Network state estimation device, network state estimation system, and network state estimation method

Abstract

A network state estimating device (100) according to the present disclosure comprises: an RTT acquiring unit (101) that acquires the round-trip-time (RTT) of each of a first received packet and a second received packet that are received via a network; a difference calculating unit (102) that calculates an RTT difference, i.e., the difference between the RTT of the first received packet and the RTT of the second received packet; a filter unit (103) that performs Kalman filtering of the RTT difference by using multiple stages of Kalman filters (1031-1 to 1031-N) connected to each other in series; a threshold value determining unit (104) that determines a threshold value with respect to the output of the final stage of Kalman filter (1031-N) on the basis of the output of the first stage of Kalman filter (1031-1); and a state estimating unit (105) that compares the output of the final stage of Kalman filter (1031-N) with the determined threshold value and that estimates the state of the network on the basis of the comparison result.

Description

[Technical Field]

[0001] The present disclosure relates to a network state estimation device, a network state estimation system, and a network state estimation method. [Background technology]

[0002] In recent years, there has been an increasing demand for remote monitoring or remote control of objects such as robots, machine tools, and cameras. Remote monitoring or remote control is characterized by frequent communication between the operator and the object. Therefore, to properly perform remote monitoring or remote control, it is necessary to estimate the state of the network used for communication in real time and robustly.

[0003] For this reason, technologies have recently been proposed for estimating network conditions in real time and robustly. One example is a technology called GCC (Google Congestion Control) disclosed in Non-Patent Document 1.

[0004] The GCC disclosed in Non-Patent Document 1 takes the RTT (Round-Trip-Time) in the network as input and estimates the queue state (increasing, decreasing, or stable) of the bottleneck link. Hereinafter, the "bottleneck link queue state" will be simply referred to as the "RTT state." At this time, since the RTT fluctuates greatly, the GCC performs smoothing using a Kalman filter. Furthermore, the GCC uses a threshold to estimate whether the RTT state is increasing, decreasing, or stable. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Gaetano Carlucci et al., “Analysis and Design of the Google Congestion Control for Web Real-time Communication (WebRTC)”, Proceedings of the 7th International Conference on Multimedia Systems, May 2016, Article No. 13, Pages 1-12 Summary of the Invention [Problem to be solved by the invention]

[0006] However, although the GCC disclosed in Non-Patent Document 1 can estimate the RTT state at high speed, it has a problem in that the estimation accuracy is not stable.

[0007] The above-mentioned problem will be described below with reference to FIG. Figure 1 shows the results of estimating the RTT state using GCC, taking the sRTT (smoothed RTT) in the network as input. In Figure 1, the horizontal axis represents the packet number of the received packet. The packet with the largest packet number is the most recently received packet.

[0008] In Figure 1, the vertical axis on the left represents sRTT. Here, the RTT of a packet received at time t is RTT_t, and the sRTT of a packet received at time t-1 is sRTT_(t-1). Then, sRTT_t, which is the sRTT of a packet received at time t, is expressed as in Equation 1 below.

number

[0009] In Figure 1, the vertical axis on the right shows the estimated RTT state. State "1" indicates that the RTT is increasing, State "0" indicates that the RTT is stable, and State "-1" indicates that the RTT is decreasing.

[0010] As shown in Figure 1, GCC is able to quickly estimate the RTT state. However, GCC often judges the RTT state as increasing or decreasing even when the RTT is actually stable. As a result, it can be seen that the accuracy of GCC's RTT state estimation is not stable.

[0011] In view of the above-mentioned problems, an object of the present disclosure is to provide a network state estimation device, a network state estimation system, and a network state estimation method that are capable of stabilizing the estimation accuracy of the network state. [Means for solving the problem]

[0012] A network state estimation method according to one aspect includes the steps of: an RTT (Round Trip Time) acquisition step of acquiring an RTT of each of a first received packet and a second received packet received via a network; a difference calculation step of calculating an RTT difference, which is a difference between an RTT of the first received packet and an RTT of the second received packet; a filtering step of smoothing the RTT difference using a plurality of stages of Kalman filters connected in series with each other; a threshold specifying step of specifying a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; and a state estimation step of comparing the output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value and estimating the state of the network based on the comparison result.

[0013] A network state estimation device according to one aspect includes: an RTT acquisition unit that acquires an RTT (Round Trip Time) of each of a first received packet and a second received packet received via a network; a difference calculation unit that calculates an RTT difference that is a difference between an RTT of the first received packet and an RTT of the second received packet; a filter unit that smooths the RTT difference using a plurality of stages of Kalman filters connected in series; a threshold specifying unit that specifies a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; and a state estimation unit that compares the output of a final-stage Kalman filter among the multiple-stage Kalman filters with the specified threshold value and estimates the state of the network based on the comparison result.

