JP2005252707A - Data transmitting method, data transmitting apparatus using same, data receiving apparatus, and data transmission system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method of controlling the transmission of data using the mutual subsidiarity of media, and to provide an apparatus using the method and a system. <P>SOLUTION: An acquisition unit 102 acquires a state parameter from the data receiving apparatus 150 of a transmission destination of data. An evaluation unit 104 calculates a mental measure introduced based on metering psychological approach on the basis of the state parameter. A controller 106 sets the resolution of the image data on the basis of the mental measure. A communication unit 108 reads the image data from an image data storage unit 110, and transmits the image data in the resolution set to the controller 106 to the data receiving apparatus 150. Thus, the data transmitting apparatus 100 can transmit the data in a range proved by a user level QoS using the mutual subsidiarity of the media. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a data transmission technique, and more particularly, to a method for controlling service quality, and an apparatus and system using the method.

With the development of infrastructure such as ADSL (Asymmetric Digital Subscriber Line) and FTTH (Fiber To The Home), high-speed communication services of 1 Mbps to 100 Mbps or more have become available. With such a communication infrastructure in place, services that handle multimedia content that integrates multiple forms of information such as audio and video, for example, are gradually spreading. In general, communication in a network is realized by using various protocols. For this reason, communication packets conforming to various types of protocols are mixed in a single network. Depending on the communication state, for example, a service that handles multimedia content may not be provided with sufficient quality. In such multimedia services, the present inventors have quantitatively demonstrated the mutual complementarity of media that the quality felt by the user can be kept high if the quality of the other media is good even if the quality of the other media is good. (Non-Patent Document 1). The quality of service felt by the user is hereinafter referred to as “user level QoS”.
Shuji Tasaka, 2 others, “A Study on QoS Control Based on User Level QoS”, 2003 IEICE Communication Society Conference

  Although the present inventors have clarified the mutual complementarity of media quantitatively, it has not been applied to an actual communication system.

  The present invention has been made in view of these points, and an object of the present invention is to provide a method for controlling transmission of data using mutual complementarity of media, and an apparatus and system using the method.

  One embodiment of the present invention is a data transmission method. This method evaluates a psychological measure introduced based on a psychometric method to guarantee the user-level service quality during data transmission, and controls the data transmission state based on the evaluation result. .

  According to this aspect, even when a high load occurs on the network, the service quality at the user level can be guaranteed by dynamically controlling the data transmission state using a psychologically supported method.

  The data handled by this data transmission method may be multimedia data. In this case, the data transmission method uses the image included in the multimedia data when the evaluation value of the psychological measure falls below a predetermined threshold value. Data resolution may be reduced.

  Another aspect of the present invention is a data transmission apparatus. The apparatus includes a communication unit for transmitting data, an evaluation unit for evaluating a psychological measure introduced based on a psychometric method to guarantee a user-level service quality during transmission of data, And a control unit that controls a data transmission state based on the evaluation result.

  The data handled by this apparatus may be multimedia data. In this case, when the evaluation value of the psychological measure falls below a predetermined threshold, the control unit determines the resolution of the image data included in the multimedia data. It may be lowered.

  The evaluation unit may evaluate a psychological measure based on a parameter indicating an application level service quality related to data transmission.

  The parameter may relate to a reception state in a device that receives data.

  Yet another embodiment of the present invention is a data receiving apparatus. The apparatus includes a communication unit that receives transmitted data and a control unit that acquires a parameter related to a reception state of the data, and the acquired parameter is transmitted from the communication unit to a data transmission source.

  Yet another embodiment of the present invention is a data transmission system. The system includes a data transmission device and a data reception device, the data transmission device was introduced based on a psychometric method to assure a user-level service quality and a communication unit for transmitting data An evaluation unit that evaluates a psychological measure during data transmission, and a control unit that controls the transmission state of the data based on the evaluation result. The data receiving device receives the transmitted data and is psychological. A communication unit that transmits parameters referred to for evaluation of the scale is provided.

  It should be noted that any combination of the above-described constituent elements and a conversion of the expression of the present invention between a method, an apparatus, a system, a recording medium, a computer program, etc. are also effective as an aspect of the present invention.

  According to the present invention, data can be transmitted while enhancing the user level QoS by utilizing the mutual complementarity of media.

(Chapter 1 Base technology)
An experiment of QoS control using mutual complementarity of media will be described as a premise for constructing a system for performing QoS control utilizing mutual complementarity of media.

1.1 Preface In multimedia communication, there is mutual complementarity of media. This means that even if the quality of a certain medium deteriorates, the user level QoS can be kept high if the quality of other media is good. Non-Patent Document 1 discusses mutual complementarity of media in multimedia transmission from QoS mapping. However, Non-Patent Document 1 assumes a case where a delay according to a normal distribution is given in audio / video transmission, and is not evaluated in an environment in which an actual load affects audio / video transmission.

