Dynamic scheduling system for cross-border warehousing data management

Abstract

The application belongs to the technical field of big data storage and management, and discloses a dynamic scheduling system for cross-border warehouse data management, which comprises a local storage acceleration module, a state difference analysis module, a dynamic transaction queue scheduling module and a layered persistent management module. The local storage acceleration module is used for generating write cache data pages and dynamic append logs. The state difference analysis module is used for extracting a transaction log write difference vector, analyzing a warehouse entity fluctuation index and a synchronization delay estimation value. The dynamic transaction queue scheduling module comprises a deterministic state vector channel and a speculative lock-free slice channel, is used for shunting the write difference vector according to priority score, and covers changed data in a lock-free slot using a write mask bitmap to complete in-place compression. The layered persistent management module is used for triggering a disk brushing submission when data reaches a physical sector alignment boundary. The application decouples transaction locks and persistent disk brushing, and eliminates disk write amplification and storage lock blocking caused by random writing.

Description

Technical Field

[0001] This invention belongs to the field of big data storage and management technology, and in particular relates to a dynamic scheduling system for cross-border warehouse data management. Background Technology

[0002] Currently, distributed data storage nodes deployed across regions typically rely on write-ahead log mechanisms and distributed transaction synchronization protocols to maintain data consistency among nodes and recover from failures. When handling cross-node repository transaction state updates and high-concurrency transaction log persistence, existing distributed storage engines usually require transactions to first flush local logs to disk and wait for cross-border confirmation packets to return before releasing the lock resources they occupy.

[0003] When cross-node data transmission has high physical latency and network links experience random jitter, the time spent waiting for cross-border confirmation packets overlaps with the time spent on random disk writes, causing the transaction lock holding time to increase exponentially. As lock waiting increases, the waiting spreads throughout the entire storage engine, and online write cache data pages accumulate, leading to transaction lock queue timeouts and eventual exhaustion of storage resources. To mitigate the decrease in write throughput caused by lock waiting, existing technologies typically employ asynchronous log batch flushing strategies. However, conventional asynchronous flushing mechanisms struggle to perform in-situ deduplication of concurrent write changes within the same storage page at byte positions, and also struggle to complete physical sector alignment before flushing. Therefore, frequent flushing still generates a large number of unaligned small random writes, accelerating the physical wear and tear of solid-state storage media. Furthermore, it increases the overhead of additional read, modify, and write operations on the disk. When business traffic increases, local storage nodes are prone to system-level deadlocks or performance degradation. For example, Chinese invention patent application CN119806391A discloses an asynchronous metadata flushing method based on a database computing separation architecture. Although a background flushing thread is introduced to asynchronously modify metadata, it still needs to lock the shared memory and write logs synchronously when handling high-concurrency write requests, failing to completely decouple transaction locks from flushing operations. At the same time, this solution lacks byte-level in-situ deduplication and physical sector alignment mechanisms, which can easily cause severe storage medium write amplification and queue blocking under high-latency conditions in cross-border networks. Therefore, it is necessary to provide a dynamic scheduling system that can achieve lock-free slice stacking and adaptive alignment flushing.

[0004] Therefore, the technical problem to be solved by this invention is how to separate the transaction lock holding period from the persistent disk flushing process, complete the in-situ stacking of the transaction log write differential in the memory mapping layer in a zero-copy manner, and then flush the disk after physical sector alignment. Summary of the Invention

[0005] To address the problems in the background art, the technical solution of the present invention is as follows: A dynamic scheduling system for cross-border warehousing data management, comprising: The local storage acceleration module is used to receive transaction write requests, generate online write cache data pages and dynamically append logs; The state differential parsing module is used to extract the transaction log write differential vector containing storage page identifier, byte offset, changed data binary stream, incrementing sequence number and write mask bitmap, and to parse the warehouse entity volatility index and synchronization delay estimate. The dynamic transaction queue scheduling module includes a deterministic state vector channel and a speculative lock-free slice channel. It is used to derive priority scores based on the warehouse entity volatility index and the synchronization delay estimate. When the priority score is lower than the preset splitting threshold, the transaction log write differential vector is pushed into the speculative lock-free slice channel, and vice versa. The hierarchical persistence management module is connected to the dynamic transaction queue scheduling module and the local hierarchical storage medium; The speculative lockless slicing channel includes a one-way lockless ring slot buffer module and a bitmap mask parsing module. It is used to write the transaction log write differential vector into the one-way lockless ring slot buffer module using atomic comparison and exchange instructions. When the storage page identifier is the same and the incrementing sequence number is incremented, the in-situ overlay is completed by overwriting the changed data binary stream according to the byte offset and the write mask bitmap. The tiered persistence management module includes an alignment detection module and an adaptive flush triggering module. The adaptive flush triggering module is activated and the data is submitted to the local tiered storage medium when the data volume reaches the 4KB physical sector alignment boundary.