[0014] A network state estimation system according to one aspect includes: an RTT acquisition unit that acquires an RTT (Round Trip Time) of each of a first received packet and a second received packet received via a network; a difference calculation unit that calculates an RTT difference that is a difference between an RTT of the first received packet and an RTT of the second received packet; a filter unit that smooths the RTT difference using a plurality of stages of Kalman filters connected in series; a threshold specifying unit that specifies a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; and a state estimation unit that compares the output of a final-stage Kalman filter among the multiple-stage Kalman filters with the specified threshold value and estimates the state of the network based on the comparison result. [Effects of the Invention]

[0015] According to the above-described aspects, it is possible to provide a network state estimation device, a network state estimation system, and a network state estimation method that are capable of stabilizing the estimation accuracy of the network state. [Brief explanation of the drawings]

[0016] [Figure 1] This is a diagram explaining the issues with GCC. [Figure 2] 1 is a diagram illustrating an example of the configuration of a network state estimation device according to a first embodiment. [Figure 3] FIG. 3 is a flowchart illustrating an example of a schematic operation flow of the network state estimation device according to the first embodiment. [Figure 4] 1 is a diagram illustrating an example of the configuration of a network state estimation system according to a first embodiment. [Figure 5] FIG. 10 is a diagram illustrating an example of the configuration of a network state estimation device according to a second embodiment. [Figure 6] FIG. 11 is a diagram showing an example of an sRTT output from an sRTT acquisition unit according to the second embodiment. [Figure 7] FIG. 10 is a diagram illustrating an example of an RTT difference output from a difference calculation unit according to the second embodiment. [Figure 8] FIG. 10 is a diagram illustrating an example of an RTT difference that has been subjected to one stage of smoothing and is output from the first stage Kalman filter according to the second embodiment. [Figure 9] FIG. 10 is a diagram illustrating an example of an RTT difference that has been smoothed in two stages and is output from the final-stage Kalman filter according to the second embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of a threshold value output from a threshold value specifying unit according to the second embodiment. [Figure 11] FIG. 10 is a diagram illustrating an example of an estimation result of an RTT state output from a state estimation unit according to the second embodiment. [Figure 12] FIG. 10 is a diagram showing an example of the results of estimating the RTT state in a mobile network using GCC. [Figure 13]13 is a diagram showing an example of the result of estimating the RTT state in the same mobile network as in FIG. 12 by the state estimating unit according to the second embodiment. FIG. [Figure 14] FIG. 10 is a flowchart illustrating an example of a schematic operation flow of a network state estimation device according to a second embodiment. [Figure 15] FIG. 10 is a diagram illustrating an example of the configuration of a network state estimation device according to a third embodiment. [Figure 16] FIG. 11 is a diagram illustrating an example of a method for calculating a reception interval by a reception interval calculation unit according to the third embodiment. [Figure 17] FIG. 11 is a flowchart illustrating an example of a schematic operation flow of a reception interval calculation unit according to the third embodiment. [Figure 18] 1 is a block diagram showing an example of the hardware configuration of a computer that realizes a network state estimation device according to first, second, and third embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that the following description and drawings have been omitted and simplified as appropriate for clarity of explanation. In addition, in each of the following drawings, the same elements are given the same reference numerals, and duplicate explanations are omitted as necessary. Furthermore, specific numerical values ​​shown below are merely examples to facilitate understanding of the present disclosure, and are not limited thereto.

[0018] <First Embodiment> First, with reference to FIG. 2, an example of the configuration of the network state estimating device 100 according to the first embodiment will be described. As shown in FIG. 2, the network state estimation device 100 according to the first embodiment includes an RTT acquisition unit 101, a difference calculation unit 102, a filter unit 103, a threshold value specification unit 104, and a state estimation unit 105.

[0019] The network state estimation device 100 may be a device that transmits and receives packets itself. In this case, the network state estimation device 100 estimates the state of the network that the network state estimation device 100 uses to transmit and receive packets. Alternatively, the network state estimation device 100 may be a device that is provided separately from other devices that transmit and receive packets. In this case, the network state estimation device 100 estimates the state of the network that the other devices use to transmit and receive packets.

[0020] The RTT acquisition unit 101 acquires the RTT of each of a first received packet and a second received packet received via a network. It is assumed that the first received packet and the second received packet are received in this order. For example, the RTT of the first received packet is the time from when the network state estimation device 100 or another device transmits a transmission packet to when the first received packet, which is a response packet to the transmission packet, is received by the network state estimation device 100 or another device. The RTT may be calculated by any component within the network state estimation device 100, or may be received from an external device.

[0021] The difference calculation unit 102 calculates an RTT difference, which is the difference (that is, gradient) between the RTT of the first received packet and the RTT of the second received packet. The filter unit 103 includes multiple stages of Kalman filters 1031-1 to 1031-N (N is an integer equal to or greater than 2) connected in series with each other. The filter unit 103 smoothes the RTT differences calculated by the difference calculation unit 102 using the multiple stages of Kalman filters 1031-1 to 1031-N.

[0022] The threshold determination unit 104 determines a threshold for the output of the final-stage Kalman filter 1031-N among the multiple-stage Kalman filters 1031-1 to 1031-N, based on the output of the first-stage Kalman filter 1031-1 among the multiple-stage Kalman filters 1031-1 to 1031-N, i.e., the result of performing one-stage smoothing on the above-mentioned RTT difference.