  In this chapter, first, audio / video transmission in a loaded environment is realized by simulation, and as with Non-Patent Document 1, user level QoS evaluation and QoS mapping from application level QoS are performed. And it proves that mutual complementarity of media exists in this environment. Next, a QoS control method using mutual complementarity of media is proposed, and finally, the effectiveness of the proposed method is verified.

1.2 Proof of mutual complementarity of media In this section, audio / video transmission in a loaded environment is realized through simulation. Then, as in Non-Patent Document 1, user level QoS evaluation is performed. After that, QoS mapping is performed by multiple regression analysis to prove that there is mutual complementarity of media.

1.2.1 Experimental Method FIG. 1 is a diagram showing a simulation model used in the experiment. For the user level QoS evaluation, a simulation model shown in FIG. 1 was constructed using ns. A simulation was conducted to transfer the contents of a tennis match on this network. The audio and video encoding methods are G. Only 711-μlaw and MPEG1 I frames. The transmission MU rate was set to 8 MU / s for audio and 30, 24, 20, 15, 10 MU / s for video. “MU (Media Unit)” is a unit defined for this experiment. In the case of audio, 1 MU is 8 kbit, and in the case of video, 1 MU corresponds to one frame.

  FIG. 2 is a diagram showing specifications of audio data and image data in the model of FIG. When content is transferred according to the specifications shown in FIG. 2, the load transmitting terminal in FIG. 1 generates a 1500-byte fixed-length message including a header as load traffic at an interval according to the exponential distribution to the corresponding load receiving terminal. sent. The five types of video transmission MU rates and the average load amount from the pair of load transmitting terminals to the load receiving terminal are set to five types of 2.00, 2.25, 2.50, 2.75, and 3.00 Mbps. By setting, a total of 5 × 5 = 25 types of evaluation objects were created. In addition, the video transmission MU rate was set to 30 MU / s, and the video created with no load was used as a target for evaluation.

  Next, 15 male students in their 20s who are unskilled in image quality / sound quality evaluation presented 28 types of subjects, including 3 types of evaluation targets for practice and 25 types of actual evaluation targets. Evaluation was made using a five-step disturbance scale. At that time, the reference object was presented once each time the first and seven evaluations were completed. When the presentation time for one evaluation object was 15 seconds, the evaluation time was about 15 minutes per person. Then, the evaluation result (order scale) was converted into a distance scale using the law of category judgment. In this chapter, the converted value is called a psychological measure, which is considered as a user level QoS parameter.

1.2.2 Application Level QoS Evaluation Results FIGS. 3 to 11 show measured application level QoS parameters. These parameters are average values of the results of 15 measurements made by simulation. FIG. 3 is a diagram showing the relationship between the average load amount and the average MU rate of voice in the model of FIG. FIG. 4 is a diagram showing the relationship between the average load amount and the average video MU rate in the model of FIG. 3 and 4, when the average load amount is 2.00 Mbps, the influence of load traffic is not observed for both audio and video. As can be seen from FIG. 2, the amount of traffic combining the average load amount and the audio / video does not exceed the bandwidth of 4 Mbps between the routers, and a sufficient bandwidth for audio / video transfer is secured. It is. Then, when the amount of traffic that combines the average load amount and the audio / video exceeds 4 Mbps, the average MU rate decreases. Accordingly, the higher the video transmission MU rate, the greater the degree of decrease in the average MU rate. Also, the degree of decrease is smaller for audio than for video.

  FIG. 5 is a diagram showing the relationship between the average load amount and the voice MU missing rate in the model of FIG. FIG. 6 is a diagram showing the relationship between the average load amount and the video MU missing rate in the model of FIG. From FIG. 5 and FIG. 6, regarding the MU missing rate, when the average load amount exceeds 2.00 Mbps, MU missing is observed. This is because, as with the average MU rate, whether or not a bandwidth for transferring audio / video is sufficiently secured.

  FIG. 7 is a diagram showing the relationship between the average load amount and the variation coefficient of the voice output interval in the model of FIG. FIG. 8 is a diagram showing the relationship between the average load amount and the variation coefficient of the video output interval in the model of FIG. From FIG. 7 and FIG. 8, the variation coefficient of the output interval increases as the average load amount increases. As the video transmission MU rate increases, the output interval variation coefficient tends to increase.

