JP5458660B2 - Data management system, data management method, program, and data server - Google Patents

Description

  The present invention relates to a data management system, a data management method, a program, and a data server, and more particularly to a data management system, a data management method, a program, and a data server for efficiently managing data.

  In a repository of a data server that manages logistics information represented by an EPCIS (Electronic Product Code Information Service) database described in Non-Patent Document 1, logistics that occurs in response to an event such as arrival or shipment of goods Information etc. are written.

  Specifically, a data server as described above that manages logistics information reads information at each site from a device having an identifier such as an RFID (Radio Frequency IDentification) tag attached to a transported article, and based on this information. Event data such as goods entering and leaving are created and stored in the repository.

  Further, when this device is a device equipped with a sensor such as a sensor RFID tag or a logger, sensor data that is an environmental history during transportation of the transported article can be acquired and stored.

  Such a data server performs processing such as deletion or compression by selecting the distribution information with the old collection time when the distribution information to be written increases due to the increase in the number of items handled and cannot be stored in the repository owned. Yes.

  Patent Document 1 discloses an information processing system for managing files in a distributed manner. The information processing system described in Patent Document 1 selects a disk device for storing a new file based on the access frequency of the disk device derived by monitoring the access status of a file already stored in each disk device. Yes.

Japanese Patent Laid-Open No. 07-152498

EPCglobal Inc., The EPCglobal Architecture Framework Version 1.2, September 2007 (http://www.epcglobalinc.org/standards/architecture/architecture_1_2-framework-20070910.pdf)

  However, in the techniques described in the above-mentioned prior art documents, data that is unlikely to be referenced is stored without being erased or compressed for a long time, or data having a long reference period is required. There is a problem that the data is erased or compressed earlier than the normal period.

  An object of the present invention is to provide a data management system, a data management method, a program, and a data server that solve the above-described problems.

  The data management system of the present invention provides a reference frequency calculation element acquisition unit that acquires at least one reference frequency calculation element indicating the property of the predicted reference frequency calculation target information, and the corresponding reference frequency calculation element based on the acquired reference frequency calculation element. Predictive reference frequency calculation means for calculating a predicted reference frequency for the predicted reference frequency calculation target information.

  The data management method of the present invention acquires at least one reference frequency calculation element indicating the nature of the predicted reference frequency calculation target information, and based on the acquired reference frequency calculation element, the corresponding predicted reference frequency calculation target information The predicted reference frequency is calculated.

  The program of the present invention acquires at least one reference frequency calculation element indicating the nature of the predicted reference frequency calculation target information, and predicts the corresponding predicted reference frequency calculation target information based on the acquired reference frequency calculation element. Causes the computer to execute processing for calculating the reference frequency.

  The data server of the present invention includes a reference frequency calculation element acquisition unit that acquires at least one reference frequency calculation element indicating the property of the prediction reference frequency calculation target information, and the corresponding prediction based on the acquired reference frequency calculation element Prediction reference frequency calculation means for calculating a prediction reference frequency for the reference frequency calculation target information.

  According to the present invention, data storage control can be performed based on the predicted access frequency indicating the possibility of data being referenced.

It is a block diagram which shows the structure of the 1st and 2nd embodiment of this invention. It is a figure which shows the structure of the event data memorize | stored in the event data memory | storage means of the 1st and 2nd embodiment of this invention. It is a figure which shows the structure of the sensor data memorize | stored in the sensor data memory | storage means of the 1st and 2nd embodiment of this invention. It is a flowchart which shows operation | movement of the data server of the 1st Embodiment of this invention. It is a flowchart which shows operation | movement of the data server of the 2nd Embodiment of this invention. It is a block diagram which shows the structure of the 3rd Embodiment of this invention. It is a flowchart which shows operation | movement of the data server of the 3rd Embodiment of this invention. It is a block diagram which shows another structure of the 3rd Embodiment of this invention. It is a block diagram which shows the structure of the 4th Embodiment of this invention. It is a block diagram which shows another structure of the 5th Embodiment of this invention. It is a block diagram which shows another structure of the 6th Embodiment of this invention.

  Next, embodiments of the present invention will be described in detail with reference to the drawings.

  Referring to FIG. 1, a traceability system (also referred to as a data management system) 901 according to the first embodiment of the present invention includes a portable storage device 200, a physical distribution information collection device (also referred to as information collection means) 300, a physical distribution An information address resolution device 400 and a data server 501 are included.

  The distribution information address resolution device 400 and the data server 501 are connected to each other via a network.

  The portable storage device 200 has a function of storing the identifier 620 and the measurement history 670 and a function of communicating with the physical distribution information collection device 300 and physical distribution equipment (not shown). The identifier 620 may be, for example, URI (Uniform Resource Identifiers) in an EPC (Electronic Product Code) tag, IDSTGIN (Serialized Global Trade Item Number), SSCC (Serial Shipping Container Code (L), or N . Further, the measurement history 670 may be, for example, temperature information, humidity information, or impact information collected by the portable storage device 200 itself or received from a distribution facility.

  The portable storage device 200 is realized by, for example, an RFID tag or a portable terminal. The portable storage device 200 is a tag with a sensor, a logger, or the like, and may have a function of collecting environmental information such as temperature, humidity, or impact.

  In addition, the portable storage device 200 transmits the identifier 620 and the measurement history 670 to the physical distribution information collection device 300.

