JP2009104395A - Data transfer apparatus, and method and program for predicting data transfer end time - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To predict data transfer end time while considering a communication time zone for data transfer and changes in a band state of a communication line. <P>SOLUTION: A data transfer apparatus 010 compares performance information of the day with an average value of past performance information for each time, and when judging that a data transfer state is "good", predicts data transfer end time by using the residual of transfer source data and the average value of the past performance information. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a data transfer device, a data transfer end time prediction method, and a program, and more particularly, a data transfer device that predicts a data transfer end time in consideration of a change in a communication time zone for data transfer and a bandwidth state of a communication line, The present invention relates to a data transfer end time prediction method and program.

  A method for predicting a related end time is disclosed in Patent Document 1. The method for predicting the end time shown in Patent Document 1 stores the transfer rate when data was transferred in the past as transfer rate information, and divides the requested data transfer capacity by the past transfer rate and ends. Predict time.

JP 2003-208401 A

  However, the above-described Patent Document 1 has a problem that it is difficult to accurately predict the end time of data transfer. This is because a change in the communication time zone for data transfer and the change in the bandwidth state of the communication line is not taken into consideration.

  An object of the present invention is to provide a data transfer apparatus, a data transfer end time prediction method, and a program that solve the above-described problems.

  The first data transfer device of the present invention compares the performance information of the day with the average value of the past performance information for each time, and determines that the data transfer state is “good” when the data transfer state is “good”. The data transfer end time is predicted using the remaining capacity and the average value of the past performance information.

  The first data transfer end time prediction method of the present invention compares the performance information of the day with the average value of past performance information for each time, and determines that the state of data transfer is “good” The data transfer end time is predicted using the remaining capacity of the transfer source data and the average value of the past performance information.

  The first data transfer end time prediction program of the present invention compares the performance information of the day with the average value of the past performance information for each time in the data transfer device, and the data transfer state is “good”. If it is determined, a process of predicting the data transfer end time using the remaining capacity of the transfer source data and the average value of the past performance information is performed.

  The present invention has an effect of accurately predicting the end time of data transfer.

  A first embodiment of the present invention will be described. First, the configuration of the first embodiment will be described in detail with reference to the drawings. Referring to FIG. 1, a data transfer device 010 according to the first embodiment is an information processing device that operates under program control, and includes a transfer state analysis unit 011, a transfer end time prediction unit 012, and a performance information database 107.

  The performance information database 107 stores performance information on data transfer at regular time intervals. The performance information database 107 includes past performance information and performance information of the day, and holds an average value for each fixed time for the past performance information. An example of the performance information database 107 is shown in FIG. In the example of FIG. 2, the current day is X month X day after April 4th, for example, April 4th.

  The transfer state analysis unit 011 compares the performance information of the day with the average value of the past performance information for each time. The performance information on the current day is the current day throughput, that is, the transfer rate (the amount of data that can be transferred per unit time) for each time from the start time of data transfer on the current day to the present time. The past performance information is the actual throughput, that is, the transfer rate at the same time in the past. The current time is the time corresponding to the current day throughput T (n = n_current). Hereinafter, the performance information, throughput, transfer rate, and line bandwidth state are used interchangeably. In addition, the method of acquiring the performance information on the day and the past performance information is not questioned.

  When the difference between the average value of the past performance information and the value of the performance information of the current day compared at a certain time is ± X% (a constant value, for example, 20%) or less, the transfer state analysis unit 011 It is determined that the line bandwidth state at a certain time is “valid”. Then, the transfer state analysis unit 011 determines the ratio (“validity”) of the number of times (the number of samples) of the performance information on the day judged to be “valid” and the total number of times compared to the day (maximum value of variables related to time) Is calculated, and it is determined whether or not the “validity” is Y% (threshold value, for example, 81%) or more. “Relevance” is (100) * (number of times of performance information on the day judged as “valid”) / (total number of times compared on that day)%.

  The transfer end time prediction unit 012 determines that the current data transfer state is “good” if the “validity” is equal to or greater than Y%, and the average of the remaining capacity of the transfer source data and the actual throughput at the current time The value is used to predict the current transfer end time.