[0023] The state estimation unit 105 compares the output of the final-stage Kalman filter 1031-N among the multi-stage Kalman filters 1031-1 to 1031-N, i.e., the result of performing N-stage smoothing on the above-mentioned RTT difference, with the threshold specified by the threshold specification unit 104, and estimates the network state based on the comparison result. The network state indicates the communication status in the network, for example, the increase / decrease status of the RTT in the network.

[0024] Next, an example of a schematic operation flow of the network state estimating device 100 according to the first embodiment will be described with reference to FIG. As shown in FIG. 3, first, the RTT acquisition unit 101 acquires the RTT of each of the first received packet and the second received packet received via the network (step S11).

[0025] Next, the difference calculation unit 102 calculates the RTT difference, which is the difference between the RTT of the first received packet and the RTT of the second received packet (step S12). Next, the filter unit 103 smoothes the RTT difference calculated by the difference calculation unit 102 using the multi-stage Kalman filters 1031-1 to 1031-N (step S13).

[0026] Next, the threshold value specifying unit 104 specifies a threshold value based on the output of the first-stage Kalman filter 1031-1 of the multi-stage Kalman filters 1031-1 to 1031-N (step S14). Note that step S14 may be performed when smoothing by the first-stage Kalman filter 1031-1 is completed during step S13, without waiting for the completion of step S13.

[0027] Thereafter, the state estimation unit 105 compares the output of the final-stage Kalman filter 1031-N among the multiple-stage Kalman filters 1031-1 to 1031-N with the threshold value identified by the threshold value identification unit 104, and estimates the state of the network based on the comparison result (step S15).

[0028] As described above, according to the first embodiment, the network state estimation device 100 acquires the RTT of each of a first received packet and a second received packet received via a network, and calculates an RTT difference, which is the difference between the RTT of the first received packet and the RTT of the second received packet. The network state estimation device 100 then smoothes the RTT difference using multiple Kalman filters 1031-1 to 1031-N. The network state estimation device 100 then identifies a threshold based on the output of the first-stage Kalman filter 1031-1, compares the output of the final-stage Kalman filter 1031-N with the threshold, and estimates the network state based on the comparison result. In this way, smoothing the RTT difference using the multiple Kalman filters 1031-1 to 1031-N makes it possible to stabilize the estimation accuracy of the network state. As a result, it becomes possible to appropriately perform remote monitoring or remote control using the stabilized estimation result of the network state.

[0029] The RTT acquisition unit 101 may further acquire the sRTT from the RTT of each of the first received packet and the second received packet using the above-described formula 1. In this case, a component subsequent to the RTT acquisition unit 101 may estimate the network state using the sRTT of each of the first received packet and the second received packet.

[0030] Furthermore, the threshold determination unit 104 may calculate a candidate threshold that is a candidate for the threshold at the time of receiving the second received packet based on the threshold at the time of receiving the first received packet and the output of the first-stage Kalman filter 1031-1 that has smoothed the RTT difference, calculate the maximum value among the calculated candidate threshold and a predetermined lower limit value, and determine the calculated maximum value as the threshold at the time of receiving the second received packet.

[0031] The lower limit may also be set based on the scheduling characteristics of the network. For example, the network scheduling characteristics may be the interval between uplink slots allocated to the uplink when a device communicating using TDD (Time Division Duplex) is present in the network. For example, assume that the source of a received packet received by the network state estimation device 100 or another device is a base station communicating using TDD. In this case, the interval between uplink slots is generally longer than the interval between downlink slots allocated to the downlink. Therefore, even if a terminal such as UE (User Equipment) connected to the base station receives a packet to be transmitted to the base station, the terminal may not be able to transmit the packet immediately and may have to wait until the next uplink slot. Therefore, the RTT fluctuates periodically depending on the interval between uplink slots. Therefore, when the source of the received packet is the base station, the lower limit is set based on the interval between uplink slots so as not to fall below the RTT fluctuation.

[0032] Furthermore, the state estimation unit 105 may estimate the increase or decrease in RTT in the network as the state of the network. In addition, the network state estimation device 100 may further include a reception interval calculation unit that calculates the reception interval between the first received packet and the second received packet based on the transmission interval of the transmission packets for the first received packet and the second received packet, the RTT of the first received packet, and the RTT of the second received packet.

[0033] Furthermore, the RTT acquisition unit 101, the difference calculation unit 102, the filter unit 103, the threshold value identification unit 104, and the state estimation unit 105 are not limited to being provided in one device (network state estimation device 100). As shown in Fig. 4, the RTT acquisition unit 101, the difference calculation unit 102, the filter unit 103, the threshold value identification unit 104, and the state estimation unit 105 may be provided in different devices or distributed across the cloud, etc., to configure a network state estimation system 100A.

[0034] <Embodiment 2> Next, a configuration example of a network state estimating device 10 according to a second embodiment will be described with reference to Fig. 5. The second embodiment corresponds to an embodiment that further embodies the first embodiment described above.