  The physical distribution information collection device 300 communicates with the portable storage device 200, creates a function for creating information to be output to the data server 501 based on the identifier 620 and the measurement history 670 received from the portable storage device 200, and data A function of communicating with the server 501.

  The physical distribution information collection device 300 includes, for example, a device such as an RFID reader that exchanges information with an RFID tag, or a general server device or personal computer including a CPU, a memory, a hard disk device, or the like connected to such a device, This is realized in combination with a program such as RFID middleware that processes data collected by the device. Further, for example, the data server 501 may be configured such that such a device is connected and RFID middleware is mounted.

  The physical distribution information collection device 300 receives the identifier 620 and the measurement history 670 from the portable storage device 200, and based on these, the event data (also referred to as shared information) 600 including at least the identifier 620, at least the identifier 620 and the measurement history 670 Sensor data 800 (also referred to as predicted reference frequency calculation target information) is sent to the data server 501.

  As shown in FIG. 2, the event data 600 includes at least an identifier 620, and may further include one or more of an event time 630, an event step 640, a reading location 650, and a tag location 660. The event time 630 may be, for example, time information when an event occurs. The event step 640 may be information indicating, for example, entering or leaving. Further, the reading location 650 may be position information of the physical distribution information collection device 300, for example. The tag location 660 may be position information of the portable storage device 200, for example.

  As shown in FIG. 3, the sensor data 800 includes at least an identifier 620 and a measurement history 670. The measurement history 670 includes a measurement start time 671, a measurement end time 672, a measurement interval 673, and a measurement value 674. Specifically, for example, the sensor data 800 is an environmental information history (for example, temperature information, humidity information, or impact information) during transportation of the article acquired by a sensor attached to the article.

  The distribution information address resolution device 400 is a computer that executes a program using a technique for address resolution such as ONS (Object Name Service) or P2P (Peer to Peer), or a general server device having such functions. Or a personal computer. Further, the distribution information address resolution device 400 may be realized as a configuration in which the data server 501 includes the distribution information address resolution device 400 by placing the above-described program on the data server 501.

  The logistics information address resolution device 400 stores a function for receiving an address resolution request including the identifier 620 from the data server 501, and event data 600 and sensor data 800 corresponding to the identifier 620 included in the received address resolution request. A function of specifying the data server 501 and a function of transmitting an address list including all the addresses of the specified data server 501 to the data server 501 of the address resolution request source. The information in the address list is also referred to as the existence state of the data server storing the shared information.

  The data server 501 includes event data storage means (also called shared information storage means) 510, sensor data storage means 520, input / output means 530, predicted reference frequency calculation means 550, reference frequency calculation element acquisition means 540, and communication means 560. ing.

  The event data storage unit 510 has a function of storing the event data 600 and a function of transmitting the event data 600 corresponding to a reception request for the event data 600 including the identifier 620.

  The sensor data storage unit 520 has a function of storing the sensor data 800 and the predicted reference frequency.

  The input / output unit 530 has a function of receiving data input from an input device (not shown) such as a keyboard and an external storage device, and a function of outputting data to an output device (not shown) such as a display and an external storage device. .

  The input / output unit 530 inputs information specifying any of the event data 600 stored in the event data storage unit 510 or information specifying any of the sensor data 800 stored in the sensor data storage unit 520. Then, it is transmitted to the predicted reference frequency calculation means 550.

  The reference frequency calculation element acquisition means 540 has a function of receiving the sensor data 800 from the physical distribution information collection device 300 and a function of transmitting an address resolution request including the identifier 620 included in the received sensor data 800 to the physical distribution information address resolution device 400. And a function of receiving an address list (also referred to as a reference frequency calculation element) transmitted from the physical distribution information address resolution device 400 as a response to the address resolution request.

  The predicted reference frequency calculation unit 550 calculates a predicted reference frequency of the received sensor data 800 based on the address list received by the reference frequency calculation element acquisition unit 540, and sensor data 800 corresponding to the calculated predicted reference frequency. In addition to the sensor data storage means 520 (in this case, also referred to as predicted reference frequency calculation target information storage means).

  The communication unit 560 has a function of transmitting / receiving data to / from the outside by controlling the Internet, a LAN, a line, a dedicated interface, and the like. The communication means 560 communicates with other data servers 501 or with the physical distribution information address resolution device 400, address resolution requests and responses, event data 600 acquisition requests and responses, and sensor data 800 acquisition requests. Controls communications such as responses. The communication unit 560 controls communication with the physical distribution information collection apparatus 300 for acquiring the event data 600 and the sensor data 800.

  In the description of the present embodiment, the description of being performed via the communication control function of the communication unit 560 described above is omitted.

  Next, the operation of the present embodiment will be described in detail with reference to FIGS.

  The operation of the traceability system 901 of the present embodiment starts when the physical distribution information collection device 300 receives the identifier 620 and the measurement history 670 from the portable storage device 200. The physical distribution information collection device 300 that has received the information creates event data 600 and sensor data 800 based on the received identifier 620 and measurement history 670. Further, the physical distribution information collection device 300 transmits the created event data 600 and sensor data 800 to the data server 501.

  Next, in response to this transmission, the data server 501 starts operation. FIG. 4 is a flowchart showing the operation of the data server 501.

