an external server or the like.

[0035] Next, specific examples of information (visiting population information by age group / time, service usage ratio information by age group, and service bandwidth information) collected by the area and service information collecting unit 121 will be described.

[0036] FIG. 3 is a diagram showing an example of information (visitor population information by age group / time at a specific time, service usage ratio information by age group, and service bandwidth information) acquired by the area and service information collecting unit 121 regarding the area of ​​interest.

[0037] FIG. 3(a) shows information on the visiting population by age group and time in area A-1 at an arbitrary time t0.

[0038] Here, the visiting population information by age / time is information showing the population composition by time in each area (population composition by attribute; in this embodiment, population composition by age). The visiting population information by age / time shown in FIG. 3(a) shows the visiting population by age. In this embodiment, as shown in FIG. 3, the user attribute "age" is shown by one of five values, namely, 20s (29 years old or younger), 30s (30 to 39 years old), 40s (40 to 49 years old), 50s (50 to 59 years old), and 60s (60 years old or older). In the following description, the user attribute "age" is shown by one of the above five values, but in the present invention, there is no limitation on what value is used to express the user attribute "age". For example, values ​​such as 10s (19 years old or younger) and 70s (70 years old or older) may be set for the age.

[0039] FIG. 3(b) shows age-specific service usage ratio information at an arbitrary time t0 in area A-1.

[0040] Here, the service usage ratio information by age group is information showing the usage ratio of each service (network service) by age group, as shown in FIG. 3(b).

[0041] In this embodiment, the services are described as being classified into any one of video (e.g., video streaming service), email (e.g., sending and receiving email data with a server), and web browsing (e.g., browsing web pages on the Internet), as shown in Fig. 3. The number and types of the services are not limited to the above three types, and various combinations can be applied.

[0042] The service usage ratio information by age group shown in FIG. 3(b) shows the usage ratio (unit: [%)) of each service by age group. For example, in FIG. 3(b), for people in their 20s, it is [video 50%, email 25%, web browsing 25%] (total 100%). Regarding the service usage ratio information by age group, different data may be applied for each area and each time (for example, each specified time), or uniform data may be applied for each area and each time.

[0043] FIG. 3(c) shows service band information at an arbitrary time t0 in area A-1.

[0044] Here, the service bandwidth information indicates the bandwidth (in [Mbps]) required for each service, as shown in FIG. 3(c). For example, in FIG. 3(c), it is [video: 30 Mbps, email: 5 Mbps, web browsing: 10 Mbps]. The service bandwidth information may use a general value that satisfies QoS. Also, the service bandwidth information may apply different data for each area and each time (for example, each specified time), or may apply uniform data for each area and each time.

[0045] FIG. 4 is a diagram showing an example of population transition information (total population transition information and age-specific population proportion transition information) acquired by the population transition information collecting unit 122 for the area of ​​interest.

[0046] FIG. 4(a) is a diagram showing an example of total population transition information for a focus area at a focus time t1.

[0047] The total population trend information shown in FIG. 4(a) shows the total population at the current time t0 and the total population at time t1, assuming that the time is t1. The total population trend information shown in FIG. 4(a) shows the total population at each time in [%]. For example, if the population information by age / time in the area of ​​interest at time t0 is as shown in FIG. 3(a), the total population at time t0 in the area of ​​interest is 2000 people. If the total population trend information at time t0 is as shown in FIG. 4(a) (t0: 100%, t1: 100%), this indicates that the proportion of the total population is the same at t0 and t1, so the total population at time t1 will also be 2000 people, just like t0.

[0048] FIG. 4(b) is a diagram showing an example of information on transition of population ratio by age group for a focus area at a focus time t1.

[0049] In the information on population percentage trends by age group shown in FIG. 4(a), the population percentage by age group at time t1 is shown in [%]. In the information on population percentage trends by age group shown in FIG. 4(a), it is [20s: 80%, 30s: 10%, 40s: 5%, 50s: 5%, 60s: 0%]. As described above, if the total population of the area of ​​interest at time t1 is 2000 people based on the total population trend information, etc., the population by age group is calculated by multiplying the percentage of each age group in the information on population percentage trends by age group by the total population (2000 people).