[0035] As shown in FIG. 5, the network state estimation device 10 according to the second embodiment includes an sRTT acquisition unit 11, a difference calculation unit 12, a filter unit 13, a threshold value specification unit 14, and a state estimation unit 15.

[0036] The network state estimation device 10 may be a device that transmits and receives packets itself. In this case, the network state estimation device 10 estimates the state of the network that the network state estimation device 10 uses to transmit and receive packets. Alternatively, the network state estimation device 10 may be a device that is provided separately from other devices that transmit and receive packets. In this case, the network state estimation device 10 estimates the state of the network that the other devices use to transmit and receive packets.

[0037] The sRTT acquisition unit 11 acquires the sRTT of each received packet received via the network. The sRTT may be calculated by any component within the network state estimation device 10, or may be received from an external device. For example, when the sRTT acquisition unit 11 calculates the sRTT, the sRTT acquisition unit 11 may first acquire the RTT of each received packet using ping, and then calculate and acquire the sRTT of each received packet from the RTT of each received packet using the above-mentioned Equation 1. However, the method of acquiring the sRTT is not limited to this. The RTT of a received packet is the time from when the network state estimation device 10 or another device transmits a transmitted packet to when the received packet, which is a response packet to the transmitted packet, is received by the network state estimation device 10 or another device. Fig. 6 shows an example of the sRTT output from the sRTT acquisition unit 11. In Fig. 6, the horizontal axis indicates the packet number of the received packet, and the vertical axis indicates the sRTT.

[0038] The difference calculation unit 12 calculates, for each received packet, an RTT difference, which is the difference (that is, gradient) between the sRTT of the received packet and the sRTT of the received packet received before the received packet.

[0039] Fig. 7 shows an example of the RTT difference output from the difference calculation unit 12. In Fig. 7, the horizontal axis indicates the packet number of the received packet, and the vertical axis indicates the RTT difference. Also, on the vertical axis, x_t indicates the sRTT of the received packet received at time t, and x_t-1 indicates the sRTT of the received packet received at time t-1.

[0040] The filter unit 13 includes two-stage Kalman filters 131-1 to 131-2 connected in series. However, the number of stages of the Kalman filters included in the filter unit 13 is not limited to two, and may be three or more. The filter unit 13 smoothes the RTT difference calculated by the difference calculation unit 12 using the two-stage Kalman filters 131-1 to 131-2.

[0041] Fig. 8 shows an example of an RTT differential that has been smoothed in one stage and is output from the first-stage Kalman filter 131-1. Fig. 9 shows an example of an RTT differential that has been smoothed in two stages and is output from the last-stage Kalman filter 131-2. In Figs. 8 and 9, the horizontal axis indicates the packet number of the received packet, and the vertical axis indicates the smoothed RTT differential.

[0042] The threshold value specifying unit 14 specifies a threshold value based on the output of the first-stage Kalman filter 131-1 of the two-stage Kalman filters 131-1 to 131-2, that is, the RTT difference that has been smoothed in one stage.

[0043] Fig. 10 shows an example of thresholds output from the threshold specification unit 14. In Fig. 10, the horizontal axis indicates the packet number of the received packet, and the vertical axis indicates the threshold. As shown in Fig. 10, the threshold is dynamically set for each received packet when the received packet is received. The thresholds are set on both the positive and negative sides, and the positive and negative thresholds are symmetrical values ​​on either side of the axis of threshold "0".

[0044] The state estimation unit 15 compares the output of the final-stage Kalman filter 131-2 of the two-stage Kalman filters 131-1 to 131-2, i.e., the RTT difference that has been smoothed in two stages, with the threshold value specified by the threshold value specification unit 14. Then, based on the comparison result, the state estimation unit 15 estimates the RTT state (increase / decrease status) of the network as the network state. Here, the state estimation unit 15 estimates whether the RTT state is increasing, stable, or decreasing. For example, when the threshold value specification unit 14 specifies a positive threshold and a negative threshold, the state estimation unit 15 estimates the RTT state as increasing if the output of the final-stage Kalman filter 131-2 is greater than the positive threshold, as decreasing if the output is smaller than the negative threshold, and as stable if the output is within the range between the positive threshold and the negative threshold.

[0045] Fig. 11 shows an example of the estimation result of the RTT state output from the state estimation unit 15. In Fig. 11, the horizontal axis indicates the packet number of the received packet, and the vertical axis indicates the estimation result of the RTT state. State "1" indicates that the RTT is increasing, and State "0" indicates that the RTT is stable. Although not shown, State "-1" indicates that the RTT is decreasing.

[0046] The following describes in detail the method for specifying a threshold value by the threshold value specifying unit 14. For comparison, the method for specifying a threshold value by GCC described in Non-Patent Document 1 will be described first.