  First, the event data storage means 510 receives the event data 600 from the physical distribution information collection device 300 and stores the event data 600 (step S101).

  Next, the reference frequency calculation element acquisition unit 540 receives the sensor data 800 from the physical distribution information collection device 300 (step S102).

  Subsequently, the reference frequency calculation element acquisition unit 540 creates an address resolution request including the identifier 620 included in the sensor data 800, and transmits it to the physical distribution information address resolution device 400 (step S103).

The logistics information address resolution device 400 that has received the address resolution request extracts the identifier 620 from the address resolution request, and specifies the data server 501 that stores the event data 600 including the identifier 620 having the same value. Subsequently, the physical distribution information address resolution device 400 creates an address list of the identified data server 501 and transmits the created address list as a response to the data server 501 that is the transmission source of the address resolution request. (The operation steps of these logistics information address resolution devices 400 are not shown.)
Next, the reference frequency calculation element acquisition unit 540 receives the address list transmitted from the physical distribution information address resolution device 400 (step S104).

  Next, the predicted reference frequency calculation unit 550 calculates the predicted reference frequency of the received sensor data 800 based on the address list received in step S104 (step S105).

  For example, when the number of addresses included in the address list is “5”, the predicted reference frequency is calculated as “5”. That is, the predicted reference frequency of the sensor data 800 is calculated based on the distributed state of the event data 600 related to the sensor data 800.

  The predicted reference frequency is calculated by, for example, the number of types when the addresses included in the address list are represented by a predetermined regular expression (for example, to avoid counting addresses in the same domain twice). It is good.

  The predicted reference frequency calculation unit 550 adds the calculated predicted reference frequency to the corresponding sensor data 800 and stores it in the sensor data storage unit 520 (step S106).

  As described above, the sensor data 800 with the predicted reference frequency is stored in the sensor data storage unit 520.

  In addition, this embodiment demonstrated above is good also considering the event data 600 as one of prediction reference frequency calculation object information by comprising so that the process with respect to the sensor data 800 may be implemented with respect to the event data 600. FIG.

  In addition, the processing for the sensor data 800 in the present embodiment described above is replaced with the event data 600 received from the physical distribution information collection device 300, and any one of the event data 600 stored in the event data storage unit 510 is used. However, the prediction reference frequency may be calculated asynchronously with the flow of physical distribution. In this case, any of the event data 600 stored in the target event data storage unit 510 may be specified via the input / output unit 530.

  In addition, the processing for the sensor data 800 in the present embodiment described above is replaced with the sensor data 800 received from the physical distribution information collection device 300, and any one of the sensor data 800 stored in the sensor data storage unit 520 is used. However, the prediction reference frequency may be calculated asynchronously with the flow of physical distribution. In this case, any one of the sensor data 800 stored in the target sensor data storage unit 520 may be specified via the input / output unit 530.

  In this embodiment, the identifier 620 is used to associate the event data 600 and the sensor data 800. For example, the sensor data is shared data, and the measurement start time 671, the measurement end time 672, or the measurement time and the measurement value 674 are used. Or a hash value created from these pairs may be used instead of the identifier. Furthermore, the event data 600 and the sensor data 800 each have different identifiers or other identification information, and for example, the logistics information address resolution device 400 is configured to have means for associating these identifiers or other identification information. May be.

  The first effect of the present embodiment described above is that the sensor data 800 to which the access frequency prediction based on the attribute of the sensor data 800 itself is added can be obtained.

  This is because the predicted reference frequency calculated based on the information related to the sensor data 800 itself is added to the sensor data 800.

  The second effect of the present embodiment described above is that the event data 600 to which the access frequency prediction based on the attribute of the event data 600 itself is added can be obtained.

  The reason is that the predicted reference frequency calculated based on information related to the event data 600 itself is added to the event data 600 and stored.

  Next, a second embodiment of the present invention will be described in detail with reference to the drawings.

  The configuration of the second embodiment of the present invention is the same as the configuration of the first embodiment shown in FIG. The second embodiment of the present invention differs from the first embodiment in the functions and operations of the reference frequency calculation element acquisition unit 540 and the predicted reference frequency calculation unit 550.

  In addition to the function described in the first embodiment, the reference frequency calculation element acquisition unit 540 includes a predetermined abnormal value (also referred to as a predetermined singular value) included in the measured value 674 of the received sensor data 800. It further has a function of counting the number (also called presence state).

  The predicted reference frequency calculation unit 550 calculates the predicted reference frequency of the received sensor data 800 based on the number of abnormal values counted by the reference frequency calculation element acquisition unit 540 in addition to the functions described in the first embodiment. It further has a function to

  For example, if the number of addresses included in the address list described in the first embodiment is N and the number of abnormal values is P (P is a natural number), the predicted reference frequency is calculated as “N × (P + 1)”. Is calculated.

  That is, the predicted reference frequency of the sensor data 800 is determined based on the distribution state of the event data 600 related to the sensor data 800 and the content of the sensor data 800 (for example, the state in which the management environment of the item to which the portable storage device 200 is attached is normal). Is calculated based on the measured value 674) indicating that the deviation is exceeded.

  Next, the operation of the present embodiment will be described in detail with reference to FIGS.

  FIG. 5 is a flowchart showing the operation of the data server 501 of this embodiment. In the operation of the present embodiment, step S201 is added between step S102 and step S103, and step S105 is changed to step S202 with respect to the flowchart of FIG. 4 describing the operation of the first embodiment. It is different from being changed.

