Intelligent power supply data sharing system based on cloud chain collaboration

Abstract

The invention relates to the technical field of data sharing, in particular to an intelligent power data sharing system based on cloud chain collaboration, which comprises a node chain type write-in module, a rhythm buffer identification module, a chain continuous path monitoring module, a cloud chain path optimization module and an intelligent sharing write-in module. According to the method, a time continuous chain segment set is generated by comparing timestamps and tail pointers, an index structure body is constructed by combining nodes and chain segment numbers, the static state of the tail pointers is periodically monitored to recognize buffer nodes, a dynamic sharing state set is formed, broken link paths are screened out through chain order difference values, and complete link order connection of the paths is guaranteed. A path sorting mechanism is constructed based on a task success record, the scheduling precision of a shared link is improved, a path number is bound with a target address, content is written according to a priority order, a sharing process full-link record is formed, and a monitorable and traceable sharing process is constructed by fusing chain segment relation recombination, state screening, path screening and preferable writing. And the data synchronization efficiency and sharing reliability are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of data sharing, and particularly to a smart power data sharing system based on cloud-chain collaboration. Background Art

[0002] The technical field of data sharing includes related technologies for realizing the orderly circulation and access control of multi-source heterogeneous data resources among different entities in a network environment. The core contents include data collection, preprocessing, identification, transmission, mapping, sharing, invocation, storage, and access permission management. By constructing a secure, trustworthy, and efficient data exchange mechanism, it promotes data interconnection among various industries to improve resource utilization and business collaboration efficiency. It is widely applied in fields such as government affairs, medical care, electric power, and transportation. Especially in a data environment involving multiple entities, it emphasizes mechanisms such as identity authentication, data rights confirmation, distributed storage, and permission control to achieve the interoperable use of data under controlled conditions.

[0003] Among them, a smart power data sharing system based on cloud-chain collaboration refers to a data system that adopts the fusion mechanism of cloud computing and blockchain to achieve the trustworthy sharing of various power data among different institutions or devices in the power energy management scenario. It covers the synchronous access of power operation data, the identity identification management of power distribution data, the recording and archiving of grid interaction data on the blockchain, and the controllable access of power-related entities to data. It converges power-side data through a multi-node parallel access method, completes the classification and annotation and immutable recording of power data through a distributed ledger structure, and then combines encryption mechanisms and access policy design to achieve the sharing permission division and data transmission collaboration among participants.

[0004] In the existing power data sharing scenarios, data access and permission allocation mostly rely on static configuration methods, lacking a dynamic identification and adjustment mechanism based on real-time data status and node behavior characteristics. In terms of node activity judgment, abnormal nodes are not screened out through continuous periodic status monitoring, which may lead to frequent access of inactive nodes to the shared network, occupying bandwidth resources and causing sharing path blockage. In the path scheduling strategy, regular path selection is adopted, lacking the recording and feedback evaluation of sharing success history, and unable to effectively screen out links with high stability, easily resulting in uncertain sharing results or scheduling deviations. In the write execution process, there is a lack of write order control based on the matching relationship between path priority and target nodes, leading to frequent problems such as duplicate sharing content coverage and path congestion. In terms of the recording mechanism, most solutions only complete content synchronization operations, do not construct a full-process link write log, and lack a transparent control basis for sharing behaviors. In complex power scenarios, if the tail pointer of a certain node is not updated for a long time and not identified and restricted in time, it will lead to the disorder of the shared data segment of the power supply, causing the synchronization failure of other dependent power nodes and seriously affecting data circulation efficiency and network collaboration effect. Summary of the Invention

[0005] The object of the present invention is to solve the disadvantages existing in the prior art, and a smart power data sharing system based on cloud-chain collaboration is proposed.

[0006] To achieve the above object, the present invention adopts the following technical solutions: The smart power data sharing system based on cloud-chain collaboration includes:

[0007] The node chain writing module obtains the power node timestamp and segment number information, detects the tail pointer time of the power node, compares the timestamp with the tail pointer time and judges the writing permission, constructs a time-continuous segment set structure by combining the power node number information and the segment number information, and generates an index-driven writing structure;

[0008] The rhythm buffer recognition module detects whether the tail pointer time remains stationary within a continuous period according to the tail pointer update period sequence of each power node in the index-driven writing structure. If the stationary state persists, the corresponding node is included in the buffer state cluster to obtain a writing rhythm buffer mapping table;

[0009] The chain sequence continuous path monitoring module reads the current chain sequence number and the previous cycle chain sequence number based on the path identifier corresponding to the node in the non-buffered state in the writing rhythm buffer mapping table, performs an equal value judgment according to the difference, screens the paths that meet the chain sequence continuity condition, and generates a continuous chain sequence sharing path set;

[0010] The cloud-chain path optimization module counts the number of successful path history sharing tasks in the continuous chain sequence sharing path set, sorts the paths by priority, determines the cloud-chain optimized path, enters it into the shared scheduling list, and generates a cloud-chain scheduling path sorting list.

[0011] As a further solution of the present invention, the index-driven writing structure includes a segment continuity identifier, a node index update mapping, and a writing permission determination flag. The writing rhythm buffer mapping table includes a buffer state identifier, a node sharing state flag, and a cycle stationary record. The continuous chain sequence sharing path set includes a path number set, a chain sequence matching identifier, and a path validity label. The cloud-chain scheduling path sorting list includes a path priority level, a shared scheduling serial number, and a scheduling list flag.

[0012] As a further solution of the present invention, the node chain writing module includes:

[0013] The time judgment sub-module collects the timestamp and segment number information generated by the local cache of the power node, reads the tail pointer time in the local index table of the power node, compares whether the timestamp has the time writing permission with the tail pointer time. If the timestamp is later than the tail pointer time, it is determined that the writing permission is available, and a writing permission determination result is obtained;

[0014] Based on the write permission determination result, if the index update sub-module determines that the permission is available, it combines the segment number information and the tail pointer time data, updates the tail pointer, arranges the segment number information in ascending order, and adds it to the end of the index table to obtain the new number sequence of the index table.

[0015] Based on the new number sequence of the index table, the structure generation sub-module constructs a time-continuous segment set structure based on the combined sorting of the power supply node number information and the segment number information, performs structure screening and sorting according to the combination order, and generates an index-driven write structure.

