CN113630477B - High-value data uplink system based on block chain prediction machine - Google Patents
High-value data uplink system based on block chain prediction machine Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
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Abstract
The invention discloses a high-value data uplink system based on a block chain prediction machine, which belongs to the technical field of block chains and comprises a node counting module, a screening and sorting module, a memory allocation module, an uplink analysis module and an uplink updating module; acquiring storage information on a block chain, acquiring the memory availability ratios of a plurality of sub-nodes according to an unstored memory and a stored memory in the storage information, and acquiring a node to be uplink and a first node sequencing set according to the memory availability ratios; acquiring a storage mean value according to first storage data in the storage information, and acquiring a second node sequencing set and a division sequencing set through the storage mean value; the invention also discloses a high-value data uplink method based on the block chain prediction machine; the method and the device are used for solving the technical problem that high-value data cannot be reasonably linked according to the memory use conditions of a plurality of sub-nodes in the existing scheme.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a high-value data uplink system and a method based on a block chain prediction machine.
Background
The prediction machine is just like a third-party data agent in the world of the blockchain, when a certain intelligent contract on the blockchain has a data interaction requirement, the fact that the prediction machine is required to do by the owner is to process a request provided by the intelligent contract in the blockchain and transmit some information and data out of the chain into the chain.
When the existing block chain data is subjected to chain loading, reasonable screening and classification are not carried out according to the memory use conditions of a plurality of sub-nodes on the block chain, so that high-value data with different occupation cannot be reasonably loaded and the chain loading effect of the high-value data is poor.
Disclosure of Invention
The invention aims to provide a high-value data uplink system and a method based on a block chain prediction machine, which solve the following technical problems: how to solve the technical problem that the high-value data cannot be reasonably uplinked according to the memory use conditions of a plurality of child nodes in the existing scheme.
The purpose of the invention can be realized by the following technical scheme:
the high-value data uplink system based on the block chain prediction machine comprises a node statistical module, a screening and sorting module, a memory allocation module, an uplink analysis module and an uplink updating module;
the node counting module is used for acquiring storage information on the block chain, wherein the storage information comprises first storage data and second storage data, and the first storage data comprises non-storage memories of a plurality of sub-nodes; the second storage data comprises a stored memory of a plurality of sub-nodes and sends storage information to the central node;
the screening and sequencing module is used for acquiring the memory availability ratios of a plurality of sub-nodes according to the non-stored memory and the stored memory, and marking the sub-nodes corresponding to the memory availability ratios not less than the preset standard availability ratio as nodes to be uplink linked; carrying out descending order arrangement on a plurality of nodes to be uplink according to the available memory rate to obtain a first node ordering set;
the memory allocation module is used for acquiring a storage mean value of an unstored memory according to first storage data in the storage information, calculating a difference value between the unstored memory and the storage mean value according to the unstored memories of the plurality of nodes to be uplink, obtaining a memory allocation value, analyzing the memory allocation value, obtaining a second node sequencing set, and performing uplink memory division on the second node sequencing set to obtain a division sequencing set;
the uplink analysis module is used for acquiring information to be uplink, acquiring value coefficients of different data in the information, matching the value coefficients with a preset value range to obtain selected data and alternative data, acquiring occupation of the selected data and marking the occupation as first occupation, and acquiring occupation of the alternative data and marking the occupation as second occupation; sorting the selected data in a descending order according to the first occupation memory to obtain a selected sorting set; performing descending order arrangement on the plurality of alternative data according to the second occupation memory to obtain an alternative ordering set;
and the uplink updating module is used for performing uplink on a plurality of selected data in the selected sorting set according to the divided sorting set and updating uplink data according to the selected sorting set.
Further, respectively aligning a plurality of the sub-unitsCarrying out value taking and marking on an unstored memory and a stored memory in a node, and marking the unstored memory as WCNi, wherein i =1, 2, 3.. n; marking the stored memory as YCNi by formula
And calculating and obtaining the memory availability of the plurality of child nodes.
