Distributed data management system and method based on blockchain
A distributed data and management system technology, applied in the direction of electrical digital data processing, instruments, hardware monitoring, etc., can solve the problems of no management, repeated invalid data, repeated data cannot be sorted, etc., and achieve the effect of improving data management efficiency
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Embodiment 1
[0072] Example 1: With limited conditions, the device operating rate analysis submodule sets the time for monitoring the operating status of different devices within the preset time period to be ti~tj, and set the operating time of device B within the above time period to 124h, and set the above The downtime of device B during this time is 78h, of which, the time for each device to be turned on but not sending data is set to 12h, and the device operating rate is set to K, according to the formula:
[0073]
[0074] It is calculated that the operation rate of device B that attempts to access the central server is 63.5%, and the device operation rate is 63.5% greater than 50%. The central server responds to the connection attempt request sent by device B.
Embodiment 2
[0075] Embodiment 2: With limited conditions, the equipment operation rate analysis sub-module in the preset time sets the time for monitoring the operation status of different equipment to be ti~tj, and the operation time of equipment B within the above time is set to 92h, and the above The downtime of device B during this time is 216h, among which, the time for each device to be turned on but no data transmission is set to 41h, and the device operating rate is set to K, according to the formula:
[0076]
[0077] It is calculated that the operation rate of device B that attempts to access the central server is 38.1%, and the device operation rate is 63.5% less than 50%. The central server rejects the connection attempt request sent by device B and no longer accepts the connection request of device B.
Embodiment 3
[0078] Example 3: Restricting conditions, setting key marks, operating equipment internal data similarity analysis sub-module analyzes the internal data of operating equipment A, segmenting the internal data of operating equipment A, and setting the segment data as L 1 , L 2 , L 3 , Compare the similarity of the divided segment data. Set the similarity of different segment data to 98%, 78%, 41%, set the similarity error rate in each segment of data to 2%, and set the actual similarity of each segment data to R(C n ), according to the formula:
[0079] R1(C n )=98%*(1-2%)≈96%
[0080] R2(C n )=78%*(1-2%)≈76%
[0081] R3(C n )=41%*(1-2%)≈40%
[0082] Calculate the actual similarity of each piece of data in the current device A, when R1(C n )≥93%, extract the two segment data L in which the similarity is compared 1 , L 2 , Re-conduct three similarity comparisons, set the re-comparison similarities to 95%, 94%, 96%, and set the current two segment data re-comparison similarity mean as Wh...
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