[0016] As a further solution of the present invention, the rhythm buffer recognition module includes:

[0017] Based on the tail pointer update cycle sequence of each power supply node in the index-driven write structure, the cycle extraction sub-module obtains the cycle time value of each node in the continuous write stage, constructs a mapping list of nodes and corresponding cycle times, and obtains a node cycle time sequence table.

[0018] Based on the node cycle time sequence table, the static judgment sub-module determines whether the time remains static according to the change of the tail pointer time of each node in the continuous cycle, and uses the formula:

[0019]

[0020] Calculate the change ratio R of the tail pointer time, and establish a buffer node number set according to the set of node numbers where the change ratio of the tail pointer time is less than the reference limit of the tail pointer change. Among them, t i is the tail pointer time of the i-th cycle, t- is the average value of the tail pointer times of all cycles, and x i is the number of write requests in the i-th cycle.

[0021] Based on the buffer node number set, the status mapping sub-module marks the nodes in the index-driven write structure as pending shared status, performs node and status label mapping, and establishes a write rhythm buffer mapping table.

[0022] As a further solution of the present invention, the chain sequence continuous path monitoring module includes:

[0023] Based on the path identifiers corresponding to the nodes in the non-buffered state in the write rhythm buffer mapping table, the path extraction sub-module reads the current chain sequence number and the previous cycle chain sequence number to obtain a chain sequence path number set.

[0024] Based on the chain sequence path number set, the chain sequence judgment sub-module analyzes the fluctuation trajectory of the chain sequence state based on the change characteristics between the current chain sequence number and the previous cycle chain sequence number, and uses the formula:

[0025]

[0026] Calculate the chain order fluctuation mapping value C, mark the paths where the chain order fluctuation mapping value is greater than the chain order consistency limit as discontinuous, remove the corresponding paths, and obtain the chain order continuous path index set, where a j is the current chain order label of the j-th path, and b j is the chain order label of the previous cycle of the j-th path, max(a j ) is the maximum value of the current chain order label, and min(b j ) is the minimum value of the chain order label of the previous cycle;

[0027] The path screening sub-module classifies and summarizes the path identifiers that meet the chain order continuous condition according to the chain order continuous path index set, and screens according to the sharing condition to perform path sequence and task sharing mapping, and generates a continuous chain order shared path set.

[0028] As a further solution of the present invention, the cloud chain path optimization module includes:

[0029] The task statistics sub-module, based on the continuous chain order shared path set, counts the number of successful historical shared tasks corresponding to each path, records the mapping of the path identifier and the corresponding number of successful times, and generates a path task success times set;

[0030] The priority judgment sub-module, based on the path task success times set, obtains the number of successful tasks and its position number of each path, and uses the formula:

[0031]

[0032] Calculate the path sorting priority value P, sort in descending order according to the size of the path sorting priority value, and obtain the path priority sorting sequence, where s k is the number of successful historical shared tasks of the k-th path, and k is the position number of the path in the path task set, represents the cumulative square root value after the number of successful times of each path is increased, and ∑ k (k - s k ) is the total deviation of the difference between the path number and its task ability;

[0033] The path annotation sub-module, based on the path priority sorting sequence, screens the path identifiers, marks the status as the cloud chain optimized path, and writes it into the shared scheduling list to generate a cloud chain scheduling path sorting list.

[0034] As a further solution of the present invention, the system further includes:

[0035] The intelligent sharing writing module sorts the cloud chain preferred paths according to the cloud chain scheduling path sorting list, reads the target node addresses corresponding to the end points of each path, synchronously writes the shared content to the target nodes in the path order, records the transmission status of the shared content of all participating paths and the update status of the target node linked list, and generates a power node sharing link record;

[0036] The power node sharing link record includes transmission data mapping, node linked list change information, and shared synchronization status logs.

[0037] As a further solution of the present invention, the intelligent sharing writing module includes:

[0038] The target positioning sub-module reads the target node addresses corresponding to the end points of each path based on all the path numbers marked as cloud chain preferred paths in the cloud chain scheduling path sorting list, extracts the binding information between the path numbers and the target nodes, performs a one-to-one correspondence mapping between the path numbers and the target nodes, and generates a path-node mapping set;

[0039] The content writing sub-module writes the shared content to the target nodes corresponding to the end points of each path in the path number order according to the path-node mapping set, records the synchronization order, data byte amount, and transmission status flag during the writing process, processes the conflicting paths and completes the path execution mark, and obtains a content synchronization performance value sequence;

[0040] The status recording sub-module checks the status of all shared content writing paths based on the content synchronization performance value sequence, extracts the linked list update results of each target node, and combines the path numbers, synchronization completion status, and node linked list change conditions to establish a power node sharing link record.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are:

[0042] In the present invention, by dynamically comparing timestamps with the time of the tail pointer to construct a time - continuous segment set structure, the problem of disordered writing caused by cache update delay can be avoided, ensuring the consistency of data synchronization in a multi - node environment. By combining the node number and the segment number to generate a structure that can drive indexing, the high - precision organization of segment relationships is realized, improving the retrieval efficiency of the data structure. Based on the continuous cycle monitoring of the static state of the node tail pointer, an intelligent recognition of the node buffer state is formed, and a cluster of node sharing states that can be determined is constructed, enhancing the dynamic recognition ability of node activity and potential lag states. By performing a chain - order difference check on non - buffered state paths, the complete connection of shared paths in the logical chain is ensured, avoiding the interruption of shared paths caused by chain - order confusion. By recording the actual number of successful shared tasks in the path history for priority sorting and evaluating paths with the ability to achieve tasks, the focused scheduling of shared link resources is realized. Binding the path number to the target node address and writing to the target node in sequence according to the priority, matching the shared content with the update status of the node linked list, a full - link recording mechanism for the sharing process is formed, improving the traceability transparency of the sharing result and the controllable update of the node link. Through segment logic reorganization, node rhythm monitoring, path status screening, and dynamic optimal scheduling, an efficient shared data structure system that can be recognized, monitored, determined, and traced is constructed, significantly improving the sharing quality and controllability of power data in a multi - institution collaborative scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is the system flow chart of the present invention;

[0044] Figure 2 is the flow chart of the node chain - type writing module of the present invention;

[0045] Figure 3 is the flow chart of the rhythm buffer recognition module of the present invention;

[0046] Figure 4 is the flow chart of the chain - order continuous path monitoring module of the present invention;