Further, the specific steps of analyzing the memory allocation value include:
setting the nodes to be uplink linked corresponding to the memory allocation values larger than k as first uplink links, and arranging the first uplink links in a descending order to obtain a first uplink link set; setting the nodes to be uplink linked corresponding to the memory allocation value not greater than k as second uplink linked nodes, and arranging the second uplink linked nodes in a descending order to obtain a second uplink linked set; the first uplink set and the second uplink set form a second node sequencing set; k is a positive integer.
Further, the specific step of dividing the uplink memory for the second node ordered set includes:
acquiring a first uplink set and a second uplink set in a second node sequencing set;
respectively dividing the non-stored memories in the first uplink set and the second uplink set according to a preset memory division ratio to obtain a first divided memory and a second divided memory, setting the first divided memory as an uplink memory, and setting the second divided memory as a dynamic memory; the uplink memory is used for storing high-value data; the dynamic memory is used for storing other data;
classifying and combining a plurality of uplink memories and dynamic memories in the first uplink set to obtain a first uplink partition set; classifying and combining a plurality of uplink memories and dynamic memories in the second uplink set to obtain a second uplink partition set;
the first uplink partition set and the second uplink partition set form a partition ordering set.
Further, the specific step of obtaining the value coefficients of different data in the information includes:
obtaining different data in the information, obtaining data per unit timeThe request times and the request frequency are marked with QQCi; marking the request frequency as QQPi; by the formula
Calculating a value coefficient of the acquired data; where a1 and a2 are represented as different scaling factors and are both greater than zero.
Further, the specific step of matching the value coefficient with the preset value range includes: label the maximum value of the value range as J1; labeling the minimum value of the value range as J2; coefficient of worth SJXiComparison with value range:
if SJXiIf the value coefficient is more than J2, judging that the value of the data corresponding to the value coefficient is high, and setting the value coefficient as selected data;
if J2 is more than or equal to SJXiIf the value coefficient is more than J1, judging that the data value corresponding to the value coefficient is medium, and setting the data value as alternative data;
if J1 is more than or equal to SJXiAnd judging that the data value corresponding to the value coefficient is low.
Further, the specific step of uplink transmission of a plurality of selected data in the selected sorted set according to the sorted set includes:
acquiring a first occupation of a plurality of selected data in the selected sorting set, and respectively matching the first occupation with a plurality of uplink memories in the first uplink partition set and the second uplink partition set;
distributing the selected data of the first uplink position to an uplink memory of the first uplink position in the first uplink partition set for storage;
distributing the selected data of the second uplink to the uplink memory of the first uplink in the second uplink partition set for matching, and if the first memory of the selected data is not greater than the uplink memory, the uplink is successful; if the first memory of the selected data is larger than the uplink memory, the uplink fails, and the selected data is distributed to the uplink memory of the second bit of the first uplink partition set for storage;
and analogizing in sequence until the selected data in the sorting set is distributed to the uplink memory in the second uplink partition set for storage, thereby realizing dynamic uplink of a plurality of selected data in the selected sorting set.
Further, the specific step of updating the uplink data according to the alternative sorting set includes:
setting the selected data at the tail of the rows in the selected sorting set as first updating data, and setting the alternative data at the head and the tail of the rows in the alternative sorting set as second updating data; and when the value coefficient corresponding to the first updating data is smaller than the value coefficient corresponding to the second updating data, the first updating data is linked down, and the second updating data is linked up according to the corresponding second occupation storage, so that the uplink updating of the high-value data is realized.