  Here, in order to understand the performance information database 107 which is an important element in the present invention, it will be described below with reference to FIGS. As shown in FIG. 2, the performance information database 107 includes the actual throughput, the day-to-day throughput, the difference, and the validity at a certain time (“time 0:58” to “time 1:06”). . The actual throughput is the throughput at a fixed time in the past month and day (April 1 to April 3) (unit: Mbps (megabits per second) such as “1883”, “1909”, “1843”), and constant An average value for each time (unit: Mbps (megabit per second) such as “1883” to “2151”) is included. FIG. 3 shows an image of the existence of throughput curves corresponding to the number of past dates (three from April 1 to April 3) as a result of throughput being recorded in the performance information database 107 at fixed time intervals. Is shown.

  Next, the operation of the first embodiment will be described in detail with reference to the drawings. Referring to FIG. 4, the transfer state analysis unit 011 compares whether the sample number n is equal to n_current. If not equal (step 101 / N), the process proceeds to step 102, and if equal (step 101 / Y), the step Proceed to 105 (step 101). Note that n represents a variable (sample number) relating to time, and takes a positive integer. N_current indicates the maximum value of a variable (sample number) relating to time, and takes a positive integer. n = 1 indicates a sample number corresponding to the start time of data transfer. n = n_current indicates the sample number corresponding to the current time, and is the maximum value of the sample number.

  When analyzing the data transfer status (validity), the transfer status analysis unit 011 compares the performance information of the current day with the average value of the past performance information for each time (step 102).

  For the performance information compared at a certain time (that is, immediately after the start of data transfer), the transfer state analysis unit 011 has a difference I between the average value of the past performance information and the value of the performance information of the day ± X% (for example, 20 %) In the following cases (step 103 / Y), it is determined that the line bandwidth state at a certain time is “valid” (step 104). The difference I is represented by the difference I = 100 * (average value of past performance information−value of performance information of the day) / (average value of past performance information). For example, in FIG. 2, since the difference is 100 * (1843−2003) /1843=−8.68% at the time corresponding to the current day throughput T (n = 1), the transfer state analysis unit 011 has a difference of ± X % Or less, and judged to be “valid”.

  When the difference I (n = 1) between the average value of the past performance information and the value of the performance information of the day is larger than ± X% (step 103 / N), the transfer state analysis unit 011 determines the line bandwidth at that time. Do not use state for analysis.

  The transfer state analysis unit 011 repeats the above operation until n becomes n_current (that is, the current time).

  The transfer state analysis unit 011 calculates a difference I (n = n_current) between the average value of the past performance information and the value of the performance information of the day. Then, the transfer state analysis unit 011 determines whether the number of times of the performance information on the day determined to be “valid” is “validity” equal to or greater than Y% with respect to the maximum value n_current of the variable n related to time. If it is determined that Y% or more (step 105 / Y), the process proceeds to step 106 (step 105). For example, in FIG. 2, since “validity” is 100 * 4/4 = 100%, “validity” is Y% or more.

  The transfer end time prediction unit 012 determines that the current data transfer state is “good” because the “validity” is Y% (for example, 81%) or more (step 106).

  Also, the transfer end time prediction unit 012 predicts the transfer end time at the current time using the remaining capacity of the transfer source data 104 at the current time and the average value of the actual throughput, and predicts the transfer end time and the analysis result (“good” ”) Is output (step 107). More specifically, the transfer end time prediction unit 012 sequentially subtracts the average value of the actual throughput after the current time from the remaining capacity of the current transfer source data 104. In the example of FIG. 2, the transfer end time prediction unit 012 sequentially subtracts the average value of the actual throughput at time 1:04, and then the average value of the actual throughput at time 1:05. The average value of the actual throughput is converted into a value in minutes. Then, the transfer end time predicting unit 012 sets the time corresponding to the average value of the actual throughput when the remaining capacity of the current transfer source data 104 becomes zero as the transfer end predicted time.

  Regarding the operation of the transfer end time prediction unit 012 using the actual throughput, FIG. 5 shows an image of the latest actual throughput curve when the current data transfer state (relevance) by the transfer state analysis unit 011 is “good”. This is illustrated in The actual throughput curve is a set of average values of past actual throughputs for the same time zone on past dates. That is, it is a throughput curve showing the actual throughput of the average value in FIG.