[0047] Figure 5 is the flow chart of the cloud - chain path optimization module of the present invention;

[0048] Figure 6 is the flow chart of the intelligent sharing writing module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0050] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0051] Please refer to Figure 1 , the intelligent power data sharing system based on cloud-chain collaboration includes:

[0052] The node chain writing module obtains the timestamp and segment number information generated by the local cache of the power node, detects the tail pointer time in the local index table of the power node, compares the timestamp with the tail pointer time and makes a writing permission judgment. If the timestamp is greater than the tail pointer time, it updates the tail pointer and records the corresponding segment number in ascending order at the end of the index table, constructs a time-continuous segment set structure by combining the power node number information and the segment number information, and generates an index-driven writing structure body;

[0053] The rhythm buffer recognition module detects whether the tail pointer time remains static within a continuous period according to the tail pointer update period sequence of each power node in the index-driven writing structure body. If the static state persists, it includes the corresponding node in the buffer state cluster, marks the shareable state of the power node as "pending", and obtains a writing rhythm buffer mapping table;

[0054] The chain sequence continuous path monitoring module reads the current chain sequence number and the previous cycle chain sequence number based on the path identifier corresponding to the non-buffered state node in the writing rhythm buffer mapping table, performs an equal value judgment through the difference between the two. If the difference is not equal to 1, it marks the path state as chain sequence discontinuous and does not have the qualification to undertake the sharing task. It screens the paths that meet the chain sequence continuity conditions and generates a continuous chain sequence sharing path set;

[0055] The cloud-chain path optimization module counts the successful times of historical sharing tasks for each path in the continuous chain sequence sharing path set, sorts the priorities of all paths, marks the paths with the top 30% of the priority levels as "cloud-chain optimized paths", enters them into the sharing scheduling list, and generates a cloud-chain scheduling path sorting list;

[0056] The intelligent sharing writing module sorts the path numbers marked as "cloud chain preferred path" in the cloud chain scheduling path sorting list, reads the target node addresses corresponding to the end points of each path, synchronously writes the shared content to the target nodes in the path order, records the transmission status of the shared content of all participating paths and the update status of the target node linked list, and generates a shared link record of the power node.

[0057] The index-driven writing structure includes a segment continuity identifier, a node index update mapping, and a writing permission determination flag. The writing rhythm buffer mapping table includes a buffer status identifier, a node sharing status flag, and a periodic stationary record. The continuous chain sharing path set includes a path number set, a chain matching identifier, and a path validity label. The cloud chain scheduling path sorting list includes a path priority level, a shared scheduling serial number, and a scheduling list flag. The shared link record of the power node includes a transmission data mapping, node linked list change information, and a shared synchronization status log.

[0058] Please refer to Figure 2 , the node chain writing module includes:

[0059] The time judgment sub-module collects the timestamp and segment number information generated by the local cache of the power node, reads the tail pointer time in the local index table of the power node, compares whether the timestamp and the tail pointer time have the time writing permission. If the timestamp is later than the tail pointer time, it is determined that the writing permission is available, and the writing permission determination result is obtained;

[0060] Collect the timestamp and segment number information generated by the local cache of the power supply node. First, extract the timestamp field of each data record in the buffer. The timestamp is recorded in a standard format. For example, 14:32:08 on April 16, 2024, when converted to the number of seconds since the system startup, it is the timestamp value. Assume that the timestamp of a certain record is 135028 seconds and the segment number is segment number L1201. Then, read the current tail pointer time from the local index table of the power supply node. Assume that the tail pointer time is 134950 seconds. Compare the two to determine whether the timestamp is later than the tail pointer time, that is, 135028 > 134950. If it holds, write permission is granted; in the edge energy management scenario, if the new record data generated by a certain power supply unit in the edge data cache is 135028 seconds, then it is necessary to compare the time relationship between it and the tail pointer of 134950 seconds. Only when the timestamp moves forward, that is, the current record does not belong to historical old records, is it considered that the segment write is valid this time; the judgment logic is that the timestamp difference should be greater than 0. In actual applications, a time offset judgment reference value will be set. For example, if the reference value is set to 10 seconds, then if the time difference is less than 10 seconds, it is considered data redundancy caused by synchronization delay and writing is prohibited. The setting of this reference value can be jointly estimated through the node synchronization frequency and the cache refresh period. For example, the node synchronizes once every 30 seconds and the cache retention period is 90 seconds. Therefore, the reference value is reasonably set between 10 and 20 seconds; taking an example, if the current record timestamp is 135028 seconds and the tail pointer time is 134950 seconds, then the time difference is 78 seconds, which is higher than the reference value range, confirming the write permission, and finally obtaining the write permission judgment result.

[0061] According to the write permission judgment result, if the permission is determined to be granted, the index update sub-module combines the segment number information and the tail pointer time data, updates the tail pointer, and adds the segment number information to the end of the index table in ascending order to obtain the new number sequence of the index table.

[0062] According to the write permission determination result, if it is confirmed that the current timestamp is greater than the tail pointer time and the difference meets the reference value condition, continue to call the corresponding segment number information, add it to the end of the power node index table, and perform the update operation of the tail pointer time field. The updated value is the current recorded timestamp of 135028 seconds. When performing the operation of inserting the segment number, it is necessary to determine whether the number already exists at the end of the current index table. If it does not exist, insert it in ascending order of the number. For example, if the existing segment number sequence is L1199, L1200, and the current new addition is L1201, there is no need to rearrange and it can be inserted directly. If the current new addition number is L1198, it should be re-sorted to form the sequence L1198, L1199, L1200. The segment numbers in the index table are combined into a one-dimensional number array in lexicographical order for subsequent chain positioning and data order organization. The ascending order judgment rule is to sort after converting the numeric part in the number string to an integer. In the actual embedded scenario, an embedded processor can be used to intercept and numericalize the segment number string during the write stage. For example, for the string "L1201", the last three digits are intercepted as 1201 and compared with 1200 at the end of the index table. If it is larger, it is directly appended. At the same time, the tail pointer time field is updated synchronously with the value of 135028 seconds written. After the data structure update is completed, the new added number sequence in the index table becomes L1201, and the timestamp information, source node number, and related attribute fields associated with this segment number are recorded in the structure. Finally, the new added number sequence in the index table is obtained.