[0006] Preferably, the transaction log write differential vector also includes the changed field identifier, the state hash value before the change, and the state hash value after the change; after receiving the transaction log write differential vector corresponding to the transaction write request, the bitmap mask parsing module extracts the storage page identifier, byte offset, and changed data binary stream and generates a write mask bitmap, and uses atomic comparison and exchange instructions to write the byte offset and write the write mask bitmap into the slot node of the corresponding storage page identifier in the unidirectional lock-free ring slot buffer module.

[0007] Preferably, the state differential parsing module includes an acknowledgment packet tracking module; the acknowledgment packet tracking module is connected to the cross-node network and is used to capture cross-border acknowledgment packets sent to the historical transaction log write differential vector of the remote storage node, calculate the round-trip time of the cross-border acknowledgment packets, calculate the moving average of the round-trip time for a preset number of round-trip times, and input the derived moving average as the synchronization delay estimate into the dynamic transaction queue scheduling module.

[0008] Preferably, the dynamic transaction queue scheduling module includes a dynamic threshold ballast module and a circuit breaker detection module; the circuit breaker detection module is used to monitor the response status of data packets sent to remote storage nodes in real time; when the circuit breaker detection module continuously detects that the number of network acknowledgment packet losses exceeds the preset loss threshold of 5 times, the dynamic threshold ballast module is activated, the preset splitting threshold is raised by 200%, the data flow entering the deterministic state vector channel is restricted, and the data containment pressure is transferred to the speculative lockless slicing channel.

[0009] Preferably, the hierarchical persistence management module includes a local version tree construction module and a cache monitoring module. The cache monitoring module is used to detect the memory usage of online write cache data pages in the local storage acceleration module in real time. When the memory usage reaches the preset safety limit of 85%, the hierarchical persistence management module stops receiving data from speculative lock-free slice channels, starts the local version tree construction module, constructs a local version tree for the data slices in the dynamically appended log based on the hash values ​​of the state before and after the change, and completes the conflict cancellation and merging of multiple modifications to the same field in memory. After generating a compressed write vector, it is sequentially written to the solid-state drive append area of ​​the local hierarchical storage medium.

[0010] Preferably, the tiered persistence management module includes a storage media wear sensing module. The storage media wear sensing module is used to read the self-monitoring analysis and reporting technical parameters of the solid-state storage device in the local tiered storage media, extract the percentage of remaining erase / write cycles and the average block erase latency, and derive the media health index. When the media health index is lower than a preset health threshold, the storage media wear sensing module calculates a dynamic blocking time window based on the media health index, and blocks the hard disk flushing command within the dynamic blocking time window, temporarily storing the data in a non-volatile memory buffer layer with independent power supply protection, until the dirty page rate reaches a preset extreme value of 90% or the dynamic blocking time window expires, triggering a multi-page continuous merging and disk flushing.

[0011] Preferably, the state difference parsing module includes an in-situ incremental vector merging module and a state change directed acyclic graph (DAG) construction module. The DAG construction module is used to construct the state change DAG. When the cross-node network interruption is recovered, the in-situ incremental vector merging module receives the deterministic state vector sent by the remote storage node. When the previous state hash value is detected to be inconsistent with the local current state hash value, the in-situ incremental vector merging module searches backward along the state change DAG to the common ancestor node, extracts the local write difference vector and the remote write difference vector, calculates the vector superposition value for the additivity commutative law numerical fields involving the increase or decrease of inventory quantity, generates a synthetic difference vector, and completes the in-situ incremental update on the online write cache data page.

[0012] Preferably, the hierarchical persistence management module also includes a timeout-filled disk flushing trigger module; the timeout-filled disk flushing trigger module is used to monitor the first write wait time of slot data in the unidirectional unlocked ring slot buffer module; when the data volume of the stacked slots in the unidirectional unlocked ring slot buffer module has not reached the 4KB physical sector alignment boundary, but the first write wait time reaches the preset limit blocking time window of 10ms, the timeout-filled disk flushing trigger module adds zero padding bits to the end of the data to align with the 4KB physical sector boundary, and submits the aligned page block data to the local hierarchical storage medium.