  Further, the estimated transfer end time can also be obtained by the following method. The remaining capacity of the transfer source data 104 after the present time is calculated by subtracting the transferred data amount from the start of the data transfer to the current time from the transfer source data 104 capacity at the start of the data transfer. Here, when the actual throughput curve is regarded as "integrated function" and each time sample is regarded as "finite number of grid points", the numerical integration method, that is, "replace the integrand with a finite number of grid points" is used. It can be said that the obtained result (integrated value) is equal to the remaining capacity of the transfer source data 104 from the current time to the data transfer end time. By knowing the “integrand”, “integral value”, and “current time”, the value is calculated using a “polynomial that connects the integrand with a finite number of grid points” as an equation related to time, and the obtained value is transferred to the data. This is the predicted end time. That is, α (predicted data transfer end time) is calculated by solving the following equation. Note that S is the remaining capacity of the transfer source data 104, t is time, and tc is time with respect to n_current.

  Next, the effect of the first embodiment will be described. The effect of this embodiment is that the end time of data transfer can be accurately predicted. The reason is that past performance information is accumulated and saved in the performance information database 107, and the past performance information is compared with the performance information of the current day, and the change of the communication time zone for data transfer and the bandwidth state of the communication line are This is because when the “validity” is greater than or equal to the threshold value, the data transfer end time is predicted based on the average value of the actual throughput.

  Next, a second embodiment of the present invention will be described. First, the configuration of the second embodiment will be described in detail with reference to the drawings. The data transfer apparatus 100 according to the second embodiment is an information processing apparatus that operates under program control.

  Referring to FIG. 6, the data transfer device 100 constantly monitors the operation status of the data transfer unit 103 for transferring the transfer source data 104 to another device (not shown) and the data transfer unit 103 and stores it in the performance information database 107. And a performance information holding unit 106 that records performance information.

  In addition, the data transfer apparatus 100 predicts the transfer end time in response to an instruction from the transfer end prediction instructing unit 108 for instructing the prediction of the transfer end time at an arbitrary time (that is, the current time) and the transfer end prediction instructing unit 108. A transfer end prediction unit 109.

  The transfer end prediction unit 109 accesses the performance information database 107 to acquire the past performance information and the current day performance information, and the current day performance obtained from the transfer state acquisition unit 110. A transfer state analysis unit 111 that compares the information with past performance information and analyzes the current performance information is included.

  The transfer end prediction unit 109 includes a transfer end time prediction unit 112 that receives the analysis result of the transfer state analysis unit 111 and predicts the transfer end time.

  Next, the operation of the second embodiment will be described in detail with reference to the drawings. Here, it is assumed that the performance information holding unit 106 constantly monitors the state of data transfer by the data transfer unit 103. More specifically, the performance information holding unit 106 determines the remaining capacity of the transfer source data 104 at every fixed time, the capacity of the transferred data, and the throughput at each time from the start to the end of the data transfer. It shall be recorded in the performance information database 107.

  Next, the outline of the operation of the transfer end prediction unit 109 will be described with reference to FIG. The transfer end prediction unit 109 uses the performance information database 107 to analyze the data transfer state (validity) and predict the data transfer end time using the instruction from the transfer end prediction instruction unit 108. The transfer end prediction unit 109 includes a transfer state acquisition unit 110, a transfer state analysis unit 111, and a transfer end time prediction unit 112.

  Referring to FIG. 7, the transfer status acquisition unit 110 accesses the performance information database 107, acquires past performance information and current performance information, and passes them to the transfer status analysis unit 111 (step 201).

  The transfer state analysis unit 111 compares the current performance information obtained from the transfer state acquisition unit 110 with the past performance information, analyzes the difference, calculates the current “validity” value, and compares it with the threshold value. (Step 202).

  The transfer end time prediction unit 112 determines the data transfer state based on the analysis result of the transfer state analysis unit 111, that is, the comparison result of the “validity” value at the present time, and predicts the end time of the data transfer ( Step 203).

  Further, details of operations of the transfer state analysis unit 111 and the transfer end time prediction unit 112, which are important elements of the transfer end prediction unit 109, will be described with reference to FIG.

  Referring to FIG. 8, Steps 301 to 304 are the same as Steps 101 to 104 of the first embodiment.

  The transfer state analysis unit 111 calculates a difference I (n = n_current) between the average value of the past performance information and the value of the performance information of the day. Then, the transfer state analysis unit 111 determines whether the number of times of the performance information on the day determined to be “valid” is “validity” equal to or more than Y% with respect to the maximum value n_current of the variable n related to time. judge. When the “validity” is Y% or more (step 305 / Y), the transfer state analysis unit 111 proceeds to step 306. When the “validity” is smaller than Y% (step 305 / N), the transfer state analysis unit 111 proceeds to step 308. (Step 305).