The high-value data uplink method based on the block chain prediction machine comprises the following steps:
acquiring storage information on a block chain, wherein the storage information comprises first storage data and second storage data, and the first storage data comprises non-storage memories of a plurality of sub-nodes; the second storage data comprises a stored memory of a plurality of sub-nodes and sends storage information to the central node;
according to the non-stored memory and the stored memory, the memory availability ratios of a plurality of sub-nodes are obtained, and the sub-nodes corresponding to the memory availability ratios not less than the preset standard availability ratio are marked as nodes to be uplink linked; carrying out descending order arrangement on a plurality of nodes to be uplink according to the available memory rate to obtain a first node ordering set;
obtaining a storage mean value of an unstored memory according to first storage data in the storage information, calculating a difference value between the unstored memory and the storage mean value according to the unstored memories of a plurality of nodes to be subjected to chain loading to obtain a memory allocation value, analyzing the memory allocation value to obtain a second node sequencing set, and performing chain loading memory division on the second node sequencing set to obtain a divided sequencing set;
acquiring information to be linked, acquiring value coefficients of different data in the information, matching the value coefficients with a preset value range to obtain selected data and alternative data, acquiring occupation of the selected data and marking the occupation as first occupation, and acquiring occupation of the alternative data and marking the occupation as second occupation; sorting the selected data in a descending order according to the first occupation memory to obtain a selected sorting set; performing descending order arrangement on the plurality of alternative data according to the second occupation memory to obtain an alternative ordering set;
and carrying out chain loading on a plurality of selected data in the selected sorting set according to the divided sorting set, and updating the chain loading data according to the selected sorting set.
The invention has the beneficial effects that:
1. screening a plurality of sub-nodes according to the memory availability of the sub-nodes on the block chain to obtain nodes to be uplink-linked, so that the sub-nodes with more used stored memories do not carry out uplink of high-value data, and the influence of the sub-nodes with more used stored memories on the operation of the high-value data uplink is avoided; classifying a plurality of nodes to be uplink according to the storage mean value of the non-storage memory, so that the non-storage memories with different sizes are used for storing high-value data with different occupation, and the uplink storage of the high-value data is more reasonable and efficient; the method comprises the steps that the non-stored memory is divided according to the memory division ratio, so that high-value data and other data can be respectively stored in the non-stored memory without mutual influence, the overall effect of chaining the high-value data can be effectively improved, and the phenomenon that the running effect of the whole sub-node is influenced due to unreasonable distribution of the high-value data is avoided;
2. different data in the information to be uplink-linked are divided into selected data and alternative data according to the value coefficient, dynamic distribution is carried out according to a first account memory of the selected data and a plurality of uplink memories in a first uplink partition set and a second uplink partition set, the plurality of uplink memories in the first uplink partition set and the second uplink partition set can be used for uplink of high-value data, uplink distribution of the high-value data is more uniform, the situation that the use of the high-value data is influenced when a certain child node goes wrong is avoided, the alternative data can be changed into the selected data and uplink according to the change of the value coefficient, the subsequent update of the uplink of the high-value data is facilitated, and the uplink effect of the high-value data is improved.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of a high value data uplink system based on a blockchain prediction machine according to the present invention.
FIG. 2 is a block diagram of a high value data uplink method based on a blockchain prediction machine according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, the present invention is a high-value data uplink system based on a block chain prediction machine, including a node statistics module, a screening and sorting module, a memory allocation module, an uplink analysis module, and an uplink update module;
in this embodiment, according to the non-stored memory and the stored memory of a plurality of sub-nodes on the block chain, the memory availability of the plurality of sub-nodes is obtained and the plurality of sub-nodes are screened to obtain nodes to be linked, so that the sub-nodes with more stored memory use no high-value data linking; classifying a plurality of nodes to be uplink according to the storage mean value of the non-storage memory, so that the non-storage memories with different sizes store high-value data with different occupation; dividing the non-stored memory according to the memory division ratio, so that high-value data and other data can be respectively stored in the non-stored memory without mutual influence; different data in the information to be uplink-linked are divided into selected data and alternative data according to the value coefficient, the selected data are dynamically uplink-linked, and uplink data are updated according to the alternative data, so that the uplink effect of the high-value data is improved.