  FIG. 9 is a diagram showing the relationship between the average load amount and the in-media synchronous mean square error of the sound in the model of FIG. FIG. 10 is a diagram showing the relationship between the average load amount and the in-media synchronous mean square error of the video in the model of FIG. FIG. 11 is a diagram showing the relationship between the average load amount and the inter-media synchronous mean square error in the model of FIG. From FIG. 9 and FIG. 10, the median mean square error tends to increase as the average load increases. From FIG. 11, the inter-media synchronous mean square error increases as the average load amount increases.

1.2.3 User Level QoS Evaluation Results FIG. 12 is a diagram showing the relationship between the average load amount and the psychological evaluation scale value in the model of FIG. From FIG. 12, when the average load amount is 2.00 or 2.25 Mbps, it is recognized that the higher the video transmission MU rate is, the better. This is because the motion of the video is large in the content relaying the tennis game, and the smooth motion of the video is required. Further, when the average load amount is 2.00 or 2.25, the target when the video transmission MU rate is 30 MU / s and the target when the video MU rate is 24 MU / s are recognized as almost the same quality. . From this, it is understood that the improvement in quality cannot be recognized even when the video transmission MU rate is 24 MU / s or more.

  In addition, when the average load amount is 2.50, 2.75, and 3.00 Mbps, it is recognized that the target whose video transmission MU rate is 24, 20, and 15 MU / s is the best. This is because, as the average load amount increases, the audio MU is lost due to congestion when the video transmission MU rate is high. From the above, it is possible to lower the audio MU missing rate by lowering the video transmission MU rate in accordance with the increase in the average load amount, and to improve the psychological scale.

1.2.4 QoS Mapping QoS mapping is performed by multiple regression analysis with psychological measures as dependent variables and application level QoS parameters as independent variables. At that time, in addition to the measured application level QoS parameter, the average load amount considered to be related to the psychological scale is also handled as the application level QoS parameter. FIG. 13 is a diagram showing application level QoS parameters handled as independent variables in the model of FIG. In multiple regression analysis, if the variables used as independent variables are not independent, the problem of multicollinearity arises. However, there is no guarantee that the application level QoS parameters are independent of each other. Therefore, first, the correlation between application level QoS parameters was examined.

FIG. 14 is a diagram showing a correlation coefficient between application level QoS parameters in the model of FIG. From FIG. 14, the application level QoS parameters are classified into the following four groups.
1. T, Ea
2. Rv
3. Lv, Eint, Cv, Ra, La, Ca
4). Ev

  Next, principal component analysis was performed on the application level QoS parameters of FIG. FIG. 15 is a diagram showing a (cumulative) contribution rate indicating how much information each principal component has about 10 application level QoS parameters. FIG. 16 is a diagram showing the principal component load amount of the application level QoS parameter in the model of FIG.

  As a result, the contribution ratio of the first principal component was 75.6, the cumulative contribution ratio to the second principal component was 96.9, and the cumulative contribution ratio to the third principal component was 99.9. Therefore, the first principal component alone is not sufficient, but if it is used up to the second principal component, 96.9% of the information represented by the ten application level QoS parameters, and further up to the third principal component, 99.9% of the information represented by the ten application level QoS parameters can be expressed. Therefore, the third principal component is obtained here. Then, a multiple regression analysis was performed using a psychological scale (hereinafter, the abbreviation symbol is I) as a dependent variable and an application level QoS parameter as an independent variable. At that time, the multiple regression analysis was performed in consideration of the following two cases.

1. When selecting two or three application level QoS parameters from four groups.
2. In FIG. 16, a QoS parameter having a high principal component load amount with each principal component is used as an independent variable.
Of these results, the multiple regression equation with a high degree of freedom adjusted coefficient of determination is shown below.

Results using average load, average audio MU rate, and average video MU rate as independent variables.
I = −1.388L + 0.939Ra + 0.04574Rv−1.116 (1)
Degree of freedom adjusted coefficient of determination: 0.940

A result using the average MU rate of audio, the average MU rate of video, and the synchronous mean square error between media as independent variables.
I = 1.264Ra + 0.03976Rv−0.001002Eint−6.280 (2)
Degree-of-freedom adjusted coefficient of determination: 0.884

-Results of using the coefficient of variation in the output interval of audio, the median mean square error of audio, and the median mean square error of media as independent variables.
I = −8.521Ca + 0.0006428Ea−0.002298Ev (3)
Degree-of-freedom adjusted coefficient of determination: 0.840

The result using the variation coefficient of the audio output interval and the average MU rate of video as independent variables.
I = −7.512Ca + 0.070Rv + 4.076 (4)
Degree-of-freedom adjusted coefficient of determination: 0.927

The result using the average MU rate of audio and the average MU rate of video as independent variables.
I = 1.190Ra + 0.07027Rv−6.929 (5)
Degree-of-freedom adjusted coefficient of determination: 0.838

・ Results using the coefficient of variation of the output interval of audio and the synchronized mean square error of video media as independent variables.
I = −7.734Ca−0.001456Ev + 5.756 (6)
Degree-of-freedom adjusted coefficient of determination: 0.838

  In these multiple regression equations, the coefficient of the parameter relating to audio is larger than that of video. Therefore, it can be seen that audio is more important than video. For example, increasing the average MU rate in equation (1) by 1 MU corresponds to increasing the average MU rate of video by 0.939 / 0.0457 = 20.5 MU. I was able to confirm the sex.