[0063] The structure generation sub-module constructs a time-continuous segment set structure based on the new added number sequence in the index table and the combined sorting of the power node number information and the segment number information, filters and organizes the structure according to the combination order, and generates an index-driven write structure.

[0064] Add a new number sequence L1201 according to the index table, and combine its timestamp of 135028 seconds with the power supply node number it belongs to. For example, if the node number is set to N07, perform segment data combination and sorting processing to form a time-continuous segment set structure. In the actual power grid operation system, when multiple power supply nodes write data to the central index table synchronously, it is necessary to sort and merge according to the time sequence to ensure the time sequence consistency of the chain record structure. For example, if the previous segment number is L1200 and the corresponding time is 134950 seconds, the new segment is L1201 and the time is 135028 seconds, then it can be confirmed that this segment is a time-continuous segment; during the sorting process, the timestamp is used as the primary key for ascending sorting. If there is an abnormal jump or regression of the timestamp, for example, a node inserts a segment number L1202 but the time is 134800 seconds, then it is excluded from the time-continuous segment set. In the structure construction, it is judged whether there is a time jump by identifying whether the difference between timestamps is greater than the preset interval threshold (such as set to 60 seconds). In the actual construction process, the segment numbers and node numbers of each segment are combined into a two-dimensional array, and sorting processing is performed according to the timestamp field in the array. For example, the two-dimensional array format is:

[0065] [L1199, N05, 134800], [L1200, N06, 134950], [L1201, N07, 135028];

[0066] The time-continuous segment set only retains the last two items; after sorting, load this time-continuous structure set into the index-driven write structure. The record fields in this structure include segment number, power supply node number, timestamp, segment status flag, write status bit, etc., and finally generate an index-driven write structure.

[0067] Please refer to Figure 3 , the rhythm buffer recognition module includes:

[0068] The period extraction sub-module updates the period sequence based on the tail pointers of each power supply node in the index-driven write structure, obtains the period time value of each node during the continuous write stage, and constructs a mapping list of nodes and corresponding period times to obtain a node period time sequence table;

[0069] Based on the tail pointer update cycle sequence of each power supply node written into the structure driven by the index, the operation of obtaining the cycle time of the power supply node needs to sequentially extract the tail pointer timestamps from the structure according to the node numbers to form an indexed time array. For nodes with a cycle number greater than 5, the adjacent differences of the timestamps are respectively extracted as the cycle values, and the sliding window mode is used to identify the start and end boundaries of the cycle and generate the cycle time array. For example, for the power supply node numbered N1, its last 6 tail pointer timestamps are 1000, 1003, 1006, 1009, 1012, 1015 respectively, then the cycle sequence is 3, 3, 3, 3, 3, indicating that this node has a stable update characteristic. Further, the cycle sequence is merged with the node number to form a mapping structure, and the storage format is in the form of key-value pairs, where the key is the node number and the value is the cycle array. After organizing all the node information, a complete set of cycle time data sets is formed. For each set of cycle time data, it is also necessary to check whether there are abnormal data jumps or zero-interval data, and the entries with a cycle less than 1 or greater than the upper limit of the preset interval are excluded. For example, when the preset upper limit is set to 30 seconds, if the cycle value is 50, it is marked as abnormal and excluded. The cycle lower limit is uniformly set to 1 second. According to the above criteria, the cycle mapping structure of each node is constructed as shown in Table 1.

[0070] Table 1 Cycle Time Mapping Table

[0071] Node number Periodic sequence (unit: second) N1 3，3，3，3，3 N2 4，4，4，3，4 N3 2，3，2，2，3

[0072] Table 1 lists the tail pointer update cycle time sequence data of some nodes, showing the rhythm stability information of the nodes after cycle calculation. The mapping structure can be used for subsequent judgment of node behavior to obtain the node cycle time sequence table.

[0073] The static judgment sub-module judges whether the time remains static according to the node cycle time sequence table and the change of the tail pointer time of each node in consecutive cycles, using the formula:

[0074]

[0075] Calculate the ratio R of the change in the tail pointer time. According to the set of node numbers with the ratio of the change in the tail pointer time less than the reference limit of the change in the tail pointer, establish a set of buffer node numbers, where, t i is the tail pointer time of the i-th cycle, is the average value of all cycle tail pointer times, x i is the number of write requests in the i-th cycle;

[0076] According to the node cycle time series table, analyze each node cycle time series to determine whether the tail pointer is in a static state. It is necessary to calculate the cycle time difference value and evaluate the change amplitude based on this. For the same node, the smaller the time difference of the tail pointer between consecutive cycles, the more likely it is to be in a static state. First, extract the time series t of each node i , measure the change using the sum of absolute differences, and further combine and write the request volume x i , and use the following simplified innovation formula to evaluate the change of the tail pointer. For node N1, if its 6 timestamps are 1000, 1003, 1006, 1009, 1012, 1015, and the corresponding write request numbers are 2, 1, 2, 2, 1, 2, then the calculation of each parameter is as follows:

[0077] ∑ i |t i -t i-1 | = 3 + 3 + 3 + 3 + 3 = 15;

[0078]

[0079]

[0080]

[0081] Substitute into the formula to get:

[0082]

[0083] Among them, the set tail pointer change threshold of 2.5 comes from the maximum expected range of the tail pointer rhythm fluctuation value in the static evaluation stage. The setting basis of this value is that the average value of the node write request volume does not exceed 3 times / cycle during the stable operation period of the system, and the offset time of the tail pointer between adjacent cycles does not exceed 5 seconds. At this time, after 500 groups of sample evaluations, 75% of the distribution of the fluctuation ratio falls in the interval of 2.0 to 2.5. Combining this statistical result and the abnormal write impact situation in the node fluctuation time series, in order to prevent misidentification, the threshold is set to the upper bound value of 2.5 to enhance the stability of buffer node recognition. This threshold fluctuates synchronously with the write request quantity and the standard deviation of the tail pointer. If the node write frequency increases, the fluctuation threshold needs to be increased synchronously to avoid normal nodes being mis-incorporated into the buffer cluster. This value is compared with the change ratio obtained by node N1. Since it is lower than the threshold, node N1 is judged as a static state node, and its number is recorded and entered into the buffer node number set. This result shows that node N1 has a stable rhythm in the current write cycle and has the possibility of being incorporated into the buffer state, and a buffer node number set is established.