  Subsequent to step S102, the reference frequency calculation element acquisition unit 540 counts the number of abnormal values included in the measured value 674 of the received sensor data 800 (step S201). For example, in the measured value 674 shown in FIG. 3, if the individual elements of the measured value 674 are expressed in hexadecimal numbers, the elements “01”, “A1”, “A5”, and “32” are included. Yes. If the predetermined abnormal value is, for example, “20 or less”, the measured value 674 includes one abnormal value “01”, so the number of abnormal values is counted as “1”. Then, the process proceeds to step S103.

  Subsequent to step S104, the predicted reference frequency calculation unit 550 calculates the predicted reference frequency of the received sensor data 800 based on the address list received in step S104 and the number of abnormal values counted in step S102 (step S104). S202). Then, the process proceeds to step S106.

  For example, when the number of addresses included in the address list is “5”, the prediction reference frequency is calculated as “N = 5” and the number of abnormal values is “1”, so “P = 1”. Is calculated as “5 × (1 + 1) = 10”.

  The effect in the present embodiment described above is that, in addition to the effect of the first embodiment, it is possible to obtain a predicted reference frequency that is more dependent on the attribute of the sensor data 800 itself.

  The reason is that the predicted reference frequency is calculated based on the content of the measured value 674 of the sensor data 800 in addition to the distributed state of the event data 600 related to the sensor data 800.

  Next, a third embodiment of the present invention will be described in detail with reference to the drawings.

  Referring to FIG. 6, the traceability system 902 according to the third embodiment of the present invention includes a portable storage device 200, a physical distribution information collection device 300, a physical distribution information address resolution device 400, and a data server 502. ing. The portable storage device 200, the distribution information collection device 300, and the distribution information address resolution device 400 are the same as those described in the first embodiment.

  Compared to the data server 501 of the first embodiment, the data server 502 is added with a corporate logistics evaluation value management means 570. Further, the data server 502 is different from the data server 501 of the first embodiment in the functions and operations of the reference frequency calculation element acquisition unit 540 and the predicted reference frequency calculation unit 550.

  The enterprise logistics evaluation value management unit 570 stores the enterprise logistics evaluation value, which is an evaluation value for the logistics business of the company performing the logistics business, and the enterprise logistics evaluation value acquisition request from the predicted reference frequency calculation unit 550. And a function of transmitting a physical distribution evaluation value.

  The enterprise logistics evaluation value is set based on, for example, a past logistics history of a logistics company, and each data server 502 and each company correspond to each other. The enterprise logistics evaluation value may be set via the input / output unit 530, or based on the event data 600 and the sensor data 800 stored in the event data storage unit 510 and the sensor data storage unit 520 of the data server 502. The enterprise physical distribution evaluation value management means 570 may calculate. For example, the input / output unit 530 may transmit the enterprise logistics evaluation value to the predicted reference frequency calculation unit 550 when it is input. Further, for example, a server administrator or a third party may input a corporate logistics evaluation value from the input / output unit 530 based on a past transportation accident of the company. Further, for example, the enterprise logistics evaluation value management means 570 has predetermined information for associating the sensor data 800 including the abnormal value in the measured value 674 with the reading location 650 corresponding thereto and the reading location 650 and each data server 502. The corporate logistics evaluation value may be calculated from the above.

  In addition to the functions in the first embodiment, the reference frequency calculation element acquisition unit 540 transmits the enterprise logistics evaluation value acquisition request to the enterprise logistics evaluation value management unit 570 of each data server 502, and is transmitted as a response thereto. It has a function to receive enterprise logistics evaluation values.

  The predicted reference frequency calculation unit 550 further has a function of calculating the predicted reference frequency of the received sensor data 800 based on the corporate physical distribution evaluation value received by the reference frequency calculation element acquisition unit 540.

  The calculation of the predicted reference frequency is, for example, a value obtained by adding all the received corporate logistics evaluation values. Further, the predicted reference frequency may be further weighted based on the number of abnormal values described in the second embodiment.

  Next, the operation of the present embodiment will be described in detail with reference to FIGS.

  FIG. 7 is a flowchart showing the operation of the data server 502 of this embodiment.

  The operation of this embodiment is different from the flowchart of FIG. 4 describing the operation of the first embodiment in that step S105 is changed to steps S301 to S305.

    Subsequent to step S104, the reference frequency calculation element acquisition unit 540 selects one unselected address from the received address list (step S301).

  Subsequently, the reference frequency calculation element acquisition unit 540 transmits a corporate logistics evaluation value acquisition request to the corporate logistics evaluation value management unit 570 of the data server 502 having the selected address (step S302).

Upon receiving the enterprise logistics evaluation value acquisition request, the enterprise logistics evaluation value management means 570 transmits the enterprise logistics evaluation value to the data server 502 that is the transmission source of the enterprise logistics evaluation value acquisition request. (Operation steps of the data server 502 are not shown.)
Next, the reference frequency calculation element acquisition unit 540 receives the corporate logistics evaluation value transmitted from the corporate logistics evaluation value management unit 570 (step S303).