[0047] In GCC, the threshold at the time of receiving the i-th received packet is defined as γ(t i ) and the threshold at the time of receiving the i-1th received packet is γ(t i-1 ), and the output of the first stage Kalman filter for the i-th received packet is m(t i ) In GCC, since only one stage of Kalman filter is provided, the output of the first stage Kalman filter is the output of the first stage Kalman filter. In GCC, γ(t i ) is specified as shown in Equation 2 below.

number

[0048] Next, a method for specifying a threshold value by the threshold value specifying unit 14 according to the second embodiment will be described. The threshold specifying unit 14 sets a lower limit according to the schedule characteristics of the network and specifies a threshold so that the threshold does not fall below the lower limit. The schedule characteristics of the network are, for example, the interval between uplink slots when there are devices communicating in TDD in the network.

[0049] For example, assume that the source of a packet received by the network state estimation device 10 or another device is a base station communicating using the TDD method. In this case, as described above, the RTT varies periodically depending on the interval between uplink slots.

[0050] Therefore, when the transmission source of the received packet is the above-mentioned base station, the threshold value specifying unit 14 sets the lower limit based on the interval of the uplink slot so that the lower limit does not fall below the amount of RTT fluctuation. tdd Then, the lower limit γ tdd (t i ) to Ttdd Set to.

[0051] Then, the threshold value specifying unit 14 calculates γ(t i ) to identify the

number

[0052] As shown in Equation 3, the threshold value specifying unit 14 first determines k γ The threshold specifying unit 14 calculates a potential threshold that is a candidate for the threshold in the same manner as in Equation 2, except that it uses the above formula, and calculates the maximum value between the calculated potential threshold and the above-mentioned lower limit value. Then, the threshold specifying unit 14 calculates the calculated maximum value as γ(t i ) to identify it.

[0053] Next, an example of the result of estimating the RTT state by the state estimation unit 15 according to the present embodiment 2 will be described. For comparison, an example of the result of estimating the RTT state by GCC described in Non-Patent Document 1 will also be described.

[0054] Fig. 12 shows an example of the result of estimating the RTT state in a certain mobile network using GCC. In the mobile network in Fig. 12, an intentional delay is generated during communication. Fig. 13 shows an example of the result of estimating the RTT state in the same mobile network as Fig. 12 using the state estimation unit 15 according to the second embodiment. In Figs. 12 and 13, the horizontal axis indicates the reception time of a received packet, and the vertical axis on the left and right are the same as in Fig. 1.

[0055] As shown in Figures 12 and 13, in this second embodiment, compared to GCC, it is more robust to sRTT fluctuations, and it can accurately estimate the RTT state (increasing, decreasing, or stable) even at times when the delay is intentionally changed.

[0056] Next, an example of a schematic operation flow of the network state estimating device 10 according to the second embodiment will be described with reference to FIG. As shown in FIG. 14, first, the sRTT acquisition unit 11 acquires the sRTT of each packet received via the network (step S21).

[0057] Next, the difference calculation unit 12 calculates, for each received packet, an RTT difference, which is the difference between the sRTT of that received packet and the sRTT of the received packet received before that received packet (step S22).

[0058] Next, the filter unit 13 smoothes the RTT difference calculated by the difference calculation unit 12 using the two-stage Kalman filters 131-1 to 131-2 (step S23).

[0059] Next, the threshold value specifying unit 14 specifies a threshold value based on the output of the first-stage Kalman filter 131-1 of the two-stage Kalman filters 131-1 to 131-2 (step S24). Note that step S24 may be performed when smoothing by the first-stage Kalman filter 131-1 is completed during step S23, without waiting for the completion of step S23.

[0060] Thereafter, the state estimation unit 15 compares the output of the final-stage Kalman filter 131-2 of the two-stage Kalman filters 131-1 to 131-2 with the threshold value identified by the threshold value identification unit 14, and estimates the RTT state in the network based on the comparison result (step S25).

[0061] As described above, according to the second embodiment, the network state estimation device 10 acquires the sRTT of each received packet received via the network and calculates the RTT difference for each received packet. The network state estimation device 10 then smooths the RTT difference using two-stage Kalman filters 131-1 and 131-2. The network state estimation device 10 then identifies a threshold based on the output of the first-stage Kalman filter 131-1, compares the output of the final-stage Kalman filter 131-2 with the threshold, and estimates the RTT state in the network based on the comparison result. By smoothing the RTT difference using the two-stage Kalman filters 131-1 and 131-2 in this way, it becomes possible to stabilize the estimation accuracy of the RTT state in the network. Furthermore, as a result, it becomes possible to appropriately perform remote monitoring or remote control using the stabilized estimation result of the RTT state in the network.

[0062] Furthermore, according to the second embodiment, the network state estimation device 10 sets a lower limit value of the threshold based on the schedule characteristics of the network, and specifies the maximum value of the potential threshold value and the lower limit value as the threshold value. This allows the threshold value to be specified so as not to fall below the lower limit value. Specifying such a threshold value can also contribute to stabilizing the accuracy of estimating the RTT state.

[0063] <Third Embodiment> Next, with reference to FIG. 15, an example of the configuration of a network state estimating device 10A according to the third embodiment will be described.

[0064] As shown in FIG. 15, a network state estimation device 10A according to the third embodiment differs from the network state estimation device 10 according to the second embodiment in that a reception interval calculation unit 16 is added.