[0050] As described above, the population calculation unit 123 of this embodiment can ascertain the visiting population by age group at the time of interest, based on the population transition information acquired from the population transition information collection unit 122. Note that there are no limitations on the specific configuration of the population transition information held by the population transition information collection unit 122 or the method of holding the population transition information, as long as the population calculation unit 123 can hold information that allows it to ascertain the visiting population by age group at the time of interest.

[0051] Next, a specific example of the population transition information storage process performed by the population transition information collection unit 122 will be described.

[0052] For example, the population transition information collecting unit 122 may generate and store population transition information for each designated time of the visiting population sample (for each designated time of the visiting population sample that is the source of the visiting population information by age group / time; for example, 4:00 on weekdays, 10:00 on weekdays, 14:00 on weekdays, 20:00 on weekdays, 4:00 on holidays, 10:00 on holidays, 14:00 on holidays, and 20:00 on holidays) based on the visiting population information by age group / time of the attention area collected by the population transition information collecting unit 122 (information on the visiting population by age group for each time series) and using the population at the current time t0 as a reference (the population at the current time t0 is 100%), and may select population transition information for a designated time corresponding to the date and time of the attention time (for example, a designated time closest to the attention time) and supply it to the population calculation unit 123. Also, for example, the population transition information collecting unit 122 may select a designated time corresponding to the attention time (for example, a designated time closest to the attention time), and generate and store population transition information corresponding to the designated time selected based on the visiting population information by age group / time, etc. Furthermore, for example, the population transition information collecting unit 122 may store population transition information for each area and for each specified time (for example, stored by an operation of a system administrator, etc.) in advance, and may store population transition information for the specified time corresponding to the date and time of the attention time. Furthermore, the population transition information collecting unit 122 may adjust (increase or decrease) each value of the population transition information according to a weather forecast (for example, temperature and weather) at the attention time of the attention area and the contents of the event being held. Also, for example, the population transition information collecting unit 122 may predict future population increases and decreases from population increases and decreases in areas where past torrential rains (heavy rains that fall in a short time in a localized area) have occurred, or may grasp information on the location and date and time of future events to be held (hereinafter referred to as "event holding information") from information on a social networking service (SNS) (for example, information posted on a timeline on an SNS), and may predict future population increases and decreases that will occur in each area based on the grasped event holding information.

[0053] (A-2) Operation of the embodiment Next, a traffic prediction process (a traffic prediction method according to the embodiment) performed by the traffic prediction unit 12 according to the embodiment will be described.

[0054] FIG. 5 is a flowchart showing the operation of the traffic prediction unit 12 when performing traffic prediction processing (processing for predicting traffic occurring in a target area at a target time).

[0055] First, the population calculation unit 123 calculates the total visiting population in the area of ​​interest at the time of interest based on information supplied from the area and service information collection unit 121 and the population transition information collection unit 122 (S101), and further performs a process of calculating the population by age group (population calculation process) (S102). Specifically, the population calculation unit 123 acquires visiting population information by age group / time at the time of interest in the area of ​​interest from the area and service information collection unit 121. In addition, the population calculation unit 123 acquires total population transition information and population ratio transition information by age group at the time of interest in the area of ​​interest from the population transition information collection unit 122. Then, the population calculation unit 123 calculates the total population in the area of ​​interest at the time of interest based on the acquired visiting population information by age group / time and total population transition information. Then, the population calculation unit 123 calculates the visiting population by age group at the time of interest in the area of ​​interest by multiplying each value of the age group population ratio transition information (population ratio by age group) by the total population.

[0056] Next, the service bandwidth calculation unit 124 performs a process (service bandwidth calculation process) of calculating the service usage bandwidth by age group at the time of interest (hereinafter referred to as "service usage bandwidth by age group") based on the information (service usage ratio information by age group and service bandwidth information) acquired from the area and service information collection unit 121 and the result of the population calculation process by the population calculation unit 123 (visiting population by age group) (S103). Specifically, the service bandwidth calculation unit 124 calculates the number of users of each service by age group (hereinafter referred to as "number of service users by age group") by multiplying each value of the service usage ratio information by age group by the visiting population by age group. Then, the service bandwidth calculation unit 124 calculates each value of the service usage bandwidth by age group by multiplying each value of the number of service users by age group by each bandwidth of the service bandwidth information.