[0084] In the above formula, the numerator is the sum of the absolute values of the differences between the cycles in the tail pointer time series, which is used to measure the total change range of the node tail pointer in consecutive cycles and reflect whether the rhythm has a jump. The denominator part adopts a square root structure to suppress the expansion effect of data under scale changes. The first term is the sum of the squares of the number of write requests in each cycle, which represents the accumulation degree of the write intensity and is used to comprehensively consider the interference of the system write density on the rhythm stability. The second term is the sum of the deviations of the tail pointer time from its average value, which is used to describe its overall fluctuation trend. A joint measure of the change range is constructed through the sum of the two terms. Finally, by jointly ratioing the change range and the square root form of the interference, a standardized index is formed to judge the stability degree of the state of the tail pointer in the node cycle write. This structure can effectively jointly model local mutations and overall fluctuations, ensuring that the identification of rhythm buffering has discrimination ability.

[0085] Based on the set of buffer node numbers, the state mapping sub-module marks the nodes in the set as pending shared state in the index-driven write structure, performs node-state label mapping, and establishes a write rhythm buffer mapping table.

[0086] Based on the set of buffer node numbers, search for and mark all the nodes in the set in the index-driven write structure, update their shared state fields to the "pending" state, and then generate a structure mapping relationship according to the node number and state marking information, uniformly identify the corresponding fields in the structure, and output them to the rhythm buffer mapping file. In the construction of the write rhythm buffer mapping table, the key-value mapping relationship between each node number and its shared state should be retained, and the format should be consistent. For example, the key is the node number and the value is "pending", and the write rhythm buffer mapping table is obtained.

[0087] Please refer to Figure 4 , the chain-order continuous path monitoring module includes:

[0088] Based on the path identifiers corresponding to the nodes in the non-buffered state in the write rhythm buffer mapping table, the path extraction sub-module reads the current chain-order label and the previous cycle's chain-order label to obtain a set of chain-order path labels.

[0089] Based on the path identifier corresponding to the node in the non-buffered state in the write rhythm buffer mapping table, it is necessary to first establish a mapping relationship between the path identifier and the node state. During execution, the node state field in the write rhythm buffer mapping table is matched with the path mapping field one by one, and all nodes with a "normal" state are screened out, and their corresponding path numbers are extracted. For example, if there are node numbers P1 to P5 in the table, among which P1, P3, and P5 are in the "non-buffered" state, and their corresponding path numbers are L1, L3, and L5 respectively, then the paths L1, L3, and L5 need to be extracted. As the subsequent processing object, the current chain number and the previous cycle chain number of these paths are extracted respectively. The data field is usually the current value and historical value in the chain field. For example, the current chain of path L1 is 12, and the chain of the previous cycle is 11, the current chain of path L3 is 9, and the previous cycle is 8, and the current chain of path L5 is 15, and the previous cycle is 14, that is, the chain data pairs (12, 11), (9, 8), and (15, 14) are formed. The above process can be organized into a path-corresponding chain data set, which can be stored in a structured table for easy execution. The example is as follows:

[0090] Table 2 Chain path number table

[0091] Path number Current chain number Previous cycle chain number L1 12 11 L3 9 8 L5 15 14 As shown in Table 2, the establishment of the path chain data pair provides a basis for the subsequent calculation of the chain difference. Next, the chain label difference is processed, and the current chain and the previous cycle chain are read as fields respectively. The difference is calculated by subtraction, and the ab operation is performed on each path, where a represents the current chain and b represents the previous cycle chain. Taking path L1 as an example, the difference is 12-11=1, the difference of path L3 is 9-8=1, and the difference of path L5 is 15-14=1. If the difference of a path is not 1, it means that the chain continuity is interrupted, and the path needs to be marked as "chain discontinuous". In this example, since the chain difference of all paths is 1, no path enters the discontinuous path set, and the obtained chain path label set is the normal chain path set, which is called the chain path label set.

[0092] The chain judgment submodule is based on the chain path label set and the change characteristics between the current chain label and the previous cycle chain label to analyze the chain state fluctuation trajectory using the formula:

[0093]

[0094] Calculate the chain order fluctuation mapping value C, mark the paths whose chain order fluctuation mapping value is greater than the chain order consistency limit as discontinuous, remove the corresponding paths, and obtain the chain order continuous path index set, where a j is the current chain number of the j-th path, b j is the chain number of the previous cycle of the j-th path, max(a j) is the maximum value of the current chain number label, min(b j ) is the minimum value of the chain number label in the previous cycle;

[0095] Based on the set of chain number path labels, obtain the current chain number a of the path j and the chain number b in the previous cycle j , and construct a set of chain number change status by combining path identification information. Subsequently, introduce an evaluation index for chain number continuity, form an evaluation formula through the sum of the squared differences of the chain number labels and the sum of their absolute differences, and construct a segmented range term by combining the maximum value of the current chain number and the minimum value of the previous cycle. For calculation, it is necessary to clarify each path parameter. The parameters corresponding to paths L1, L3, and L5 in Table 3 are as follows:

[0096] Current chain number: a1 = 12, a2 = 9, a3 = 15;

[0097] Chain number in the previous cycle: b1 = 11, b2 = 8, b3 = 14;

[0098] Substitute the above data into the formula for calculation:

[0099] Calculate the sum of the squared differences:

[0100]

[0101]

[0102]

[0103]

[0104] Calculate the sum of the absolute differences:

[0105] |a1 - b1| = 1;

[0106] |a2 - b2| = 1;

[0107] |a3 - b3| = 1;

[0108] ∑|a j -b j | = 1 + 1 + 1 = 3;

[0109] Calculate the range term:

[0110] max(a j ) = 15;

[0111] min(b j ) = 8;

[0112] max(a j ) - min(b j ) = 7;

[0113] Substitute into the formula:

[0114]

[0115] The calculated result is C = 120.75, and the preset chain order consistency limit is set to 80. This setting is based on the actual corresponding relationship between the chain order stability and the jump frequency during the continuous load-bearing process of the path. Specifically, in the standard continuous writing stage of the system, the difference in the chain order within 5 to 6 cycles of a single path usually ranges from 1 to 2. If the sum of the squared differences in the chain order exceeds 60, and at the same time the range term is above 6, it indicates that there is a cross-cycle jump phenomenon in the path, which is likely to cause synchronization anomalies. Therefore, the chain order consistency limit is set to 80. The limit value is positively correlated with the amplitude and frequency of the chain order change of the path. That is, when the chain order changes frequently but the difference fluctuation is less than the normal range, the C value remains below the threshold. When the jump between chain orders increases or accumulates continuously, the C value rises rapidly and exceeds the boundary. If the chain order change term exceeds 4-cycle changes and the range is greater than 6, the limit value should not be lower than 80. Therefore, when C > 80, it is determined that the chain order fluctuates severely and the chain order continuity is interrupted. The benefit of the formula is that by constructing a non-linear fluctuation term through the squared difference and combining it with the range to form a chain order deviation penalty term, it can amplify the abnormal jump behavior on the critical path and strengthen the chain order continuous determination boundary. Therefore, in the current data, the calculated result C = 120.75 > 80, indicating that the chain order continuity is damaged, there is a jump behavior in the current path set, and the generated result is the chain order continuous path index set.