The node counting module is used for acquiring storage information on the block chain, wherein the storage information comprises first storage data and second storage data, and the first storage data comprises non-storage memories of a plurality of sub-nodes; the second storage data comprises a stored memory of a plurality of sub-nodes and sends storage information to the central node;
the screening and sequencing module is used for acquiring the memory availability ratios of the sub-nodes according to the non-stored memory and the stored memory, respectively taking values and marking the non-stored memory and the stored memory in the sub-nodes, and marking the non-stored memory as WCNi, wherein i =1, 2, 3.. n; marking the stored memory as YCNi by formula
Calculating and acquiring the memory availability of a plurality of child nodes;
the memory availability ratio is compared and matched with a preset standard availability ratio for screening each child node, and the child node corresponding to the memory availability ratio not less than the preset standard availability ratio is marked as a node to be uplink; carrying out descending order arrangement on a plurality of nodes to be uplink according to the available memory rate to obtain a first node ordering set;
for example, there is a child node A, B, C, D, where A has a total memory of 1000G, unused memory of 400G, and used memory of 600G; the total memory for storage of B is 2000G, the unused memory is 1300G, and the used memory is 700G; c, the total memory for storage is 3000G, the unused memory is 2000G, and the used memory is 1000G; d, the total memory for storage is 4000G, the unused memory is 3300G, and the used memory is 700G; the memory availability ratios corresponding to A, B, C, D are 2/3, 13/7, 2 and 33/7, respectively, and when the preset standard availability ratio is 1, the child node B, C, D corresponding to the memory availability ratio greater than or equal to 1 is the node to be uplink, and the child node a does not perform uplink operation of high-value data, because the used memory of the child node a is more used, which affects the processing speed of data, and the overall effect of uplink of high-value data can be effectively improved by screening each child node.
The memory allocation module is configured to obtain a storage average value of an unstored memory according to first storage data in the storage information, where the storage average value refers to a storage average value of an unstored memory of a node to be uplink linked, calculate a difference value between the unstored memory and the storage average value according to the unstored memories of a plurality of nodes to be uplink linked, obtain a memory allocation value, analyze the memory allocation value, and obtain a second node ordering set, where the specific steps include:
setting the nodes to be uplink linked corresponding to the memory allocation values larger than k as first uplink links, and arranging the first uplink links in a descending order to obtain a first uplink link set; setting the nodes to be uplink linked corresponding to the memory allocation value not greater than k as second uplink linked nodes, and arranging the second uplink linked nodes in a descending order to obtain a second uplink linked set; the first uplink set and the second uplink set form a second node sequencing set; k is a positive integer;
for example, the stored mean value corresponding to the node to be uplink B, C, D is 2200G, and the memory allocation value of the node-B to be uplink is-900G; the memory allocation value of the node C to be uplinked is-200G; the memory allocation value of the node D to be uplinked is 900G; k can be valued according to the stored mean value of the node to be uplink, and k can be valued as 100, so that the node to be uplink D is a first uplink node, and the nodes to be uplink B and C are second uplink nodes; the sorted nodes to be subjected to uplink transmission are grouped and arranged according to the non-stored memory and the storage mean value, so that the follow-up dynamic distribution of high-value data with different occupation is conveniently carried out, the nodes to be subjected to uplink transmission with more non-stored memory store high-value data with large occupation, the nodes to be subjected to uplink transmission with less non-stored memory transmit high-value data with small occupation, and the nodes to be subjected to uplink transmission with medium occupation in the non-stored memory are further dynamically distributed subsequently, so that the high-value data distribution effect is improved, and the unreasonable high-value data distribution is avoided, and the operation effect of the whole sub-node is further influenced.