  It can also be seen that the higher the average MU rate for audio and video, the higher the psychological scale. However, if the video transmission MU rate is set high when the average load increases, packet loss occurs due to network congestion, and both the average MU rate for voice and video becomes small.

  In order to obtain the optimal video transmission MU rate for a certain average load, the relationship between the average MU rate of audio and video was examined. First, the average load amount was set in increments of 0.05 Mbps from 2 Mbps to 3 Mbps, and the average output MU rate of video and audio was measured while changing the video transmission MU rate. The measurement was performed 20 times and the average was obtained. FIG. 17 shows an estimated value of a psychological measure obtained by substituting the average load amount and the measured video and audio average output MU rate value into the multiple regression equation (1).

  FIG. 17 is a diagram showing the relationship between the average load amount and the estimated value of the psychological evaluation scale in the model of FIG. As can be seen from FIG. 17, for example, the average load amount is 30 MU / s at about 2.2 Mbps, 24 MU / s at about 2.5 Mbps, 20 MU / s at about 2.8 Mbps, and 15 MU / s at about 3.0 Mbps. Thus, the psychological scale can be kept highest by controlling the transmission MU rate of video.

1.3 Proposal of QoS control method using mutual complementarity of media In this section, we propose a QoS control scheme using mutual complementarity of media proved in the previous section. The proposed QoS control method is based on a multiple regression equation indicating mutual complementarity of media. In the previous section, the application level QoS parameter that increases the degree of freedom adjusted coefficient of determination is used as the independent variable of the multiple regression equation. However, as an independent variable of the multiple regression equation used for QoS control, it is desirable to increase the coefficient of determination of the multiple regression equation and to easily measure and control it. Taking this into consideration, the multiple regression equation was obtained using the audio MU reception rate shown in FIG. 18 and the video MU reception rate shown in FIG. 19 as independent variables. These two types of reception rates may also be defined as application level QoS parameters. The multiple regression equation thus obtained is shown below. Moreover, the estimated value of the psychological scale with respect to the average load calculated from this multiple regression equation is shown in FIG.

I = 5.805Pa + 3.037Pv-4.987 ... (7)
Degree-of-freedom adjusted coefficient of determination: 0.719
Pa: Audio MU reception rate Pv: Video MU reception rate

  From this multiple regression equation, it can be seen that the decrease in the reception rate of the audio MU has a greater influence on the decrease in the estimated value of the psychological measure than the decrease in the reception rate of the video MU. Therefore, even if the reception rate of the video MU is greatly reduced, if the reception rate of the audio MU is slightly increased, the psychological measure can be prevented from being lowered. This property can be used for QoS control for guaranteeing user-level QoS.

  Therefore, a QoS control method using this property is proposed. In the proposed method, when the network is congested, the video transmission MU rate is lowered to prevent the voice MU reception rate from being lowered. Such a video dynamic resolution control method itself has been known for some time, but the conventional method changes the resolution independently of the user level QoS. Therefore, there is no guarantee of what the user level QoS will be. In contrast, the proposed method is greatly different in that the resolution is systematically changed so as to guarantee the user level QoS obtained by the psychometric method.

  An example of a specific method for realizing the proposed method using the above equation is shown below. Two video transmission MU rates of 30 MU / s and 15 MU / s are prepared and switched according to the estimated value of the psychological scale. As a result of preliminary experiments, the threshold value of the estimated value I for changing the video transmission MU rate was set to 3.65. When the estimated value I is less than 3.65, the video transmission MU rate is 15 MU / s, and when it is 3.65 or more, 30 MU / s. Further, based on the result of the preliminary experiment, the transmission MU rate is changed every 10 seconds based on the reception rate of the audio / video MU for the past 10 seconds.

  Here, as a specific example of the proposed method, a case has been described where a multiple regression equation for content relaying a tennis game used in the experimental method of 1.2.1 is used. This formula may not work effectively for different content. Therefore, as a practical application method, it is necessary to classify content into categories such as sports, news, drama, and animation, and obtain a multiple regression equation for each category. And the method of selecting the multiple regression equation used for control according to the content made into object is used.

1.4 Verification of the effectiveness of the proposed method In this section, the user level QoS is continuously evaluated to verify the effectiveness of the proposed method.