[0116] The formula first sums the differences between the square of the current chain order of each path and the square of the chain order in the previous cycle to form the numerator part of the formula. Its core is to amplify the volatility of the chain order change. The square operation can strengthen the proportion of abnormal chain order jumps in the overall change. Subsequently, the denominator part is composed of the sum of the absolute values of the differences between the current chain order and the previous chain order plus one. The plus-one operation avoids the denominator being zero, and at the same time, the accumulation of the absolute values of the differences can reflect the overall continuity level of the path. If the chain order remains stable, this value is small, thereby increasing the relative weight of the volatility and enhancing the recognition sensitivity. Finally, it is multiplied by the difference between the maximum value of the current chain order and the minimum value of the chain order in the previous cycle, that is, the range term. This term reflects the chain order coverage range of the path within the cycle span. If the range increases significantly, it usually corresponds to the chain order fault of the jump path. Therefore, through the combination of the three items to form a multiplication-division composite structure, while expressing the chain order fluctuation intensity of the path, it integrates the continuity degree and the distribution density, so as to realize the three-dimensional evaluation of the chain order continuity.

[0117] The path screening sub-module classifies and summarizes the path identifiers that meet the chain order continuous conditions according to the chain order continuous path index set, and screens according to the sharing conditions to perform the path sequence and task sharing mapping, generating a continuous chain order shared path set;

[0118] According to the chain - order continuous path index set, summarize the path numbers of each path that meets the chain - order continuous condition. During the path screening process, first extract the path identifiers that have not been eliminated from the chain - order path label set. For example, if paths L1 and L3 have not been eliminated, they are summarized into a shared path set. At the same time, establish the association relationship between the path and the task assignment field, and construct a mapping table from the path number to the task acceptance status in the database structure. The task acceptance status field is initially set to "candidate", and in the subsequent process, it can be updated by the task scheduling module according to dimensions such as the sharing degree. The current state record result is output as a combined set of paths and sharing status, and the finally generated structure is the continuous chain - order shared path set.

[0119] Please refer to Figure 5 , the cloud - chain path optimization module includes:

[0120] The task statistics sub - module, based on the continuous chain - order shared path set, counts the number of successful historical shared tasks corresponding to each path, and records the mapping between the path identifier and the corresponding number of successful times, generating a set of path task success times;

[0121] Based on each path in the continuous chain - order shared path set, obtain the unique identifier number of each path, respectively extract the shared task records of each path in the system log, and count the number of tasks determined to be successful among all historical shared tasks participated in by this path. During the execution process, first access the historical shared log structure body, extract the path identifier and task status information fields recorded in the structure body. The task status field determines whether it is a successful task through the system confirmation flag field. For example, if the task status is "1", it means the task is completed and is successful, otherwise it is a failure. Scan each path in turn, accumulate the number of successful tasks, and obtain its corresponding number of successful times. For example, if path "P1" has completed 15 tasks in the past 20 schedules, its number of successful times is 15. If path "P2" has participated in 10 tasks and only completed 3 tasks, its number of successful times is 3. After counting the number of successful tasks of all paths in a similar way, form a mapping data structure with the result and the path number for subsequent path sorting calculations, and obtain the set of path task success times.

[0122] The priority judgment sub - module, based on the set of path task success times, obtains the number of successful tasks and its position number of each path, and uses the formula:

[0123]

[0124] Calculate the path sorting priority value P, and perform a descending order arrangement according to the size of the path sorting priority value to obtain the path priority sorting sequence. Among them, s k is the number of successful historical shared tasks of the k - th path, and k is the position number of the path in the path task set. Represents the cumulative square root value after the gain of the number of successful times for each path, ∑ k (k - s k ) is the total deviation of the difference between the path number and its task ability;

[0125] Based on the set of path task success times, prioritize and score the paths through a custom priority sorting structure to obtain the following sample data (see Table 3):

[0126] Table 3 Path Priority Sorting Calculation Parameter Table

[0127] Path number Historical success times (si) Path position number (i) A1 8 1 B2 5 2 C3 12 3 D4 3 4 E5 6 5

[0128] As shown in Table 3, the number of successful times of path A1 is 8, and its position number is 1. Substitute each value into the formula for specific calculation:

[0129] Calculation of the numerator

[0130]

[0131]

[0132] Calculation of the denominator

[0133] |∑(k - s k )| + 1 = |(1 - 8) + (2 - 5) + (3 - 12) + (4 - 3) + (5 - 6)| + 1;

[0134] = |-7 - 3 - 9 + 1 - 1| + 1 = |-19| + 1 = 20;

[0135] Final calculation:

[0136] P = 13.71 ÷ 20 = 0.6855;

[0137] This result indicates that the comprehensive sorting priority value of all paths under the current path set is 0.6855. The larger the value, the better the overall task success performance of the path and the more consistent the number matching performance. Subsequently, the paths can be sorted based on this value to obtain the path priority sorting sequence.

[0138] The operation logic of the formula is constructed based on the consistency between the path task execution history and the number order. Its core idea is to consider both the historical success performance of the path and its position number in the path set. Among them, the numerator part emphasizes the non - linear growth effect of the path execution times by taking the square root of the number of successful times s of each path i after adding 1 and then summing, that is, as the number of successful times increases, its impact on the priority value gradually weakens in a form of slowing growth, avoiding a single high - success path from having too much interference on the overall sorting structure; while the denominator part uses the path number i and the corresponding number of successful times s iThe structure of taking the absolute value of the sum of the differences and adding 1 is intended to measure the degree of deviation between the ranking of the path in the number position and its actual performance. When the number is high but the number of successes is too small or the number is low but the number of successes is high, the difference will increase, thereby suppressing its ranking priority value. In this way, while maintaining the positive evaluation of the execution record, the number-performance consistency calibration is incorporated to form a stable and bias-resistant path priority scoring mechanism.