Performing uplink memory division on the second node sequencing set to obtain a divided sequencing set; the method comprises the following specific steps:
acquiring a first uplink set and a second uplink set in a second node sequencing set;
respectively dividing the non-stored memories in the first uplink set and the second uplink set according to a preset memory division ratio to obtain a first divided memory and a second divided memory, setting the first divided memory as an uplink memory, and setting the second divided memory as a dynamic memory; the uplink memory is used for storing high-value data; the dynamic memory is used for storing other data;
classifying and combining a plurality of uplink memories and dynamic memories in the first uplink set to obtain a first uplink partition set; classifying and combining a plurality of uplink memories and dynamic memories in the second uplink set to obtain a second uplink partition set;
the first uplink partition set and the second uplink partition set form a partition ordering set.
For example, the unused memory of the node D to be uplink in the first uplink set is 3300G, the unused memories of the nodes B and C to be uplink in the second uplink set are 1300G and 2000G, and the preset memory division ratio may be 0.2, the unused memory of the node D to be uplink is divided into 660G and 2640G, where 660G is the first divided memory for storing high-value data, and 2640G is the second divided memory for storing other data; similarly, the unused memory of the uplink node B is divided into 260G and 1040G, where 260G is the first divided memory of the uplink node B and 1040G is the second divided memory of the uplink node B; the unused memory of the uplink node C is divided into 400G and 1600G, 40G is the first divided memory of the uplink node C, and 1600G is the second divided memory of the uplink node C; through carrying out one-step screening on unused memories in the screened nodes to be uplink-connected, the high-value data can acquire exclusive storage space, and uplink of the high-value data cannot influence operation of the nodes to be uplink-connected, for example, the high-value data occupies a distributable memory larger than the uplink node during uplink, which affects uplink of the high-value data and normal operation of the nodes to be uplink-connected.
The uplink analysis module is used for acquiring information to be uplink, acquiring value coefficients of different data in the information, acquiring request times and request frequency of the data in unit time, wherein the unit time can be 10min, and marking the request times with QQCi; marking the request frequency as QQPi; by the formula
Calculating a value coefficient of the acquired data; wherein a1 and a2 represent different scaling factors and are both greater than zero; the request frequency is the ratio of the request times of the data to the total times of all data requests;
matching the value coefficient with a preset value range, and marking the maximum value of the preset value range as J1; labeling the minimum value of the value range as J2; coefficient of worth SJXiComparison with value range:
if SJXiIf the value coefficient is more than J2, judging that the value of the data corresponding to the value coefficient is high, and setting the value coefficient as selected data;
if J2 is more than or equal to SJXiIf the value coefficient is more than J1, judging that the data value corresponding to the value coefficient is medium, and setting the data value as alternative data;
if J1 is more than or equal to SJXiIf so, judging that the data value corresponding to the value coefficient is low, and setting the data value as basic data; wherein, the basic data can become alternative data according to the change of the value coefficient; the alternative data can be changed into the selected data according to the change of the value coefficient and the uplink is connected, so that the subsequent update of the uplink of the high-value data is facilitated.
Acquiring the occupation of the selected data and marking the occupation as a first occupation, and acquiring the occupation of the alternative data and marking the occupation as a second occupation; sorting the selected data in a descending order according to the first occupation memory to obtain a selected sorting set; and performing descending order arrangement on the plurality of alternative data according to the second occupation memory to obtain an alternative ordering set.
In this embodiment, the data to be uplink is analyzed and classified according to the value coefficient, so that the data to be uplink is classified into high-value data capable of being uplink immediately and medium-value data capable of being uplink immediately, wherein the medium-value data to be uplink can be uplink in time according to the value coefficient, and the efficiency of high-value data uplink is improved.
The uplink updating module is used for performing uplink on a plurality of selected data in the selected sorting set according to the divided sorting set, and the specific steps comprise:
and acquiring a first occupation of a plurality of selected data in the selected sorting set, and respectively matching the first occupation with a plurality of uplink memories in the first uplink partition set and the second uplink partition set.