[0013] Preferably, the local tiered storage media includes non-volatile memory, solid-state drives (SSDs), and hard disk drives (HDDs); the tiered persistence management module includes a media routing allocation module, which is used to directly submit the data output from the deterministic state vector channel to the non-volatile memory for persistence, and submit the data pages in the speculative lockless slice channel that have been overlaid and stacked and have reached the 4KB physical sector alignment boundary to the sequential append write area of ​​the SSD.

[0014] Compared with existing technologies, the dynamic scheduling system for cross-border warehousing data management of this invention has the following advantages: 1. In the dynamic scheduling of cross-border warehouse data management, the state differential parsing module dynamically distributes the transaction log write differential vectors based on the warehouse entity volatility index and the synchronization delay estimate. This allows data that needs to be synchronized across nodes to enter the deterministic state vector channel, while other data first enters the speculative lock-free slice channel for local processing. This reduces the continuous waiting of local transactions for cross-border confirmation packets, separates the release of transaction locks from physical disk flushing, alleviates transaction lock backlog and storage queue blockage during high-concurrency writes, and improves the responsiveness of cross-border warehouse data writes.

[0015] 2. The speculative lock-free slicing channel uses a bitmap mask parsing module and a one-way lock-free ring slot buffer module to overwrite and merge multiple write changes generated within the same storage page in situ, reducing repeated intermediate state writes. The hierarchical persistence management module only flushes the disk when the data reaches the physical sector alignment condition or the waiting time reaches the upper limit. It can merge scattered small random writes into continuous page block writes, reduce disk read / write overhead, suppress write amplification of persistent media, and reduce wear of solid-state storage media.

[0016] 3. When acknowledgment packets are continuously lost across nodes, the dynamic threshold ballast module can adjust the amount of data entering the deterministic state vector channel, transferring some of the write pressure to the speculative lock-free slice channel, thus preventing network anomalies from escalating into global synchronization queue blockage. When the memory usage of online write cache data pages is high, the local version tree construction module can merge duplicate or conflicting write changes locally, and then write the merged data sequentially to the storage medium, thereby alleviating cache backlog and network duplicate transmissions, and ensuring that local transaction writes can maintain continuous response even under network fluctuations or interruptions. Attached Figure Description

[0017] Figure 1 This is a logical principle diagram of the warehouse data dynamic scheduling system of the present invention; Figure 2 This is the overall structure diagram of the dynamic scheduling system for warehouse data of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0019] A dynamic scheduling system for cross-border warehousing data management includes: The local storage acceleration module is used to receive transaction write requests, generate online write cache data pages and dynamically append logs; The state differential parsing module is used to extract the transaction log write differential vector containing storage page identifier, byte offset, changed data binary stream, incrementing sequence number and write mask bitmap, and to parse the warehouse entity volatility index and synchronization delay estimate. The dynamic transaction queue scheduling module includes a deterministic state vector channel and a speculative lock-free slice channel. It is used to derive priority scores based on the warehouse entity volatility index and the synchronization delay estimate. When the priority score is lower than the preset splitting threshold, the transaction log write differential vector is pushed into the speculative lock-free slice channel, and vice versa. The hierarchical persistence management module is connected to the dynamic transaction queue scheduling module and the local hierarchical storage medium; The speculative lockless slicing channel includes a one-way lockless ring slot buffer module and a bitmap mask parsing module. It is used to write the transaction log write differential vector into the one-way lockless ring slot buffer module using atomic comparison and exchange instructions. When the storage page identifier is the same and the incrementing sequence number is incremented, the in-situ overlay is completed by overwriting the changed data binary stream according to the byte offset and the write mask bitmap. The tiered persistence management module includes an alignment detection module and an adaptive flush triggering module. The adaptive flush triggering module is activated and the data is submitted to the local tiered storage medium when the data volume reaches the 4KB physical sector alignment boundary.

[0020] Preferably, the transaction log write differential vector also includes the changed field identifier, the state hash value before the change, and the state hash value after the change; after receiving the transaction log write differential vector corresponding to the transaction write request, the bitmap mask parsing module extracts the storage page identifier, byte offset, and changed data binary stream and generates a write mask bitmap, and uses atomic comparison and exchange instructions to write the byte offset and write the write mask bitmap into the slot node of the corresponding storage page identifier in the unidirectional lock-free ring slot buffer module.

[0021] Preferably, the state differential parsing module includes an acknowledgment packet tracking module; the acknowledgment packet tracking module is connected to the cross-node network and is used to capture cross-border acknowledgment packets sent to the historical transaction log write differential vector of the remote storage node, calculate the round-trip time of the cross-border acknowledgment packets, calculate the moving average of the round-trip time for a preset number of round-trip times, and input the derived moving average as the synchronization delay estimate into the dynamic transaction queue scheduling module.