[0065] The reception interval calculation unit 16 calculates the reception interval of the received packets. Hereinafter, with reference to FIG. 16, a method for calculating the reception interval by the reception interval calculation unit 16 will be described in detail.

[0066] The transmission interval of the packets transmitted by the network state estimation device 10 or another device is δ, and the transmission time of the i-th packet is s i The reception time of the i-th received packet, which is a response packet to the i-th transmitted packet, received by the network state estimation device 10 or another device is defined as r i Let's say.

[0067] At this time, the RTT of the i-th received packet is u i is calculated as shown in the following formula 4.

number

number

[0068] Here, when Equation 4 of the RTT is used to transform Equation 5 of the reception interval, the following Equation 6 is obtained.

number

[0069] In this way, the reception interval d i,i+1 is the transmission interval of the transmitted packets, δ, and the RTT of the i-th received packet, u i, and the RTT of the i+1th received packet, u i+1 It can be calculated based on the following.

[0070] Therefore, the reception interval calculation unit 16 calculates the reception interval between the i-th received packet and the i+1-th received packet based on the transmission interval of the transmission packets, the RTT of the i-th received packet, and the RTT of the i+1-th received packet.

[0071] Of these, the transmission interval of the transmission packets is a predetermined setting value, and therefore the reception interval calculation unit 16 stores the transmission interval of the transmission packets in advance. Furthermore, the reception interval calculation unit 16 acquires the RTTs of the i-th and (i+1)-th received packets from the sRTT acquisition unit 11. However, without being limited to this, the reception interval calculation unit 16 may acquire the RTTs of the i-th and (i+1)-th received packets by itself using ping.

[0072] Next, an example of a schematic operation flow of the reception interval calculation unit 16 according to the third embodiment will be described with reference to Fig. 17. Here, it is assumed that the reception interval calculation unit 16 calculates the reception interval between the i-th reception packet and the (i+1)-th reception packet.

[0073] As shown in FIG. 17, first, the reception interval calculation unit 16 acquires the RTTs of the i-th and (i+1)-th received packets from the sRTT acquisition unit 11 (step S31). Thereafter, the reception interval calculation unit 16 calculates the reception interval between the i-th received packet and the (i+1)-th received packet based on the transmission interval of the transmission packets stored in advance and the RTTs of the i-th and (i+1)-th received packets (step S31).

[0074] In addition to performing the operations shown in Fig. 17, the network state estimating device 10A also performs the operations shown in Fig. 14, which are similar to those of the second embodiment described above. The network state estimating device 10A may perform these operations sequentially in any order, or may perform these operations in parallel approximately simultaneously.

[0075] As described above, according to the third embodiment, the network state estimation device 10A calculates the reception interval between the ith received packet and the (i+1)th received packet based on the transmission interval of the transmitted packets and the RTT of the ith and (i+1)th received packets. This makes it possible to calculate the reception interval of the received packets. Therefore, it becomes possible to perform remote monitoring or remote control by taking into consideration not only the RTT state in the network but also the reception interval of the received packets. Furthermore, on the application side, the interval T of the uplink slot is generally received from the base station. tdd Therefore, the base station setting value T tdd By estimating the lower limit of the dynamic threshold γ tdd It is expected that this will optimize the network conditions (RTT conditions) and enable highly accurate estimation. Other effects are the same as those of the second embodiment described above.

[0076] <Hardware Configuration of a Network State Estimation Device According to an Embodiment> Next, with reference to FIG. 18, an example of the hardware configuration of the computer 90 that realizes the network state estimation devices 100, 10, and 10A according to the first, second, and third embodiments will be described.

[0077] 18, a computer 90 includes a processor 91, a memory 92, a storage 93, an input / output interface (input / output I / F) 94, and a communication interface (communication I / F) 95. The processor 91, the memory 92, the storage 93, the input / output interface 94, and the communication interface 95 are connected by a data transmission path for transmitting and receiving data to and from each other.

[0078] The processor 91 is, for example, an arithmetic processing device such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The memory 92 is, for example, a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The storage 93 is, for example, a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a memory card. The storage 93 may also be a memory such as a RAM or a ROM.

[0079] The storage 93 stores programs that realize the functions of the components of the network state estimation devices 100, 10, and 10A. The processor 91 executes each of these programs to realize the functions of the components of the network state estimation devices 100, 10, and 10A. When executing each of the above programs, the processor 91 may read these programs onto the memory 92 before executing them, or may execute them without reading them onto the memory 92. The memory 92 and the storage 93 also serve to realize the storage functions of the network state estimation devices 100, 10, and 10A.

[0080] Furthermore, the above-described program includes a set of instructions (or software code) that, when loaded into a computer, causes the computer to perform one or more functions of the network state estimation device 100, 10, 10A described in the above-described embodiments. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, computer-readable media or tangible storage media include RAM, ROM, flash memory, SSD or other memory technology, compact disc (CD)-ROM, digital versatile disk (DVD), Blu-ray (registered trademark) disc or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may also be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, transitory computer-readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.