And allocating the selected data of the first uplink position to the uplink memory of the first uplink position in the first uplink partition set for storage.
Distributing the selected data of the second uplink to the uplink memory of the first uplink in the second uplink partition set for matching, and if the first memory of the selected data is not greater than the uplink memory, the uplink is successful; and if the first memory of the selected data is larger than the uplink memory, the uplink fails, and the selected data is distributed to the uplink memory of the second bit arranged in the first uplink partition set for storage.
And analogizing in sequence until the selected data in the sorting set is distributed to the uplink memory in the second uplink partition set for storage, thereby realizing dynamic uplink of a plurality of selected data in the selected sorting set.
And after the selected data is successfully uplink distributed to the second uplink divided set, the next selected data is distributed to the second uplink divided set for uplink, and the next selected data is redistributed to the first uplink divided set for uplink, so that the high-value data is subjected to cross uplink on the second uplink divided set and the first uplink divided set.
In this embodiment, dynamic allocation is performed according to the occupancy of the selected data and the plurality of uplink memories in the first uplink partition set and the second uplink partition set, so that the plurality of uplink memories in the first uplink partition set and the second uplink partition set can perform uplink of high-value data, uplink allocation of the high-value data is more uniform, influence on use of the high-value data when a certain child node fails is avoided, and safety of the high-value data is improved.
Updating the uplink data according to the alternative sorting set, which comprises the following specific steps:
setting the selected data at the tail of the rows in the selected sorting set as first updating data, and setting the alternative data at the head and the tail of the rows in the alternative sorting set as second updating data; and when the value coefficient corresponding to the first updating data is smaller than the value coefficient corresponding to the second updating data, the first updating data is linked down, and the second updating data is linked up according to the corresponding second occupation storage, so that the uplink updating of the high-value data is realized.
Example two
Referring to fig. 2, a method for high-value data uplink based on a blockchain prediction machine includes:
acquiring storage information on a block chain, wherein the storage information comprises first storage data and second storage data, and the first storage data comprises non-storage memories of a plurality of sub-nodes; the second storage data comprises stored memories of a plurality of sub-nodes, and storage information is sent to the central node.
According to the non-stored memory and the stored memory, the memory availability ratios of a plurality of sub-nodes are obtained, and the sub-nodes corresponding to the memory availability ratios not less than the preset standard availability ratio are marked as nodes to be uplink linked; and performing descending order arrangement on a plurality of nodes to be uplink according to the available memory rate to obtain a first node ordering set.
The method comprises the steps of obtaining a storage mean value of an unstored memory according to first storage data in storage information, calculating a difference value between the unstored memory and the storage mean value according to the unstored memories of a plurality of nodes to be subjected to chain loading to obtain a memory allocation value, analyzing the memory allocation value to obtain a second node sequencing set, and performing chain loading memory division on the second node sequencing set to obtain a division sequencing set.
Acquiring information to be linked, acquiring value coefficients of different data in the information, matching the value coefficients with a preset value range to obtain selected data and alternative data, acquiring occupation of the selected data and marking the occupation as first occupation, and acquiring occupation of the alternative data and marking the occupation as second occupation; sorting the selected data in a descending order according to the first occupation memory to obtain a selected sorting set; and performing descending order arrangement on the plurality of alternative data according to the second occupation memory to obtain an alternative ordering set.