1.4.1 Experimental method In order to verify the effectiveness of the proposed method, we conducted a simulation to transmit audio and video over the same network as in Fig. 1. The content to be transmitted is the same as when the user level QoS is evaluated, and the encoding method is also the same. However, the video transmission MU rate when the dynamic resolution control of video is not performed is 30 MU / s. The audio transmission MU rate is 8 MU / s. Further, in order to change the quality of the media with time, the time-varying traffic shown in FIG. 21 is used as load traffic.

  The load traffic volume transmitted to all load transmitting terminals to the corresponding load receiving terminals was changed at 15-second intervals, and transmitted at a CBR (Constant Bit Rate) by UDP. At this time, the load traffic is a 1500-byte IP datagram including a header. While transmitting load traffic, audio / video is transmitted from the media transmitting terminal to the media receiving terminal in the same manner as when the user level QoS evaluation is performed.

  Then, the audio / video output from the media receiving terminal is the target of the user level QoS continuous evaluation. At this time, two evaluation objects were created depending on whether the proposed method was applied. Moreover, what was created in the no-load state was set as a target for evaluation. Note that the quality of media changes with time due to time-varying traffic. Therefore, in the proposed method, application level QoS, which is an independent variable, must be continuously evaluated in order to perform QoS control. Therefore, in the proposed method, an estimated value of a psychological measure is sequentially obtained from an application level QoS parameter by a multiple regression equation, and control is performed based on this value.

  Next, in order to verify the effectiveness of the proposed method, continuous evaluation of user level QoS is performed. The subject sequentially evaluates the quality while looking at the evaluation object whose quality changes with time. The evaluation uses a three-stage disturbance scale method (3: I don't know deterioration, 2: I'm worried about deterioration but it doesn't get in the way, 1: Deterioration is very disturbing). The test subject continuously evaluates by pressing the corresponding keyboard button according to the evaluated quality. The test subjects were 16 students who were unskilled in image quality / sound quality evaluation. Initially, subjects were presented with a reference object, and the practice of evaluation was practiced using the evaluation object for practice. After that, the subjects to whom the proposed method was not applied and the subjects to be evaluated were presented to the subjects. At that time, in order to prevent the bias of data due to the order of presentation, 8 subjects presented from an evaluation object to which the proposed method was not applied, and the remaining 8 subjects presented from an evaluation object to which the proposed method was applied. The presentation time for one evaluation object was 3 minutes, and the total evaluation time per person was about 15 minutes including the teaching of the evaluation method. Then, the evaluation result was converted into a distance scale (psychological scale) using a series category method, and this was used as a user level QoS parameter.

1.4.2 Experimental Results and Discussion FIG. 22 shows psychological measures and average audio / video MU rates from 100 seconds to 140 seconds after the start of playback. It should be noted that the determination criteria are not determined until 100 seconds after the start of reproduction, so the result of this section is not handled. The results after 140 seconds after the start of reproduction were the same as in FIG. RC in FIG. 22 is a result of applying the proposed method, and Ra and Rv indicate the average MU rate of audio / video, respectively.

  From FIG. 22, the psychological scale is higher when the proposed method is applied in most sections than when it is not applied. In particular, in a playback time of 105 seconds from 105 seconds, the loss of audio MUs is suppressed by the proposed method, and the psychological measure is high even if the average MU rate of video is low. From this, it can be seen that even if the average MU rate of the video is lowered and the motion is not smooth, the subject does not feel so much deterioration if the sound is hardly interrupted. However, in the reproduction time from 127 seconds to 10 seconds, there is almost no difference in the psychological scale depending on the presence or absence of the proposed method. This is because the voice was not regarded as important because this section was a quiet scene. Therefore, depending on the scene, there are cases where the mutual complementarity of the media appears prominently or not.

  In the playback time from 116 seconds to 8 seconds, although the average MU rate of audio / video is almost the same, the psychological scale is different. This seems to be because the past psychological scale has an influence on the current psychological scale.

1.5 Conclusion A user-level QoS evaluation was performed for a plurality of video transmission MU rates. Then, a multiple regression analysis was performed using a psychological measure as a dependent variable and an application level QoS parameter as an independent variable. As a result, we proved the existence of mutual complementarity of the media that the psychological scale can be improved by lowering the video transmission MU rate according to the increase of the average load. It was also shown that for some average load, there is a video transmission MU rate that maximizes the psychological measure. Next, we proposed a QoS control method using mutual complementarity of media. Finally, in an environment using time-varying traffic, the effectiveness of the proposed method could be demonstrated by actually performing continuous evaluation of user level QoS.

(Chapter 2 Data transmission system using prerequisite technology)
The actual transmission control using mutual complementarity of media will be described.