[0057] Next, the traffic calculation unit 125 calculates the total bandwidth of the traffic occurring in the attention area at the attention time by summing up the service usage bandwidths by age group calculated by the service bandwidth calculation unit 124, and obtains it as a result of the traffic prediction process. Then, the traffic prediction output unit 126 outputs the result of the traffic prediction process (total bandwidth) in a predetermined manner (S104).

[0058] In the above manner, the traffic prediction unit 12 performs the traffic prediction process.

[0059] Next, a specific example of the process and results of traffic prediction processing when the traffic prediction unit 12 operates according to the flowchart in Fig. 5 will be described. Here, an example of traffic prediction processing at future target times t1 and t2 will be described. Note that the following procedure of traffic prediction (calculation processing) is merely an example, and the present invention is not limited to the following procedure.

[0060] [Traffic prediction processing for time t1] First, a case will be described in which the traffic prediction unit 12 performs a traffic prediction process for traffic that will occur in area A-1 at a future time t1 at time t0. That is, the area of ​​interest here is area A-1.

[0061] Here, it is assumed that the visiting population information by age group / time, service usage ratio information by age group, and service bandwidth information of the attention area A-1 at time t0 are the contents shown in Fig. 3. Also, it is assumed that the total population transition information and population ratio transition information by age group of the attention area A-1 at the attention time t1 are the contents shown in Fig. 4.

[0062] FIG. 6 is a diagram showing a process in which the traffic predicting unit 12, at time t0, performs a process of predicting traffic that will occur in the area A-1 at a future time t1 of interest.

[0063] In step S101, the population calculation unit 123 calculates the total number of people and the visiting population by age group at the target time t1 from the visiting population information by age group / time (FIG. 3(a)), the total population transition information (FIG. 4(a)), and the population ratio transition information by age group (FIG. 4(b)). Here, as shown in FIG. 6(a), the total population at time t1 is 2000×100(%), which is 2000 people. In addition, the population of each age group at time t1 is multiplied by the population ratio by age group, so as shown in FIG. 6(a), it is [20s: 1600 people, 30s: 200 people, 40s: 100 people, 50s: 100 people, 60s: 0 people].

[0064] Next, in step S102, the population calculation unit 123 multiplies the service usage ratio information by age group (FIG. 3(b)) by the result (visiting population by age group) obtained in step S101 to obtain the number of service users by age group at the target time t1 (FIG. 6(b)). Note that here, if the calculation result is a decimal point, the number of users is rounded up to avoid a bandwidth shortage.

[0065] Next, in step S103, the service bandwidth calculation unit 124 multiplies the number of service users by age group (Figure 6(b)) by the corresponding value of the service bandwidth information at time t0 (Figure 3(c)), to obtain the service usage bandwidth by age group (Figure 6(c)).

[0066] Next, in step S104, the traffic calculation unit 125 calculates the total bandwidth (traffic) occurring in the area of ​​interest A-1 at the future time t1 of interest by summing up each bandwidth (bandwidth by age group / service) shown in the service usage bandwidth by age group (FIG. 6(c)). In this case, as shown in FIG. 6(d), the predicted value of the total bandwidth of the traffic occurring in the area of ​​interest A-1 at the future time t1 of interest is 35725 Mbps.

[0067] [Traffic prediction processing for time t2] Next, a case will be described where the traffic predicting unit 12 performs a process of predicting traffic that will occur in the area A-1 at a future time t2 at time t0.

[0068] FIG. 7 is a diagram showing total population transition information and age-specific population ratio transition information at a time of interest t2 in an area of ​​interest A-1.

[0069] FIG. 8 is a diagram showing a process in which the traffic predicting unit 12 predicts traffic that will occur in the area A-1 at a future time of interest t2.