[0139] The path marking submodule screens the top 30% of path identifiers based on the path priority sorting sequence, marks the status as the cloud chain preferred path, writes it into the shared scheduling list, and generates the cloud chain scheduling path sorting list;

[0140] According to the path priority sorting sequence, select the top 30% of the priority paths from all the sorting results, set the interval screening boundary to the total number of paths multiplied by 30%, and when the total number of paths is 5, the first 1.5 paths after sorting will be screened and rounded off and processed as the first 2. Determine their identification numbers respectively, and mark the corresponding paths as "Cloud Chain Preferred Paths". Then, write the path state mapping dictionary composed of the marking results and the path numbers into the shared scheduling list and enter it into the corresponding scheduling structure for subsequent task scheduling strategy processing to establish a cloud chain scheduling path sorting list.

[0141] See also Figure 6 , the smart sharing writing module includes:

[0142] The target positioning submodule reads the target node address corresponding to the end point of each path based on the path numbers of all the paths marked as the cloud chain preferred paths in the cloud chain scheduling path sorting list, extracts the binding information between the path number and the target node, performs a one-to-one mapping between the path number and the target node, and generates a path node mapping set;

[0143] Based on the path numbers marked as cloud chain preferred paths in the cloud chain scheduling path sorting list, extract the path number information and sequentially read the end node index numbers corresponding to the path numbers. Query the target node network addresses recorded in the scheduling index, and establish a binding relationship between the path numbers and the target node addresses. Path numbers such as P01, P02, P03, etc. can be mapped to corresponding nodes such as Node_A, Node_B, Node_C, etc. If the path number is P01, then read its target node address Node_A in the structure table. After recording the end node address of this path, further verify whether this node address has the ability to access the effective linked list. If it does, enter the stage of establishing the binding relationship. If the node address is missing or in an abnormal format, record the path status as non-bindable. The validity check between P01 and Node_A can be completed through methods such as address bit number, format, check bit, etc. If Node_A is in a valid IPv6 format, then construct the mapping between the path and the node address. As shown in Table 1, the mapping relationship between P01 and Node_A is a valid mapping form. After establishing the mapping relationships for all path numbers, establish a path-node mapping set for the content writing process in the next stage.

[0144] Table 4 Record Table of Path Number and Target Node Writing

[0145]

[0146] As shown in Table 4, each path number corresponds to a unique target node address, and provides a complete mapping basis for subsequent shared data synchronization.

[0147] The content writing sub-module writes the shared content to the target nodes corresponding to the ends of each path in the order of the path numbers according to the path-node mapping set, records the synchronization order, data byte volume, and transmission status identifier during the writing process, processes the conflicting paths during writing and completes the path execution mark, and obtains the content synchronization performance value sequence;

[0148] Based on the path node mapping set, various types of shared content payloads are written to the corresponding target nodes according to the path number sorting rule. The writing process involves the extraction of shared data, content encapsulation, construction of a chained structure, and execution of the end-node writing action. If the target node corresponding to path P01 is Node_A and its shared data volume is 120MB, the system will perform content synchronization in units of write packets. The content is divided into several data blocks, with each block having a maximum unit of 10MB. Therefore, a total of 12 write actions are required to complete the synchronization. During the synchronization process, the sending time of each written data block and the response status of the target node are recorded. If the response delay is greater than the set threshold of 15ms, the transmission status of this time is recorded as an unstable state. In this example, the transmission delay corresponding to P01 is 10ms, which is within the stable range. The transmission data volume of path P03 is 130MB and the transmission delay is 8ms, so the synchronization rate is faster and the writing coherence is stronger. Although the data volume of path P04 is only 80MB, the delay is 20ms, resulting in a problem of insufficient timeliness. The system needs to mark the transmission timeliness warning value during the recording process, and record parameters such as the writing status, content size, and time delay for each path number one by one to form a content synchronization performance value sequence for subsequent path reliability scheduling. See the corresponding situations of path numbers, shared data volumes, transmission delays, and linked list statuses in Table 4.

[0149] Based on the content synchronization performance value sequence, the status recording sub-module checks the status of all shared content writing paths, extracts the linked list update results of each target node, and combines the path number, synchronization completion status, and node linked list change situation to establish a power node shared link record;

[0150] Read the content synchronization performance value sequence, and perform status marking records on the linked list status of all paths after content writing. Read whether the status code of each target node linked list has changed. The status codes are in forms such as "updated", "unchanged", and "abnormal". Among them, "updated" means that the target node has been successfully written and the linked list has been modified. "Unchanged" indicates that the write action has not triggered the movement of the linked list tail pointer. The statuses of path numbers P01, P03, and P04 are "updated", indicating that the linked list structure of the target node has been completed after the content is written. The status codes of paths P02 and P05 are "unchanged", indicating that although the content synchronization of these two paths is completed, the linked list tail pointer structure has not changed. The situation where the write is successful but the pointer is not updated needs to be marked as the linked list structure not responding to the write. The system further collects the path number, shared data volume, linked list status code, and generates a power node shared link record in combination with the path number and node address. The record structure covers the basic path information and writing behavior characteristics. See the write record parameters shown in Table 1 to provide an input basis for the subsequent task scheduling logic.

[0151] The above are only the preferred embodiments of the present invention and do not limit the present invention in other forms. Any person skilled in the relevant art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A smart power data sharing system based on cloud-chain collaboration, characterized in that The system includes: The node chain writing module obtains the power node timestamp and segment number information, detects the tail pointer time of the power node, compares the timestamp with the tail pointer time and makes a writing permission judgment, combines the power node number information and the segment number information to construct a time-continuous segment set structure, and generates an index-driven writing structure; The rhythm buffer recognition module detects whether the tail pointer time remains static within consecutive periods according to the tail pointer update period sequence of each power node in the index-driven writing structure. If the static state persists, the corresponding node is included in the buffer state cluster to obtain a writing rhythm buffer mapping table; The chain sequence continuous path monitoring module reads the current chain sequence number and the previous cycle chain sequence number based on the path identifier corresponding to the node in the non-buffered state in the writing rhythm buffer mapping table, performs an equal value judgment according to the difference, filters the paths that meet the chain sequence continuity condition, and generates a continuous chain sequence shared path set; The cloud chain path optimization module counts the successful times of the path historical sharing tasks in the continuous chain sequence shared path set, sorts the paths by priority, determines the cloud chain optimized path, enters it into the shared scheduling list, and generates a cloud chain scheduling path sorting list.