(First embodiment)
FIG. 23 is a configuration diagram of the data transmission system 50 according to the first embodiment. The data transmission apparatus 100 evaluates a psychological measure introduced based on a psychological technique during data transmission, and controls the data transmission state based on the evaluation result. The data reception device 150 receives data from the data transmission device 100 via the network 10 and transmits information regarding the reception state to the data transmission device 100. The “information regarding the reception state” may be an application level QoS parameter shown in FIG. 13, or may be a reception rate of audio data and a reception rate of video data. The “information regarding the reception state” is hereinafter simply referred to as “state parameter”. In the present embodiment, it is assumed that video data including audio and images is transmitted as multimedia data transmitted by data transmission apparatus 100, and the audio data reception rate and image data reception rate are transmitted as state parameters. .

  FIG. 24 is an internal block diagram of the data transmission apparatus 100 of FIG. In terms of hardware components, each component of the data transmission apparatus 100 is a CPU, a memory, a program that realizes the components of this figure loaded in the memory, and a storage unit such as a hard disk that stores the program. However, it will be understood by those skilled in the art that there are various modifications in the implementation method and apparatus. Each figure to be described below shows functional unit blocks, not hardware unit configurations.

  The acquisition unit 102 acquires a state parameter from the data reception device 150. For example, this state parameter may be included in a packet transmitted according to an arbitrary protocol using TCP or UDP as a lower layer protocol. The evaluation unit 104 calculates the evaluation value of the psychological measure by substituting the state parameter into the above-described calculation formula. The evaluation unit 104 outputs the evaluation value to the control unit 106. This evaluation value corresponds to the psychological scale I described above. As described above, the psychological scale I has information related to audio data and information related to image data as variables. As the coefficient in this calculation formula, an optimum value may be obtained experimentally and used as appropriate.

  The control unit 106 controls the data transmission state in the communication unit 108 based on the evaluation value and a preset threshold value. The control unit 106 sets the transmission rate of image data and audio data, and instructs the communication unit 108 to transmit the respective data at the transmission rate. In this embodiment, when the user level QoS decreases, the transmission rate of the image data, that is, the resolution of the image data is adjusted without changing the transmission rate of the audio data. For example, the control unit 106 may adjust the spatial resolution by changing the quantization step (quantization coefficient) of the pixel, or may adjust the temporal resolution by changing the number of frames. By reducing the resolution, the data size per frame is reduced, so that the transmission rate can be lowered.

  For example, the control unit 106 sets the resolution of the image data set when the user level QoS is sufficiently high (hereinafter simply referred to as “standard resolution”) and the resolution of the image data set when the user level QoS is low. (Hereinafter simply referred to as “guaranteed resolution”). When the evaluation value falls below the threshold, the control unit 106 sets the guaranteed resolution as the resolution of the image data. When the evaluation value exceeds the threshold value, the control unit 106 sets a standard resolution as the resolution of the image data. In another example, the control unit 106 may hold, for example, a plurality of threshold values and resolutions associated with the respective threshold values, and gradually reduce the resolution of the image data as the evaluation value decreases.

  The communication unit 108 reads the image data from the image data storage unit 110 and transmits the image data to the data receiving device 150 with the resolution set in the control unit 106. The communication unit 108 reads the audio data from the audio data storage unit 112 and transmits the audio data to the data receiving device 150 at the transmission rate set in the control unit 106. For example, standard resolution image data and guaranteed resolution image data are stored in the image data storage unit 110 in advance, and the communication unit 108 converts the image data associated with the resolution designated by the control unit 106 into image data. The data may be read from the storage unit 110 and transmitted to the data receiving device 150. Further, the communication unit 108 may perform image processing on the image data read from the image data storage unit 110 at the time of transmission, generate image data with the resolution designated by the control unit 106, and transmit the image data.

  With such a configuration, it is possible to perform transmission with guaranteed user level QoS based on the psychological method described as the prerequisite technology.

  FIG. 25 is an internal block diagram of the data receiving apparatus 150 of FIG. The communication unit 152 receives image data and audio data from the data transmission apparatus 100. The control unit 154 acquires information regarding the reception state of the image data and audio data received by the communication unit 152, that is, a state parameter. In the present embodiment, the control unit 154 acquires the reception rate of image data and the reception rate of audio data. The reception state notification unit 156 transmits the state parameter acquired by the control unit 154 to the data transmission apparatus 100. Thereby, the data transmission apparatus 100 is notified of the data reception state in the data reception apparatus 150.