  The reference frequency calculation element acquisition unit 540 determines whether the acquisition process of the corporate physical distribution evaluation value has been performed for all addresses included in the received address list (step S304). If there is an address that has not been subjected to the acquisition process of the corporate physical distribution evaluation value (NO in step S304), the process returns to step S301. If the enterprise logistics evaluation value acquisition process has been performed for all addresses (YES in step S304), the process proceeds to step S305.

  The predicted reference frequency calculation means 550 calculates a predicted reference frequency based on the acquired corporate physical distribution evaluation value (step S305). Then, the process proceeds to S106.

  For example, the number of addresses included in the received address list is “3”, and the enterprise logistics evaluation values received from the enterprise logistics evaluation value management means 570 of the data server 502 corresponding to each address are “3” and “5”, respectively. ”,“ 2 ”, the predicted reference frequency calculation means 550 calculates the predicted reference frequency as the sum of the corporate physical distribution evaluation values“ S = 3 + 5 + 3 = 10 ”. Furthermore, the predicted reference frequency calculation means 550 sets the predicted reference frequency to “S × (P + 1) = 10 × (1 + 1) when the reference frequency calculation element acquisition means 540 counts the number of abnormal values“ P = 1 ”. = 20 "may be calculated.

  Instead of arranging the enterprise logistics evaluation value management means 570 in each data server 502, as shown in FIG. 8, the enterprise logistics evaluation value management means 770 for collectively managing the enterprise logistics evaluation values of each data server 502 is provided. The enterprise logistics evaluation value management server 700 may be a constituent element.

  Further, the distribution information address resolution device 400 has a corporate distribution evaluation value management means 770 which also functions as the corporate distribution evaluation value management server 700, and adds a corporate distribution evaluation value corresponding to the address list of the data server 502. You may make it return.

  The effect of the present embodiment described above is that a more accurate prediction reference frequency can be obtained in addition to the effect of the first embodiment.

  The reason is that the predicted reference frequency is calculated based on the corporate physical distribution evaluation value correlated with the reliability of the sensor data 800.

  In other words, in the actual logistics industry, it is conceivable that the delivery quality differs for each company. Therefore, when a certain product passes through a company with low delivery quality, it is considered that the possibility that the quality of the product is deteriorated increases. The sensor data 800 of an item with reduced quality has a higher probability of being accessed to investigate the cause of the reduced quality. In this embodiment, it is possible to cope with such a situation.

  Next, a fourth embodiment of the present invention will be described in detail with reference to the drawings.

  Referring to FIG. 9, the traceability system 903 according to the fourth embodiment of the present invention includes a portable storage device 200, a physical distribution information collection device 300, a physical distribution information address resolution device 400, and a data server 503. ing. The portable storage device 200, the distribution information collection device 300, and the distribution information address resolution device 400 are the same as those described in the first embodiment.

  Compared to the data server 501 of the first embodiment, a storage control unit 580 is added to the data server 503 of the present embodiment.

  The storage control unit 580 is configured to store the event data 600 and the event data 600 based on the event data 600 stored in the event data storage unit 510 and the predicted reference frequency added to the sensor data 800 stored in the sensor data storage unit 520, respectively. Control storage of sensor data 800.

  For example, when the event data 600 is deleted in order to prevent the storage allowable value of the event data storage unit 510 from being insufficient, the storage control unit 580 includes the event data 600 stored in the event data storage unit 510. The corresponding event data 600 having the lowest predicted reference frequency is selected and deleted.

  The effect of the present embodiment described above is that the optimum event data 600 and sensor data 800 can be selected as the sensor data 800 to be erased or compressed.

The reason is that the sensor data 800 to be deleted or compressed is selected based on the predicted reference frequency. That is, by adding the magnitude of the predicted reference frequency to the selection criteria of the unnecessary sensor data 800, the accessibility can be improved. It is possible to enable selection of unnecessary sensor data 800 based on the selection.

  Next, a fifth embodiment of the present invention will be described in detail with reference to the drawings.

  Referring to FIG. 10, a traceability system 904 according to the fifth embodiment of the present invention includes a portable storage device 200, a logistics information collection device 300, a logistics information address resolution device 400, and a data server 504. ing. The portable storage device 200, the distribution information collection device 300, and the distribution information address resolution device 400 are the same as those described in the first embodiment.

  Compared to the data server 501 of the first embodiment, the arrangement control unit 590 is added to the data server 504 of the present embodiment.

  The arrangement control unit 590 includes the predicted reference frequency added to the event data 600 already stored in the event data storage unit 510 and the sensor data 800 already stored in the sensor data storage unit 520 and the new event data 600. And based on the predicted reference frequency added to each of the sensor data 800, the data server 504 in which these are arranged is selected.

  The effect in the present embodiment described above is that an optimal arrangement location can be selected as the arrangement location of the event data 600 and the sensor data 800.

  The reason is that the arrangement location of the event data 600 and the sensor data 800 is selected based on the predicted reference frequency.

  That is, if the event data 600 and the sensor data 800 of each data server 504 are distributed and arranged so that the total number of predicted reference frequencies is equal, not the event data 600 and the sensor data 800, the event data 600 and the sensors based on accessibility are provided. It is possible to realize load distribution of data 800 to a plurality of data servers 504.

  Next, a sixth embodiment of the present invention will be described in detail with reference to the drawings. This embodiment is composed of basic elements of the present invention.