[0081] The input / output interface 94 is connected to a display device 941, an input device 942, a sound output device 943, etc. The display device 941 is a device that displays a screen corresponding to drawing data processed by the processor 91, such as an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) display, or a monitor. The input device 942 is a device that accepts operational inputs from an operator, such as a keyboard, a mouse, or a touch sensor. The display device 941 and the input device 942 may be integrated and realized as a touch panel. The sound output device 943 is a device that outputs sound corresponding to audio data processed by the processor 91, such as a speaker.

[0082] The communication interface 95 transmits and receives data to and from an external device. For example, the communication interface 95 communicates with the external device via a wired communication path or a wireless communication path.

[0083] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. For example, the above-described embodiments may be used in combination.

[0084] Furthermore, some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. (Appendix 1) an RTT (Round Trip Time) acquisition step of acquiring an RTT of each of a first received packet and a second received packet received via a network; a difference calculation step of calculating an RTT difference, which is a difference between an RTT of the first received packet and an RTT of the second received packet; a filtering step of smoothing the RTT difference using a plurality of stages of Kalman filters connected in series with each other; a threshold specifying step of specifying a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; a state estimation step of comparing an output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value, and estimating a state of the network based on the comparison result. Network state estimation method. (Appendix 2) In the threshold specifying step, calculating a candidate threshold that is a candidate for the threshold when the second received packet is received, based on the threshold when the first received packet is received and an output of the first-stage Kalman filter that has performed smoothing on the RTT difference; Calculating the maximum value of the calculated possible threshold value and a predetermined lower limit value; specifying the calculated maximum value as the threshold value at the time of receiving the second received packet; 2. The network state estimation method according to claim 1. (Appendix 3) the lower limit is set based on scheduling characteristics of the network; 3. The network state estimation method according to claim 2. (Appendix 4) In the state estimation step, an increase or decrease in the RTT in the network is estimated as the state of the network. 4. A network state estimation method according to any one of appendixes 1 to 3. (Appendix 5) further comprising a receiving interval calculation step of calculating a receiving interval between the first received packet and the second received packet based on a transmission interval of a transmission packet for the first received packet and the second received packet, an RTT of the first received packet, and an RTT of the second received packet; 5. A network state estimation method according to any one of appendixes 1 to 4. (Appendix 6) an RTT acquisition unit that acquires an RTT (Round Trip Time) of each of a first received packet and a second received packet received via a network; a difference calculation unit that calculates an RTT difference that is a difference between an RTT of the first received packet and an RTT of the second received packet; a filter unit that smooths the RTT difference using a plurality of stages of Kalman filters connected in series; a threshold specifying unit that specifies a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; a state estimation unit that compares an output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value and estimates a state of the network based on the comparison result. Network state estimation device. (Appendix 7) The threshold value specifying unit calculating a candidate threshold that is a candidate for the threshold when the second received packet is received, based on the threshold when the first received packet is received and an output of the first-stage Kalman filter that has performed smoothing on the RTT difference; Calculating the maximum value of the calculated possible threshold value and a predetermined lower limit value; specifying the calculated maximum value as the threshold value at the time of receiving the second received packet; 7. A network state estimation device according to claim 6. (Appendix 8) the lower limit is set based on scheduling characteristics of the network; 8. A network state estimation device according to claim 7. (Appendix 9) The state estimation unit estimates, as the state of the network, a state of increase or decrease of the RTT in the network. 9. A network state estimation device according to any one of appendixes 6 to 8. (Appendix 10) further comprising a reception interval calculation unit that calculates a reception interval between the first received packet and the second received packet based on a transmission interval of a transmission packet for the first received packet and the second received packet, an RTT of the first received packet, and an RTT of the second received packet; 10. A network state estimation device according to any one of appendixes 6 to 9. (Appendix 11) an RTT acquisition unit that acquires an RTT (Round Trip Time) of each of a first received packet and a second received packet received via a network; a difference calculation unit that calculates an RTT difference that is a difference between an RTT of the first received packet and an RTT of the second received packet; a filter unit that smooths the RTT difference using a plurality of stages of Kalman filters connected in series; a threshold specifying unit that specifies a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; a state estimation unit that compares an output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value and estimates a state of the network based on the comparison result. Network state estimation system. (Appendix 12) The threshold value specifying unit calculating a candidate threshold that is a candidate for the threshold when the second received packet is received, based on the threshold when the first received packet is received and an output of the first-stage Kalman filter that has performed smoothing on the RTT difference; Calculating the maximum value of the calculated possible threshold value and a predetermined lower limit value; specifying the calculated maximum value as the threshold value at the time of receiving the second received packet; 12. The network state estimation system of claim 11. (Appendix 13) the lower limit is set based on scheduling characteristics of the network; 13. The network state estimation system of claim 12. (Appendix 14) The state estimation unit estimates, as the state of the network, a state of increase or decrease of the RTT in the network. 14. A network state estimation system according to any one of appendixes 11 to 13. (Appendix 15) further comprising a reception interval calculation unit that calculates a reception interval between the first received packet and the second received packet based on a transmission interval of a transmission packet for the first received packet and the second received packet, an RTT of the first received packet, and an RTT of the second received packet; 15. A network state estimation system according to any one of appendices 11 to 14. [Explanation of symbols]