  FIG. 26 is a diagram illustrating an example of a sequence at the time of data transmission in the data transmission device 100 and the data reception device 150 in FIG. The data receiving apparatus 150 requests the data transmission apparatus 100 to transmit content (S10). The data transmission apparatus 100 transmits the requested content data to the data receiving apparatus 150 (S12). The data reception device 150 calculates the reception rate of the audio data and the reception rate of the image data as the state parameters (S14), and transmits them to the data transmission device 100 (S16).

  The data transmission apparatus 100 confirms the presence or absence of unsent data, triggered by the acquisition of the state parameter (S18). If there is no unsent data, that is, if the content transmission is completed (N in S18), the process is terminated. When there is untransmitted data (Y in S18), the data transmission device 100 calculates an evaluation value based on the reception rate acquired from the data reception device 150 (S20). When the evaluation value falls below the threshold value (Y in S22), the data transmission apparatus 100 lowers the resolution of the image data (S24) and transmits the next data. If the evaluation value is not below the threshold value (N in S22), the data transmission apparatus 100 sets the resolution of the image data as a standard (S26) and transmits the next data.

(Second Embodiment)
FIG. 27 is a configuration diagram of a data transmission system 52 according to the second embodiment. In the second embodiment, the data transmission device 100 described with reference to FIG. 24 is incorporated in a relay device 30 such as a wireless access point or a router. Configurations denoted by the same reference numerals as those already described in this figure are substantially the same in operation and function as those already described. In this figure, the configuration different from the first embodiment will be mainly described.

  The network 10 is a broadband communication network such as FTTH or ADSL. The content providing device 20 and the relay device 30 are connected to the network 10. In this figure, the relay device 30 is a wireless access point, and is connected to the data receiving device 150 by wireless communication. The content providing device 20 holds content to be transmitted to the data receiving device 150 and transmits the content to the data receiving device 150 when requested by the data receiving device 150.

  The relay device 30 transmits the content received from the content providing device 20 to the data receiving device 150 via the data transmission device 100. The data transmission device 100 incorporated in the relay device 30 stores a content received from the content providing device 20 in the image data storage unit 110 and the audio data storage unit 112 described with reference to FIG. 24 (not shown). Is further provided. As a result, the data transmission device 100 can be used by being incorporated in the relay device 30.

(Third embodiment)
FIG. 28 is an internal configuration diagram of the data transmission apparatus 100 according to the third embodiment. The data transmission apparatus 100 according to the third embodiment inputs live video and audio corresponding to the video from an apparatus such as a television broadcast receiving apparatus or a photographing apparatus, and transmits them. Configurations denoted by the same reference numerals as those already described in this figure are substantially the same in operation and function as those already described. In this figure, the configuration different from the first embodiment will be mainly described.

  The input unit 124 inputs video signals and audio signals in a predetermined format from a device that outputs video signals and audio signals in real time such as a television broadcast receiving device or a photographing device. Then, the input unit 124 outputs the video signal to the image data generation unit 120 and outputs the audio signal to the audio data generation unit 122. After capturing the video signal, the image data generation unit 120 generates image data with the resolution designated by the control unit 106. The audio data generation unit 122 generates audio data at a predetermined sampling rate based on the audio signal. The communication unit 108 transmits the image data and audio data generated by the image data generation unit 120 and the audio data generation unit 122 to the data receiving device 150. With this configuration, the data transmission apparatus 100 can transmit audio data corresponding to live image data while enhancing the user level QoS by utilizing mutual complementarity.

  The present invention has been described based on the embodiments. This embodiment is an exemplification, and it will be understood by those skilled in the art that various modifications can be made to combinations of the respective constituent elements and processing processes, and such modifications are also within the scope of the present invention. is there. The following are examples of such modifications.

  The evaluation unit 104 described with reference to FIG. 24 may be provided in the data reception device 150 in FIG. That is, the data reception device 150 may calculate an evaluation value based on the state parameter and output the evaluation value to the data transmission device 100. Further, the data transmission apparatus 100 may control the data transmission state based on the evaluation value. For example, the data reception device 150 further includes an evaluation unit that calculates an evaluation value based on the state parameter acquired by the control unit 154 in FIG. The reception state notification unit 156 in FIG. 25 notifies the data transmission apparatus 100 of the evaluation value. On the other hand, the acquisition unit 102 in FIG. 24 receives the evaluation value from the data receiving device 150, and the control unit 106 controls the data transmission state based on the evaluation value and a preset threshold value. Similarly, the evaluation unit 104 described with reference to FIG. 28 may also be provided in the data reception device 150. At this time, the control unit 106 in FIG. 28 instructs the resolution to the image data generation unit 120 based on the evaluation value supplied from the acquisition unit 102 in FIG.