[0070] Then, in step S101, the population calculation unit 123 calculates the total number of people and the visiting population by age group at the target time t2 from the visiting population information by age group / time (FIG. 3(a)), the total population transition information (FIG. 7(a)), and the population ratio transition information by age group (FIG. 7(b)). Here, as shown in FIG. 8(a), the total population at time t2 is 2000×100(%), which is 2000 people. In addition, the population of each age group at time t2 is multiplied by the population ratio by age group, so as shown in FIG. 8(a), it becomes [20s: 0 people, 30s: 100 people, 40s: 100 people, 50s: 200 people, 60s: 1600 people].

[0071] Next, in step S102, the population calculation unit 123 multiplies the service usage ratio information by age group (Figure 3(b)) by the result obtained in step S101 (visiting population by age group) to obtain the number of service users by age group at the time of interest t2 (Figure 8(b)).

[0072] Next, in step S103, the service bandwidth calculation unit 124 multiplies the number of service users by age group (Figure 8(b)) by the corresponding value of the service bandwidth information at time t0 (Figure 3(c)), to obtain the service usage bandwidth by age group (Figure 8(c)).

[0073] Next, in step S104, the traffic calculation unit 125 calculates the total bandwidth (traffic) occurring in the area of ​​interest A-1 at the future time of interest t2 by summing up each bandwidth (bandwidth by age group / service) shown in the service utilization bandwidth by age group (FIG. 8(c)). In this case, as shown in FIG. 8(d), the predicted value of the total bandwidth of the traffic occurring in the area of ​​interest A-1 at the future time of interest t2 is 24760 Mbps.

[0074] [Comparison with conventional traffic prediction processing] Here, a case will be described where the total bandwidth of traffic occurring in the area of ​​interest A-1 at the times of interest t1 and t2 is calculated simply by using the total population of the area of ​​interest A-1, without using the service usage bandwidth by age group (FIGS. 6(c) and 8(c)). Here, the average bandwidth for each service is used to calculate the predicted value of the total bandwidth, as in the conventional technology. In this case, the average bandwidth for each service is (30+5+10) / 3=15Mbps, which is multiplied by the visiting population of 2000 people to obtain 30000Mbps. In other words, when the traffic prediction process is performed at the times of interest t1 and t2 using the conventional technology, the predicted values ​​of the total bandwidth are both 30000Mbps, but since the service usage bandwidth by age group in the area of ​​interest A-1 (FIGS. 6(c) and 8(c)) is not taken into account, there is a high possibility that the accuracy is lower than that of the traffic prediction unit 12 of this embodiment.

[0075] (A-3) Effects of the embodiment According to this embodiment, the following effects can be obtained.

[0076] In the traffic prediction unit 12 of this embodiment, the prediction accuracy can be improved by calculating the service usage bandwidth by age group from the service usage ratio information by age group and predicting the traffic based on the service usage bandwidth by age group. This has the effect of satisfying the QoS in the communication system 1 and suppressing excess power consumption (for example, suppressing an increase in power consumption of each device due to excessive bandwidth allocation).

[0077] (B) Other embodiments The present invention is not limited to the above-described embodiment, and may include modified embodiments such as those exemplified below.

[0078] (B-1) In the above embodiment, the transmission path between the master station communication device 10 and each slave station communication device 20 is not limited, and various transmission paths can be applied. The type of the transmission path between the master station communication device 10 and each slave station communication device 20 is not limited, and may be, for example, various PtP (Point-to-Point) type transmission paths (e.g., various Ethernet (registered trademark) lines and digital leased lines, etc.) or various PtMP (Point-to-Multipoint) type transmission paths (e.g., PON (Passive Optical Network) type connection configuration and branchable digital leased lines, etc.).

[0079] FIG. 9 shows an example of the configuration of a communication system 1A in which a PON type transmission line is applied to the transmission line between the master station communication device 10 and each of the slave station communication devices 20 (20-1 to 20-N).

[0080] In the communication system 1A shown in Fig. 9, a master station communication device 10 and each slave station communication device 20 (20-1 to 20-N) are connected to each other by an optical communication network system 30, which is a PON type transmission path. The optical communication network system 30 has an OLT (Optical Line Terminal) 31 connected to the master station communication device 10, and ONUs (Optical Network Units) 32 (32-1 to 32-N) connected to each slave station communication device 20 (20-1 to 20-N). In the optical communication network system 30, the OLT 31 and each ONU 32 (32-1 to 32-N) are connected to each other by an optical fiber 33, which serves as an optical transmission path branched into N by a splitter 34.