  Steps 306 to 307 are the same as steps 106 to 107 in the first embodiment.

  If the “validity” is smaller than Y%, the transfer end time prediction unit 112 determines that the current data transfer state is “Needs Attention” (step 308). “Attention” is sometimes expressed as “not good”.

  The transfer end time prediction unit 112 averages the remaining capacity of the current transfer source data 104 and the value of the current day throughput (in the example of FIG. 2, four current day throughputs corresponding to time 1:00 to time 1:03). Using the average value, the current transfer end time is predicted. Then, the transfer end time prediction unit 112 outputs the transfer end prediction time and the analysis result (“caution”) (step 309). More specifically, the transfer end time prediction unit 112 divides the remaining capacity of the current transfer source data 104 by the average value of the current day throughput values, and adds the divided value to the current time to determine the transfer end predicted time and To do.

  Regarding the operation of the transfer end time prediction unit 112 using the current day throughput, an image of the average value of the current day throughput values when the current data transfer state (relevance) by the transfer state analysis unit 111 is “Needs Attention” Is illustrated in FIG.

  Next, the effect of the second embodiment will be described. The present embodiment has the following effects in addition to the effects of the first embodiment. That is, it is possible to accurately predict the end time of data transfer. The reason is that past performance information is accumulated and saved in the performance information database 107, and the past performance information is compared with the performance information of the current day. This is because the data transfer end time is predicted based on the average value.

  Next, a third embodiment of the present invention will be described. The present embodiment is a data transfer system using the data transfer apparatus 100 described in the second embodiment. First, the configuration of the third embodiment will be described in detail with reference to the drawings. Referring to FIG. 10, the data transfer system according to the third embodiment includes a data transfer apparatus 100, a data reception apparatus 102, and a network 101 such as a communication line that connects the data transfer apparatus 100 and the data reception apparatus 102. .

  The data receiving apparatus 102 is an information processing apparatus that operates under program control. The data receiving apparatus 102 receives the transfer source data 104 from the data transfer unit 103 via the network 101 and stores the data receiving unit 113 that stores the data as transferred data 105 therein. Including.

  Subsequently, the operation of the third embodiment will be described. The operation of the third embodiment conforms to the operation of the data transfer apparatus 100 described in the second embodiment.

  Next, the effect of the third embodiment will be described. The effect of this embodiment is the same as that of the second embodiment. That is, it is possible to accurately predict the end time of data transfer. The reason is that the past performance information is accumulated and stored in the performance information database 107, the past performance information is compared with the performance information of the current day, and if the “validity” is equal to or greater than the threshold, the average value of the actual throughput This is because the data transfer end time is predicted based on the above. Further, when the “validity” is below the threshold value, the data transfer end time is predicted based on the average value of the throughput values on the day.

  Next, a fourth embodiment of the present invention will be described. This embodiment is a system applied to a disk array having a data transfer function between disk arrays. First, the configuration of the fourth embodiment will be described with reference to the drawings. Referring to FIG. 11, the fourth embodiment includes a server A 120, a network 101, a server B 122, a disk array A 130, a second network 131, and a disk array B 132. The disk array A 130 transfers data to the disk array B 132 via the second network 131.

  The server A 120 is an information processing apparatus that operates under program control. For example, the server A 120 may have a configuration equivalent to that of the data transfer apparatus 100 according to the third embodiment. The server B 122 is an information processing apparatus that operates under program control. The server B 122 may have a configuration equivalent to, for example, the data receiving apparatus 102 of the third embodiment.

  The disk array A 130 is a device for storing data, and includes a data transfer unit 103, transfer source data 104, a performance information holding unit 106, a performance information database 107, a transfer end prediction instruction unit 108, and a transfer end prediction unit. 109, a transfer state acquisition unit 110, a transfer state analysis unit 111, and a transfer end time prediction unit 112.

  The disk array B 132 is a device for storing data, and includes transferred data 105 and a data receiving unit 113. The second network 131 is a communication line or the like that connects the disk array A 130 and the disk array B 132.

  Next, the operation of the fourth embodiment will be described. The operation of the fourth embodiment is similar to the operation of the third embodiment. The operation of the disk array A 130 is in accordance with the operation of the data transfer apparatus 100. Further, the operation of the disk array B 132 is in accordance with the operation of the data receiving apparatus 102.

  Then, the effect of 4th Embodiment is demonstrated. The effect of this embodiment is that the data transfer end time can be accurately predicted even in the data transfer between the disk arrays.