It is a figure which shows the simulation model used for experiment. It is a figure which shows the specification of the audio | voice data and image data in the model of FIG. It is a figure which shows the relationship between the average load amount and the audio | voice average MU rate in the model of FIG. It is a figure which shows the relationship between the average load amount and the average MU rate of a video in the model of FIG. It is a figure which shows the relationship between the average load amount in the model of FIG. It is a figure which shows the relationship between the average load amount in the model of FIG. 1, and the MU loss rate of a video. It is a figure which shows the relationship between the average load amount in the model of FIG. 1, and the variation coefficient of the audio | voice output interval. It is a figure which shows the relationship between the average load amount in the model of FIG. 1, and the variation coefficient of the output interval of a video. It is a figure which shows the relationship between the average load amount in the model of FIG. It is a figure which shows the relationship between the average load amount in the model of FIG. 1, and the synchronous average square error in the media of a video. It is a figure which shows the relationship between the average load amount in the model of FIG. 1, and the synchronous average square error between media. It is a figure which shows the relationship between the average load in the model of FIG. 1, and a psychological evaluation scale value. It is a figure which shows the application level QoS parameter handled as an independent variable in the model of FIG. It is a figure which shows the correlation coefficient between the application level QoS parameters in the model of FIG. It is a figure which shows the relationship between the number of the main components in the model of FIG. 1, and a cumulative contribution rate. It is a figure which shows the main component load amount of the application level QoS parameter in the model of FIG. It is a figure which shows the relationship between the average load in the model of FIG. 1, and the estimated value of a psychological evaluation scale. It is a figure which shows the relationship between the average load amount in the model of FIG. 1, and the reception rate of the audio | voice MU. It is a figure which shows the relationship between the average load amount and the receiving rate of video MU in the model of FIG. It is a figure which shows the relationship between the average load in the model of FIG. 1, and the estimated value of a psychological scale. It is a figure which shows the relationship between the reproduction | regeneration time and load amount in the model of FIG. It is a figure which shows the relationship between the reproduction time in the model of FIG. 1, a psychological scale, and the average MU rate of an audio | voice and a video. 1 is a configuration diagram of a data transmission system according to a first embodiment. FIG. It is an internal block diagram of the data transmission apparatus of FIG. It is an internal block diagram of the data receiver of FIG. It is a figure which shows an example of the sequence at the time of the data transmission in the data transmission apparatus and data receiver of FIG. It is a block diagram of the data transmission system which concerns on 2nd Embodiment. It is an internal block diagram of the data transmission apparatus which concerns on 3rd Embodiment.

Explanation of symbols

  10 network, 12 wireless section, 20 content providing device, 30 relay device, 50 data transmission system, 100 data transmission device, 102 acquisition unit, 104 evaluation unit, 106 control unit, 108 communication unit, 110 image data storage unit, 112 audio Data storage unit, 120 Image data generation unit, 122 Audio data generation unit, 124 Input unit, 150 Data reception device, 152 Communication unit, 154 Control unit, 156 Reception state notification unit

Claims (9)

  It is characterized by evaluating the psychological measure introduced based on the psychometric method to guarantee the user-level service quality during data transmission and controlling the data transmission state based on the evaluation result. Data transmission method.   2. The method according to claim 1, wherein the data is multimedia data, and when the evaluation value of the psychological measure falls below a predetermined threshold value, the resolution of the image data included in the multimedia data is reduced. A data transmission method characterized by the above. A communication unit for transmitting data;
An evaluation unit that evaluates psychological measures introduced during the transmission of data, based on a psychometric method to guarantee user-level service quality;
A control unit for controlling the transmission state of data based on the evaluation result;
A data transmission device comprising:   4. The apparatus according to claim 3, wherein the data is multimedia data, and when the evaluation value of the psychological measure falls below a predetermined threshold value, the control unit is configured to store image data included in the multimedia data. A data transmission device characterized in that the resolution is lowered.   5. The data transmission device according to claim 3, wherein the evaluation unit evaluates the psychological measure based on a parameter indicating an application level service quality related to the transmission of the data.   6. The data transmission apparatus according to claim 5, wherein the parameter relates to a reception state in the apparatus that receives the data. A communication unit for receiving the transmitted data;
A control unit for obtaining parameters relating to a data reception state;
A data receiving apparatus, wherein the acquired parameter is transmitted from the communication unit to a transmission source of the data. Including a data transmission device and a data reception device,
The data transmission device is:
A communication unit for transmitting data;
An evaluation unit that evaluates psychological measures introduced during the transmission of data, based on a psychometric method to guarantee user-level service quality;
A control unit for controlling the data transmission state based on the evaluation result,
The data receiving apparatus includes a communication unit that receives transmitted data and transmits a parameter referred to in the evaluation of the psychological measure.   9. The data transmission system according to claim 8, wherein the parameter is a data reception rate.