And carrying out chain loading on a plurality of selected data in the selected sorting set according to the divided sorting set, and updating the chain loading data according to the selected sorting set.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (9)
1. The high-value data uplink system based on the block chain prediction machine comprises a node counting module, a screening and sorting module, a memory allocation module, an uplink analysis module and an uplink updating module, and is characterized in that the screening and sorting module screens and sorts a plurality of sub-nodes through acquired storage information to obtain a first node sorting set containing a plurality of nodes to be uplink; the memory allocation module calculates and divides a plurality of nodes to be uplink according to first storage data in the storage information to obtain a division sequencing set;
the uplink analysis module is used for acquiring information to be uplink, processing and arranging the information to be uplink, and obtaining a selected ordered set comprising a plurality of selected data and a standby ordered set comprising a plurality of standby data;
the uplink updating module is used for performing uplink on a plurality of selected data in the selected sorting set according to the divided sorting set, acquiring first occupation of the plurality of selected data in the selected sorting set, and respectively matching the first occupation with a plurality of uplink memories in the first uplink dividing set and the second uplink dividing set; the first uplink partition set and the second uplink partition set form a partition sequencing set;
distributing the selected data of the first uplink position to an uplink memory of the first uplink position in the first uplink partition set for storage; distributing the selected data of the second bit row to the uplink memory of the first bit row in the second uplink partition set for matching, and if the first memory of the selected data of the second bit row is not larger than the uplink memory, the uplink is successful; if the first memory of the selected data of the second bit row is larger than the uplink memory, the uplink fails, and the selected data of the second bit row is distributed to the uplink memory of the second bit row in the first uplink division set for storage;
and analogizing in sequence until the selected data in the selected sorting set is distributed to the uplink memory in the second uplink partition set for storage, thereby realizing dynamic uplink of a plurality of selected data in the selected sorting set.
2. The system of claim 1, wherein the stored information comprises a first stored data and a second stored data, the first stored data comprising an un-stored memory of a plurality of sub-nodes; the second stored data includes stored memory for a plurality of child nodes.
3. The system of claim 2, wherein the memory availability of a plurality of sub-nodes is obtained by storing information, and the sub-nodes corresponding to the memory availability not less than a predetermined standard availability are marked as to-be-uplink nodes; and performing descending order arrangement on a plurality of nodes to be uplink according to the available memory rate to obtain a first node ordering set.
4. The system of claim 3, wherein the average value of the non-stored memories is obtained according to the first stored data in the stored information, the difference between the average value and the non-stored memories of the plurality of nodes to be uplink-scheduled is calculated to obtain a memory allocation value, the memory allocation value is analyzed to obtain a second node ordered set, and the uplink memory partition is performed on the second node ordered set to obtain a partition ordered set.
5. The system of claim 4, wherein the value coefficients of different data in the information are obtained, the value coefficients are matched with a predetermined value range to obtain selected data and alternative data, and the selected sorted set and the alternative sorted set are obtained according to the selected data and the alternative data.
6. The system of claim 5, wherein the selected data is acquired and marked as a first occupancy and the alternative data is acquired and marked as a second occupancy; sorting the selected data in a descending order according to the first occupation memory to obtain a selected sorting set; and performing descending order arrangement on the plurality of alternative data according to the second occupation memory to obtain an alternative ordering set.
7. The system of claim 6, wherein the step of analyzing the memory allocation value comprises: setting nodes to be uplink linked corresponding to the memory allocation values larger than k as first uplink nodes and arranging the nodes in descending order to obtain a first uplink set; setting the nodes to be uplink-linked corresponding to the memory allocation values not greater than k as second uplink-linked nodes and arranging in descending order to obtain a second uplink-linked set; the first uplink set and the second uplink set form a second node ordered set.
8. The system of claim 7, wherein the step of matching the cost factor to a predetermined cost range comprises: labeling the minimum value of the value range as J1; label the maximum value of the value range as J2; coefficient of worth SJXiComparison with value range: if SJXiIf the value coefficient is more than J2, setting the data corresponding to the value coefficient as selected data; if J2 is more than or equal to SJXiIf J1 is greater, the data value corresponding to the value coefficient is set as the candidate data.
9. The system of claim 8, wherein the selected data at the end of the row in the selected ordered set and the candidate data at the end of the row in the candidate data are downlink and uplink according to the corresponding value coefficients to achieve uplink update of the high value data.
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