  The above-described data transfer apparatuses 010 and 100 in the embodiments of the present invention are realized by the configuration shown in FIG.

  Referring to FIG. 12, the data transfer devices 010 and 100 include a data processing device 991 constituted by a CPU (Central Processing Unit) and the like, a storage device 992 constituted by a memory having a short read / write time, and a storage such as a hard disk. A large-capacity recording medium 993, an input device 994 for controlling data input, an output device 995 for controlling data output, and a communication device 996 for controlling data transmission / reception with the outside are configured. Yes.

  In this configuration, for example, for the data transfer device 010 shown in FIG. 1, a program for the data transfer device 010 is stored in the recording medium 993. The data processing device 991 reads the program for the data transfer device 010 from the recording medium 993 into the storage device 992 and executes it, thereby realizing the transfer state analysis unit 011 and the transfer end time prediction unit 012.

  For example, for the data transfer apparatus 100 shown in FIG. 5, a program for the data transfer apparatus 100 is stored in the recording medium 993. When the data processing device 991 reads the program for the data transfer device 100 from the recording medium 993 into the storage device 992 and executes it, the data transfer unit 103, the performance information holding unit 106, the transfer end prediction instruction unit 108, and the transfer end prediction unit 109, a transfer state acquisition unit 110, a transfer state analysis unit 111, and a transfer end time prediction unit 112.

It is a figure which shows the structure of the 1st Embodiment of this invention. It is a figure which shows the example of the performance information database. It is a figure explaining the performance information database. It is a figure which shows the flowchart of the operation | movement of the 1st Embodiment of this invention. It is a figure explaining performance throughput. It is a figure which shows the structure of the 2nd Embodiment of this invention. FIG. 10 is a diagram illustrating a flowchart of a schematic operation of a transfer end prediction unit 109. The flowchart of the detailed operation | movement of the transfer state analysis part 111 and the transfer end time prediction part 112 is shown. It is a figure explaining the through-the-day throughput. It is a figure which shows the structure of the 3rd Embodiment of this invention. It is a figure which shows the structure of the 4th Embodiment of this invention. It is a block diagram which shows schematic structure of the data processor and recording medium in embodiment of this invention.

Explanation of symbols

010 Data transfer device 011 Transfer state analysis unit 012 Transfer end time prediction unit 100 Data transfer device 101 Network 102 Data receiving device 103 Data transfer unit 104 Transfer source data 105 Transferred data 106 Performance information holding unit 107 Performance information database 108 Transfer end prediction Instruction unit 109 Transfer end prediction unit 110 Transfer state acquisition unit 111 Transfer state analysis unit 112 Transfer end time prediction unit 113 Data reception unit 120 Server A
122 Server B
130 Disk array A
131 Second network 132 Disk array B
991 Data processing device 992 Storage device 993 Recording medium 994 Input device 995 Output device 996 Communication device

Claims (20)