2. The intelligent power data sharing system based on cloud-chain collaboration according to claim 1, wherein The index-driven writing structure includes a segment continuity identifier, a node index update mapping, and a writing permission determination flag. The writing rhythm buffer mapping table includes a buffer state identifier, a node sharing state flag, and a cycle static record. The continuous chain sequence shared path set includes a path number set, a chain sequence matching identifier, and a path validity label. The cloud chain scheduling path sorting list includes a path priority level, a shared scheduling serial number, and a scheduling list flag.

3. The intelligent power data sharing system based on cloud-chain collaboration according to claim 1, wherein The node chain writing module includes: The time judgment sub-module collects the timestamp and segment number information generated by the local cache of the power node, reads the tail pointer time in the local index table of the power node, and compares whether the timestamp and the tail pointer time have the time writing permission. If the timestamp is later than the tail pointer time, it is determined that the writing permission is available, and a writing permission determination result is obtained; The index update sub-module updates the tail pointer and adds the segment number information to the end of the index table in ascending order according to the writing permission determination result. If the permission is determined, the index table new number sequence is obtained by combining the segment number information and the tail pointer time data; The structure generation sub-module constructs a time-continuous segment set structure based on the index table new number sequence and the combined sorting of the power node number information and the segment number information, filters and arranges the structure according to the combination order, and generates an index-driven writing structure.

4. The intelligent power data sharing system based on cloud-chain collaboration according to claim 1, wherein The rhythm buffer recognition module includes: The period extraction sub-module obtains the period time value of each node during the continuous writing stage based on the tail pointer update period sequence of each power node in the index-driven writing structure, and constructs a mapping list of the node and the corresponding period time to obtain a node period time sequence table; The static judgment sub-module judges whether the time remains static according to the change of the tail pointer time of each node within consecutive periods according to the node period time sequence table. The formula is used: Calculate the tail pointer time change ratio R, and establish a buffer node number set according to the set of node numbers where the tail pointer time change ratio is less than the tail pointer change reference limit. Among them, t i is the tail pointer time of the i-th cycle, is the average value of the tail pointer times of all cycles, x i is the number of write requests in the i-th cycle; Based on the set of buffered node numbers, the status mapping sub-module marks the nodes in the set as pending shared status in the index-driven write structure, performs node and status label mapping, and establishes a write rhythm buffer mapping table.

5. The intelligent power data sharing system based on cloud-chain collaboration according to claim 1, wherein The chain sequence continuous path monitoring module includes: Based on the path identifiers corresponding to the nodes in the non-buffered state in the write rhythm buffer mapping table, the path extraction sub-module reads the current chain sequence number and the previous cycle's chain sequence number to obtain a set of chain sequence path numbers; Based on the set of chain sequence path numbers, the chain sequence judgment sub-module analyzes the chain sequence status fluctuation trajectory based on the change characteristics between the current chain sequence number and the previous cycle's chain sequence number, using the formula: Calculate the chain order fluctuation mapping value C, mark the paths with the chain order fluctuation mapping value greater than the chain order consistency limit as discontinuous, remove the corresponding paths, and obtain the chain order continuous path index set, where, a j is the current chain order label of the j-th path, and b j is the chain order label of the previous cycle of the j-th path, max(a j ) is the maximum value of the current chain order label, and min(b j ) is the minimum value of the chain order label of the previous cycle; Based on the set of chain sequence continuous path indexes, the path screening sub-module classifies and summarizes the path identifiers that meet the chain sequence continuous conditions, filters according to the sharing conditions, performs path sequence and task sharing mapping, and generates a set of continuous chain sequence shared paths.

6. The intelligent power data sharing system based on cloud-chain collaboration according to claim 1, characterized in that, The cloud chain path optimization module includes: Based on the set of continuous chain sequence shared paths, the task statistics sub-module counts the number of successful historical shared tasks corresponding to each path, records the mapping of the path identifier and the corresponding number of successful times, and generates a set of path task success times; Based on the set of path task success times, the priority judgment sub-module obtains the number of successful tasks and its position number for each path, using the formula: Calculate the path sorting priority value P, and perform a descending order arrangement according to the size of the path sorting priority value to obtain the path priority sorting sequence, where s k is the historical shared task success count of the k-th path, and k is the position number of the path in the path task set. represents the cumulative square root value after the success count gain of each path, ∑ k (k - s k ) is the total deviation of the difference between the path number and its task ability; Based on the path priority sorting sequence, the path annotation sub-module filters the path identifiers, marks the status as the cloud chain optimized path, and writes it into the shared scheduling list to generate a cloud chain scheduling path sorting list.

7. The intelligent power data sharing system based on cloud-chain collaboration according to claim 1, characterized in that The system further includes: According to the cloud chain optimized paths in the cloud chain scheduling path sorting list, the intelligent shared write module reads the target node addresses corresponding to the end points of each path, synchronously writes the shared content into the target nodes in path order, records the transmission status of the shared content and the update status of the target node linked list for all participating paths, and generates a power node shared link record; The power node shared link record includes transmission data mapping, node linked list change information, and shared synchronization status log.

8. The intelligent power data sharing system based on cloud-chain collaboration according to claim 7, wherein The intelligent shared write module includes: Based on the path numbers of all paths marked as cloud chain optimized paths in the cloud chain scheduling path sorting list, the target location sub-module reads the target node addresses corresponding to the end points of each path, extracts the binding information between the path number and the target node, performs a one-to-one mapping between the path number and the target node, and generates a path-node mapping set; According to the path-node mapping set, the content write sub-module writes the shared content into the target nodes corresponding to the end points of each path in path number order, records the synchronization order, data byte volume, and transmission status identifier during the writing process, processes the conflicting write paths and completes the path execution mark, and obtains a content synchronization performance value sequence; Based on the content synchronization performance value sequence, the status record sub-module checks the status of all shared content write paths, extracts the linked list update results of each target node, and combines the path number, synchronization completion status, and node linked list change situation to establish a power node shared link record.

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