[0081] (B-2) In the above embodiment, an example has been described in which the traffic prediction unit 12 as a traffic prediction device of the present invention is mounted in the master station communication device 10, but there is no limitation on the device in which the traffic prediction unit 12 is arranged. For example, the traffic prediction unit 12 may be configured as an independent traffic prediction device.

[0082] (B-3) In the traffic prediction unit 12 of each of the above embodiments, the concept of age is used as a user attribute, and traffic prediction processing is performed based on the population by age group and the service usage rate thereof, but the applied user attribute is not limited to age, and other concepts may be used. For example, in the traffic prediction unit 12 of each of the above embodiments, the user attributes may be classified based on other attributes such as gender, occupation, etc. (or classified using a combination of multiple user attributes) to perform traffic prediction processing. [Explanation of symbols]

[0083] 1...communication system, 10...master station communication device, 11...communication control unit, 12...traffic prediction unit, 20, 20-1 to 20-N...slave station communication device, 20-1...slave station communication device, 30...optical communication network system, OLT...31, ONU...32-1 to 32-N, 33...optical fiber, 34...splitter, 121...service information collection unit, 122...population trend information collection unit, 123...population calculation unit, 124...service bandwidth calculation unit, 125...traffic calculation unit, 126...traffic prediction output unit, A, A-1 to AN...area, CN...core network, TE...mobile terminal

Claims

1. A traffic prediction device for predicting traffic generated in a communication system for connecting a user device used by a user to a network, comprising: an information collecting means for collecting information including attribute-specific population information on the population for each user attribute in a target area, attribute-specific service usage ratio information indicating the network service usage ratio for each user attribute in the target area, and service bandwidth information on the bandwidth used by the user for each network service; an information storage means for storing information including population transition information regarding a population transition in the area of ​​interest at a future time of interest; a calculation processing means for calculating a total bandwidth of traffic generated in the user devices accessing the network from the target area at the target time based on the information collected by the information collecting means and the information stored in the information storing means; A traffic prediction device comprising:

2. The calculation processing means includes: Calculating the population for each user attribute in the attention area at the attention time based on the attribute-specific population information and the population transition information; determining a user attribute-specific service utilization bandwidth, which is a bandwidth utilized by the user for each user attribute and for each network service in the area of ​​interest at the time of interest, based on the service bandwidth information, the population for each user attribute in the area of ​​interest at the time of interest, and the attribute-specific service utilization ratio information; Calculating the total bandwidth in the area of ​​interest at the time of interest based on the service bandwidth by user attribute and the service bandwidth information 2. The traffic prediction device according to claim 1, wherein:

3. 3. The traffic prediction device according to claim 2, wherein the user attribute is an age group of the user.

4. A computer installed in a traffic prediction device that predicts traffic generated in a communication system that connects a user device used by a user to a network, an information collecting means for collecting information including attribute-specific population information on the population for each user attribute in a target area, attribute-specific service usage ratio information indicating the network service usage ratio for each user attribute in the target area, and service bandwidth information on the bandwidth used by the user for each network service; an information storage means for storing information including population transition information regarding a population transition in the area of ​​interest at a future time of interest; a calculation processing means for calculating a total bandwidth of traffic generated in the user devices accessing the network from the target area at the target time based on the information collected by the information collecting means and the information stored in the information storing means; A traffic prediction program characterized by functioning as a

5. A traffic prediction method performed by a traffic prediction device that predicts traffic generated in a communication system that connects a user device used by a user to a network, comprising: The traffic prediction device includes an information collection means, an information storage means, and a calculation processing means, The information collecting means collects information including attribute-specific population information on a population for each user attribute in a target area, attribute-specific service usage ratio information indicating a network service usage ratio for each user attribute in the target area, and service bandwidth information on a bandwidth used by the user for each network service; The information storage means stores information including population transition information regarding a population transition in the area of ​​interest at a future time of interest, The calculation processing means calculates a total bandwidth of traffic generated in the user devices accessing the network from the attention area at the attention time based on the information collected by the information collecting means and the information stored in the information storing means. A traffic prediction method comprising:

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