Compare the performance information of the day with the average value of the past performance information for each time, and if the data transfer status is determined to be “good”, the remaining capacity of the transfer source data and the average of the past performance information Predict the data transfer end time using the value,
A data transfer device. A performance information database that accumulates performance information of data transfer at a certain time, and holds an average value at the certain time for the past performance information;
When the difference between the average value of the past performance information and the value of the performance information on the day is equal to or less than a predetermined value, the line bandwidth state at that time is determined to be “valid”, and the “valid” is determined. A transfer state analysis unit that determines whether or not the “validity” is equal to or greater than a threshold with respect to the total number of times compared with the number of times;
If the “validity” is equal to or greater than the threshold, it is determined that the current data transfer state is “good”, and the average value of the past performance information is sequentially subtracted from the remaining capacity of the transfer source data at the current time. A transfer end time prediction unit that sets a time corresponding to the average value of the past performance information when the remaining capacity of the transfer source data becomes zero as a transfer end prediction time,
The data transfer device according to claim 1. The transfer end time prediction unit
When the “validity” is smaller than the threshold value, it is determined that the current data transfer state is “not good”, and the remaining capacity of the transfer source data at the current time is divided by the average value of the performance information of the day. Predict the transfer end time by adding
The data transfer apparatus according to claim 2, wherein: A data transfer unit for transferring data;
The data transfer apparatus according to claim 3. Performance information that records in the performance information database the capacity of the transfer source data at a certain time, the capacity of the transferred data, and the performance information of the day at the certain time from the start to the end of the data transfer With a holding part,
5. The data transfer apparatus according to claim 4, wherein Accessing the performance information database, obtaining the past performance information and the performance information of the day, and comprising a transfer state acquisition unit that passes to the transfer state analysis unit,
6. The data transfer apparatus according to claim 5, wherein A transfer end prediction instruction unit for instructing the prediction of the transfer end time at the present time;
The data transfer apparatus according to claim 6. Compare the performance information of the day with the average value of the past performance information for each time, and if the data transfer status is determined to be “good”, the remaining capacity of the transfer source data and the average of the past performance information Predict the data transfer end time using the value,
A method for predicting a data transfer end time. The transfer status analyzer
The performance information of data transfer at a certain time is accumulated, and the past performance information is read from a performance information database that holds the average value at the certain time for the past performance information, and the average value of the past performance information and the current day When the difference from the value of the performance information is below a certain value, the line bandwidth state at that time is determined to be “valid”, and the number of times determined as “valid” is compared with the total number of times compared. Determine if the "validity" is above a threshold,
The transfer end time prediction unit
If the “validity” is equal to or greater than the threshold, it is determined that the current data transfer state is “good”, and the average value of the past performance information is sequentially subtracted from the remaining capacity of the transfer source data at the current time. The time corresponding to the average value of the past performance information when the remaining capacity of the transfer source data becomes zero is set as the transfer end predicted time.
9. The data transfer end time prediction method according to claim 8, wherein: The transfer end time prediction unit
When the “validity” is smaller than the threshold value, it is determined that the current data transfer state is “not good”, and the remaining capacity of the transfer source data at the current time is divided by the average value of the performance information of the day. Predict the transfer end time by adding
The data transfer end time prediction method according to claim 9. The performance information holding unit
From the start to the end of the data transfer, record the capacity of the transfer source data at every fixed time, the capacity of the transferred data, and the performance information of the day at every fixed time in the performance information database.
The data transfer end time prediction method according to claim 10. The transfer status acquisition unit
Access the performance information database to obtain the past performance information and the performance information of the day and pass it to the transfer state analysis unit;
The data transfer end time prediction method according to claim 11. The transfer end prediction instruction unit
Instructing the prediction of the current transfer end time,
13. The data transfer end time prediction method according to claim 12, wherein: In the data transfer device,
Compare the performance information of the day with the average value of the past performance information for each time, and if the data transfer status is determined to be “good”, the remaining capacity of the transfer source data and the average of the past performance information Processing to predict the data transfer end time using the value,
A data transfer end time prediction program characterized in that The performance information of data transfer at a certain time is accumulated, the performance information database holding the average value at the certain time for the past performance information is read, the average value of the past performance information and the current day When the difference from the value of the performance information is below a certain value, the line bandwidth state at that time is determined to be “valid”, and the number of times determined as “valid” is compared with the total number of times compared. A transfer state analysis process for determining whether or not the “validity” is equal to or greater than a threshold;
If the “validity” is equal to or greater than the threshold, it is determined that the current data transfer state is “good”, and the average value of the past performance information is sequentially subtracted from the remaining capacity of the transfer source data at the current time. And a transfer end time prediction process in which a time corresponding to the average value of the past performance information when the remaining capacity of the transfer source data becomes zero is used as a transfer end prediction time. 14. A data transfer end time prediction program according to 14. If the “relevance” is smaller than the threshold, the transfer end time prediction process determines that the current data transfer state is “not good”, and determines the remaining capacity of the transfer source data at the current time as the performance information of the current day. The value obtained by dividing by the average value of is added to the current time to predict the transfer end time,
16. The data transfer end time prediction program according to claim 15, wherein: The data transfer end time prediction program according to claim 16, wherein a data transfer process for performing data transfer is performed. Performance information for recording in the performance information database the capacity of the transfer source data at a certain time, the capacity of the transferred data, and the performance information of the day at the certain time from the start to the end of the data transfer 18. The data transfer end time prediction program according to claim 17, wherein a holding process is performed. 19. The data transfer according to claim 18, wherein the performance information database is accessed to acquire the past performance information and the performance information of the day, and to perform a transfer state acquisition process to be passed to the transfer state analysis process. End time prediction program. 20. The data transfer end time prediction program according to claim 19, further comprising: a transfer end prediction instruction process for instructing prediction of a transfer end time at a current time.

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