  Referring to FIG. 11, the data server 505 according to the sixth embodiment of the present invention includes a reference frequency calculation element acquisition unit 540 and a predicted reference frequency calculation unit 550.

  The reference frequency calculation element acquisition unit 540 acquires at least one reference frequency calculation element indicating the nature of the predicted reference frequency calculation target information.

  The predicted reference frequency calculation unit 550 calculates a predicted reference frequency for the corresponding predicted reference frequency calculation target information based on the reference frequency calculation element acquired by the reference frequency calculation element acquisition unit 540.

  The effect in the present embodiment described above is that it is possible to calculate the predicted reference frequency based on the attribute of the predicted reference frequency calculation target information itself to be accessed.

  This is because the reference frequency calculation element indicating the nature of the predicted reference frequency calculation target information is acquired, and the predicted reference frequency is calculated based on the reference frequency calculation element.

  Each component described in each of the above embodiments may cause a computer to execute a predetermined process by a program, for example.

  Each component described in each of the above embodiments does not necessarily have to be individually independent, and a plurality of components are realized as one module, or one component is realized as a plurality of modules. Alternatively, a configuration in which a certain component is a part of another component, a part of a certain component overlaps with a part of another component, or the like may be employed.

  Further, in each of the embodiments described above, a plurality of operations are described in order in the form of a flowchart, but the described order does not limit the order in which the plurality of operations are executed. For this reason, when each embodiment is implemented, the order of the plurality of operations can be changed within a range that does not hinder the contents.

  Furthermore, in each embodiment described above, a plurality of operations are not limited to being executed at different timings. For example, another operation may occur during the execution of a certain operation, or part or all of the execution timing of a certain operation and the execution timing of another operation may overlap.

  Furthermore, in each of the embodiments described above, a certain operation is described as a trigger for another operation, but the description does not limit all relationships between the certain operation and the other operations. For this reason, when each embodiment is implemented, the relationship between the plurality of operations can be changed within a range that does not hinder the contents. The specific description of each operation of each component does not limit each operation of each component. For this reason, each specific operation | movement of each component may be changed in the range which does not cause trouble with respect to a functional, performance, and other characteristic in implementing each embodiment.

  Each component in each embodiment described above may be realized by hardware, software, or a mixture of hardware and software, if necessary. May be.

  Further, the physical configuration of each component is not limited to the description of the above embodiment, and may exist independently, may exist in combination, or may be configured separately. May be.

  According to the embodiment of the present invention described above, for example, a plurality of traceability systems 901 to 904 for managing event data 600 and sensor data 800 (hereinafter simply referred to as data), selecting unnecessary management data, and managing data in a distributed manner. It is possible to solve the problem that the load is not made uniform among the data servers 501 to 504 based on the possibility of access of the data itself.

  More specifically, a general traceability system targets a large number of physical distributions and collects a large amount of data. Data collected at the time of distribution is stored in a data server for detailed investigation when trouble occurs later. The stored data will exceed the storage capacity of the data server unless it is deleted. Therefore, the data is erased or compressed.

  In such a case, if data having an old data collection time is selected, and deletion or compression is performed, there is a problem that data that is not referred to despite its large size exists for a long time, This causes a problem that data that continues to be referred to over time is erased or compressed quickly.

  The traceability systems 901 to 904 and the data servers 501 to 505 according to the present embodiment make it possible to avoid such problems.

  In addition, the portable storage device 200 accumulates the measurement history 670 until it arrives at the final delivery place (end point) of the normal article and is collected. Therefore, the data servers 501 to 504 acquire and store data including various information as the base is closer to the end point. For this reason, the data servers 501 to 504 at bases closer to the end point have a larger access load due to data acquisition.

  As a method of reducing such a load, a distributed arrangement has been performed in which the number of sensor data and the size of data managed by each data server are equalized using a distributed technology such as P2P.

  However, the reference frequency of each data is not uniform and is independent of the size of individual data. For this reason, there is a problem that the access load is not always reduced in the distributed arrangement in consideration of the equalization of the amount.

  The traceability systems 901 to 904 and the data servers 501 to 505 according to the present embodiment can solve the occurrence of such a problem.

  That is, according to the embodiment of the present invention, efficient data management is performed by calculating and adding an expected value of the frequency with which data is referred to the data collected using the portable storage device 200. Make it possible.

  The present invention can be applied to data management in a system that shares information among a plurality of data servers, as represented by a traceability system.

DESCRIPTION OF SYMBOLS 200 Portable storage apparatus 300 Physical distribution information collection apparatus 400 Physical distribution information address resolution apparatus 501 Data server 502 Data server 503 Data server 504 Data server 505 Data server 510 Event data storage means 520 Sensor data storage means 530 Input / output means 540 Reference frequency calculation element Acquisition means 550 Predictive reference frequency calculation means 560 Communication means 570 Enterprise logistics evaluation value management means 580 Storage control means 590 Placement control means 600 Event data 620 Identifier 640 Event step 650 Reading place 660 Tag location 670 Measurement history 671 Measurement start time 672 Measurement end time 673 Measurement interval 674 Measurement value 700 Enterprise logistics evaluation value management server 770 Enterprise logistics evaluation value management means 901 Traceability system 90 Traceability system 903 traceability system 904 traceability system

Claims (63)