[0085] 100 Network state estimation device 101 RTT acquisition section 102 Difference calculation part 103 Filter section 1031-1~1031-N Kalman filter 104 Threshold determination unit 105 State Estimation Unit 100A Network Status Estimation System 10,10A Network State Estimation Device 11 sRTT acquisition part 12 Difference calculation part 13 Filter section 131-1~131-2 Kalman filter 14 Threshold determination unit 15 State estimation unit 16 Reception interval calculation unit 90 Computer 91 processors 92 memory 93 Storage 94 Input / Output Interface 941 Display device 942 Input Device 943 Sound Output Device 95 Communication Interface

Claims

1. an RTT (Round Trip Time) acquisition step of acquiring an RTT of each of a first received packet received via a network and a second received packet received after the first received packet; a difference calculation step of calculating an RTT difference, which is a difference between an RTT of the first received packet and an RTT of the second received packet; a filtering step of smoothing the RTT difference using a plurality of stages of Kalman filters connected in series with each other; a threshold specifying step of specifying a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; a state estimation step of comparing an output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value, and estimating a state of increase or decrease in the RTT in the network based on the comparison result, Network state estimation method.

2. In the threshold specifying step, calculating a candidate threshold that is a candidate for the threshold when the second received packet is received, based on the threshold when the first received packet is received and an output of the first-stage Kalman filter that has performed smoothing on the RTT difference; Calculating the maximum value of the calculated possible threshold value and a predetermined lower limit value; specifying the calculated maximum value as the threshold value at the time of receiving the second received packet; The network state estimation method according to claim 1 .

3. the lower limit is set based on scheduling characteristics of the network; The network state estimation method according to claim 2 .

4. a reception interval calculation step of calculating a reception interval between the first received packet and the second received packet based on a transmission interval of a transmission packet for the first received packet and the second received packet, an RTT of the first received packet, and an RTT of the second received packet, The network state estimation method according to any one of claims 1 to 3.

5. an RTT acquisition unit that acquires an RTT (Round Trip Time) of each of a first received packet received via a network and a second received packet received after the first received packet; a difference calculation unit that calculates an RTT difference that is a difference between an RTT of the first received packet and an RTT of the second received packet; a filter unit that smoothes the RTT difference using a plurality of stages of Kalman filters connected in series with each other; a threshold specifying unit that specifies a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; a state estimation unit that compares an output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value and estimates a state of increase or decrease in the RTT in the network based on the comparison result, Network state estimation device.

6. The threshold value specifying unit calculating a candidate threshold that is a candidate for the threshold when the second received packet is received, based on the threshold when the first received packet is received and an output of the first-stage Kalman filter that has performed smoothing on the RTT difference; Calculating the maximum value of the calculated possible threshold value and a predetermined lower limit value; specifying the calculated maximum value as the threshold value at the time of receiving the second received packet; The network state estimation device according to claim 5 .

7. the lower limit is set based on scheduling characteristics of the network; The network state estimation device according to claim 6.

8. a reception interval calculation unit that calculates a reception interval between the first reception packet and the second reception packet based on a transmission interval of a transmission packet for the first reception packet and the second reception packet, an RTT of the first reception packet, and an RTT of the second reception packet; The network state estimation device according to any one of claims 5 to 7.

9. an RTT acquisition unit that acquires an RTT (Round Trip Time) of each of a first received packet received via a network and a second received packet received after the first received packet; a difference calculation unit that calculates an RTT difference that is a difference between an RTT of the first received packet and an RTT of the second received packet; a filter unit that smoothes the RTT difference using a plurality of stages of Kalman filters connected in series with each other; a threshold specifying unit that specifies a threshold for an output of a final-stage Kalman filter among the plurality of stages of Kalman filters based on an output of a first-stage Kalman filter among the plurality of stages of Kalman filters; a state estimation unit that compares an output of a final-stage Kalman filter among the plurality of stages of Kalman filters with the specified threshold value and estimates a state of increase or decrease in the RTT in the network based on the comparison result, Network state estimation system.

10. The threshold value specifying unit calculating a candidate threshold that is a candidate for the threshold when the second received packet is received, based on the threshold when the first received packet is received and an output of the first-stage Kalman filter that has performed smoothing on the RTT difference; Calculating the maximum value of the calculated possible threshold value and a predetermined lower limit value; specifying the calculated maximum value as the threshold value at the time of receiving the second received packet; The network state estimation system according to claim 9 .

11. the lower limit is set based on scheduling characteristics of the network; The network state estimation system according to claim 10.

12. a reception interval calculation unit that calculates a reception interval between the first reception packet and the second reception packet based on a transmission interval of a transmission packet for the first reception packet and the second reception packet, an RTT of the first reception packet, and an RTT of the second reception packet; The network state estimation system according to any one of claims 9 to 11.

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