A reference frequency calculation element acquisition unit for acquiring indicate to see the frequency calculating element the dispersion state of the storage of the prediction reference frequency calculation target information,
Data management system, characterized in that it comprises a prediction reference frequency calculation means based on the reference frequency calculation element the acquired, to calculate a prediction reference frequency for the previous SL prediction reference frequency calculation target information. A plurality of data servers;
The data management system according to claim 1, wherein each of the data servers includes a shared information storage unit that stores shared information that is shared among the data servers and that is related to the predicted reference frequency calculation target information.   The data management system according to claim 2, wherein the prediction reference frequency calculation target information includes attribute information indicating that the prediction reference frequency calculation target information is related to the shared information.   4. The data management system according to claim 2, wherein the predicted reference frequency calculation target information is the shared information.   5. The data management system according to claim 2, wherein the reference frequency calculation element acquisition unit acquires an existence state of a data server storing the shared information as the reference frequency calculation element. . Further comprising information collecting means,
The predicted reference frequency calculation target information is information generated by the information collecting unit based on information received from a portable storage device attached to an article, and includes event data including an identifier, an identifier, and a measurement history. The data management system according to claim 1, wherein the data management system is at least one of sensor data included therein. Event data storage means for storing the event data; sensor data storage means for storing the sensor data; and input means;
The data management system according to claim 6, wherein at least one of the event data and the sensor data designated by the input unit is used as the shared information. Further comprising information collecting means,
The predicted reference frequency calculation target information is information generated by the information collecting unit based on information received from a portable storage device attached to an article, and includes event data including an identifier, an identifier, and a measurement history. 6. The data management system according to claim 2, wherein the data management system is at least one of sensor data.   9. The data management system according to claim 8, wherein the shared information is at least one of the event data and the sensor data.   10. The data management system according to claim 8, further comprising a physical distribution information address resolution device that transmits an address list of a data server storing shared information in response to the received address resolution request. Event data storage means for storing the event data; sensor data storage means for storing the sensor data; and input means;
11. The data management system according to claim 8, wherein at least one of the event data and the sensor data specified by the input unit is used as the shared information.   The data management system according to claim 7 or 11, wherein at least one of the event data and the sensor data specified by the input unit is used as the predicted reference frequency calculation target information.   13. The data management system according to claim 1, further comprising a predicted reference frequency calculation target information storage unit that stores the predicted reference frequency in addition to the predicted reference frequency calculation target information.   The reference frequency calculation element acquisition unit acquires the presence state of a predetermined singular value included in the predicted reference frequency calculation target information as the reference frequency calculation element. The data management system described in Crab. It further comprises a corporate logistics evaluation value management means for storing the enterprise logistics evaluation value,
15. The data management system according to claim 1, wherein the reference frequency calculation element acquisition unit acquires a corporate logistics evaluation value stored in the corporate logistics evaluation value management unit as the reference frequency calculation element.   16. The data management system according to claim 1, further comprising an arrangement control unit that controls storage of the predicted reference frequency calculation target information based on the predicted reference frequency.   16. The data management system according to claim 1, further comprising an arrangement control unit that controls arrangement of the prediction reference frequency calculation target information based on the prediction reference frequency. Acquires shown to see the frequency calculating element the dispersion state of the storage of the prediction reference frequency calculation target information,
Data management method characterized in that based on the reference frequency calculation element the acquired, to calculate a prediction reference frequency for the previous SL prediction reference frequency calculation target information.     19. The prediction reference frequency calculation target information includes attribute information indicating that it is related to shared information that is shared among a plurality of data servers and related to the prediction reference frequency calculation target information. The data management method described.   The data management method according to claim 19, wherein the prediction reference frequency calculation target information is the shared information.   The data management method according to claim 19 or 20, wherein an existence state of a data server storing the shared information is acquired as the reference frequency calculation element.   The predicted reference frequency calculation target information is information generated based on information received from a portable storage device attached to an article, and includes event data including an identifier and sensor data including an identifier and a measurement history. The data management method according to claim 18, wherein the data management method is at least one of the following.   The data management method according to claim 22, wherein at least one of the event data and the sensor data is used as the shared information.   The predicted reference frequency calculation target information is information generated based on information received from a portable storage device attached to an article, and includes event data including an identifier and sensor data including an identifier and a measurement history. The data management method according to claim 19, wherein the data management method is at least one of the following.   The data management method according to claim 24, wherein the shared information is at least one of the event data and the sensor data.   26. The data management method according to claim 24, wherein at least one of the event data and the sensor data is used as the shared information.   27. The data management method according to claim 23, wherein at least one of the event data and the sensor data is used as the predicted reference frequency calculation target information.   28. The data management method according to claim 18, wherein the predicted reference frequency is added to the predicted reference frequency calculation target information and stored.   29. The data management method according to claim 18, wherein an existence state of a predetermined singular value included in the predicted reference frequency calculation target information is acquired as the reference frequency calculation element.   30. The data management method according to claim 18, wherein an enterprise logistics evaluation value is acquired as the reference frequency calculation element.   31. The data management method according to claim 18, wherein storage of the predicted reference frequency calculation target information is controlled based on the predicted reference frequency.   32. The data management method according to claim 18, wherein the arrangement of the predicted reference frequency calculation target information is controlled based on the predicted reference frequency. Acquires shown to see the frequency calculating element the dispersion state of the storage of the prediction reference frequency calculation target information,
A program characterized by causing performed based on the reference frequency calculation element the acquired, the process of calculating the prediction reference frequency for the previous SL prediction reference frequency calculation target information to the computer.     The prediction reference frequency calculation target information includes attribute information indicating that the prediction reference frequency calculation target information is related to shared information that is shared among a plurality of data servers and related to the prediction reference frequency calculation target information. The data evaluation device described.   The program according to claim 34, wherein the prediction reference frequency calculation target information is the shared information.   36. The program according to claim 34 or 35, which causes a computer to execute a process of acquiring an existence state of a data server storing the shared information as the reference frequency calculation element.   The predicted reference frequency calculation target information is information generated based on information received from a portable storage device attached to an article, and includes event data including an identifier and sensor data including an identifier and a measurement history. 34. The program according to claim 33, wherein the program is at least one of the following.   38. The program according to claim 37, further causing a computer to execute a process of using at least one of the event data and sensor data as the shared information.   The predicted reference frequency calculation target information is information generated based on information received from a portable storage device attached to an article, and includes event data including an identifier and sensor data including an identifier and a measurement history. 37. The program according to claim 34, wherein the program is at least one of the following.   40. The program according to claim 39, wherein the shared information is at least one of the event data and the sensor data.   41. The program according to claim 39 or 40, causing a computer to execute a process of using at least one of the event data and the sensor data as the shared information.   42. The program according to claim 38 or 41, further causing a computer to execute a process of setting at least one of the event data and the sensor data as the predicted reference frequency calculation target information.   43. The program according to claim 33, further comprising causing a computer to execute a process of adding the predicted reference frequency to the predicted reference frequency calculation target information and storing the information.   44. The computer according to claim 33, further comprising: causing a computer to execute a process of acquiring an existence state of a predetermined singular value included in the predicted reference frequency calculation target information as the reference frequency calculation element. Program.   45. The program according to claim 33, further comprising causing a computer to execute a process of acquiring a corporate physical distribution evaluation value as the reference frequency calculation element.   46. The program according to claim 33, further causing a computer to execute processing for controlling storage of the predicted reference frequency calculation target information based on the predicted reference frequency.   47. The program according to claim 33, further causing a computer to execute processing for controlling arrangement of the predicted reference frequency calculation target information based on the predicted reference frequency. A reference frequency calculation element acquisition unit for acquiring indicate to see the frequency calculating element the dispersion state of the storage of the prediction reference frequency calculation target information,
Data server characterized in that it comprises a prediction reference frequency calculation means based on the reference frequency calculation element the acquired, to calculate a prediction reference frequency for the previous SL prediction reference frequency calculation target information.
  49. The data server according to claim 48, further comprising shared information storage means for storing shared information that is shared among a plurality of data servers and that is related to the predicted reference frequency calculation target information.   50. The data server according to claim 49, wherein the prediction reference frequency calculation target information includes attribute information indicating that the prediction reference frequency calculation target information is related to the shared information.   51. The data server according to claim 49, wherein the predicted reference frequency calculation target information is the shared information.   52. The data server according to claim 49, wherein the reference frequency calculation element acquisition unit acquires the presence state of the data server storing the shared information as the reference frequency calculation element. . Further comprising information collecting means,
The predicted reference frequency calculation target information is information generated by the information collecting unit based on information received from a portable storage device attached to an article, and includes event data including an identifier, an identifier, and a measurement history. 49. The data server according to claim 48, wherein the data server is at least one of sensor data included therein. Event data storage means for storing the event data; sensor data storage means for storing the sensor data; and input means;
54. The data server according to claim 53, wherein at least one of the event data and the sensor data designated by the input means is used as the shared information. Further comprising information collecting means,
The predicted reference frequency calculation target information is information generated by the information collecting unit based on information received from a portable storage device attached to an article, and includes event data including an identifier, an identifier, and a measurement history. 53. The data server according to claim 49, wherein the data server is at least one of sensor data.   56. The data server according to claim 55, wherein the shared information is at least one of the event data and the sensor data. Event data storage means for storing the event data; sensor data storage means for storing the sensor data; and input means;
57. The data server according to claim 55 or 56, wherein at least one of the event data and the sensor data designated by the input means is used as the shared information.   58. The data server according to claim 54 or 57, wherein at least one of the event data and the sensor data designated by the input means is used as the predicted reference frequency calculation target information.   59. The data server according to claim 48, further comprising predicted reference frequency calculation target information storage means for storing the predicted reference frequency in addition to the predicted reference frequency calculation target information.   The said reference frequency calculation element acquisition means acquires the presence state of the predetermined singular value contained in the said prediction reference frequency calculation object information as said reference frequency calculation element, Any one of Claim 48 thru | or 59 characterized by the above-mentioned. The data server described in Crab. It further comprises a corporate logistics evaluation value management means for storing the enterprise logistics evaluation value,
61. The data server according to claim 48, wherein the reference frequency calculation element acquisition unit acquires a corporate logistics evaluation value stored in the corporate logistics evaluation value management unit as the reference frequency calculation element.   62. The data server according to claim 48, further comprising an arrangement control unit that controls storage of the predicted reference frequency calculation target information based on the predicted reference frequency.   The data server according to any one of claims 48 to 62, further comprising an arrangement control unit that controls arrangement of the prediction reference frequency calculation target information based on the prediction reference frequency.

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