[0022] Preferably, the dynamic transaction queue scheduling module includes a dynamic threshold ballast module and a circuit breaker detection module; the circuit breaker detection module is used to monitor the response status of data packets sent to remote storage nodes in real time; when the circuit breaker detection module continuously detects that the number of network acknowledgment packet losses exceeds the preset loss threshold of 5 times, the dynamic threshold ballast module is activated, the preset splitting threshold is raised by 200%, the data flow entering the deterministic state vector channel is restricted, and the data containment pressure is transferred to the speculative lockless slicing channel.

[0023] Preferably, the hierarchical persistence management module includes a local version tree construction module and a cache monitoring module. The cache monitoring module is used to detect the memory usage of online write cache data pages in the local storage acceleration module in real time. When the memory usage reaches the preset safety limit of 85%, the hierarchical persistence management module stops receiving data from speculative lock-free slice channels, starts the local version tree construction module, constructs a local version tree for the data slices in the dynamically appended log based on the hash values ​​of the state before and after the change, and completes the conflict cancellation and merging of multiple modifications to the same field in memory. After generating a compressed write vector, it is sequentially written to the solid-state drive append area of ​​the local hierarchical storage medium.

[0024] Preferably, the tiered persistence management module includes a storage media wear sensing module. The storage media wear sensing module is used to read the self-monitoring analysis and reporting technical parameters of the solid-state storage device in the local tiered storage media, extract the percentage of remaining erase / write cycles and the average block erase latency, and derive the media health index. When the media health index is lower than a preset health threshold, the storage media wear sensing module calculates a dynamic blocking time window based on the media health index, and blocks the hard disk flushing command within the dynamic blocking time window, temporarily storing the data in a non-volatile memory buffer layer with independent power supply protection, until the dirty page rate reaches a preset extreme value of 90% or the dynamic blocking time window expires, triggering a multi-page continuous merging and disk flushing.

[0025] Preferably, the state difference parsing module includes an in-situ incremental vector merging module and a state change directed acyclic graph (DAG) construction module. The DAG construction module is used to construct the state change DAG. When the cross-node network interruption is recovered, the in-situ incremental vector merging module receives the deterministic state vector sent by the remote storage node. When the previous state hash value is detected to be inconsistent with the local current state hash value, the in-situ incremental vector merging module searches backward along the state change DAG to the common ancestor node, extracts the local write difference vector and the remote write difference vector, calculates the vector superposition value for the additivity commutative law numerical fields involving the increase or decrease of inventory quantity, generates a synthetic difference vector, and completes the in-situ incremental update on the online write cache data page.

[0026] Preferably, the hierarchical persistence management module also includes a timeout-filled disk flushing trigger module; the timeout-filled disk flushing trigger module is used to monitor the first write wait time of slot data in the unidirectional unlocked ring slot buffer module; when the data volume of the stacked slots in the unidirectional unlocked ring slot buffer module has not reached the 4KB physical sector alignment boundary, but the first write wait time reaches the preset limit blocking time window of 10ms, the timeout-filled disk flushing trigger module adds zero padding bits to the end of the data to align with the 4KB physical sector boundary, and submits the aligned page block data to the local hierarchical storage medium.

[0027] Preferably, the local tiered storage media includes non-volatile memory, solid-state drives (SSDs), and hard disk drives (HDDs); the tiered persistence management module includes a media routing allocation module, which is used to directly submit the data output from the deterministic state vector channel to the non-volatile memory for persistence, and submit the data pages in the speculative lockless slice channel that have been overlaid and stacked and have reached the 4KB physical sector alignment boundary to the sequential append write area of ​​the SSD.

[0028] Example 1: The current multinational regional warehouse data center adopts a distributed deployment. The physical round-trip latency between nodes is 150ms, accompanied by random packet loss. The local storage acceleration module receives high-concurrency transaction write requests submitted by warehouse terminals during peak business periods, generates online write cache data pages and dynamic append logs, and the state differential parsing module captures transaction write requests in real time and extracts information including storage page identifiers. Byte offset Change the binary data stream and increment the sequence number. With write mask bitmap Transaction log write difference vector Simultaneously, the acknowledgment packet tracking module captures cross-border acknowledgment packets of historical transaction log write differential vectors sent to remote storage nodes, calculates the moving average of round-trip time delay, and derives the synchronization delay estimate. By combining the cumulative frequency and magnitude of modifications to warehouse entities within a preset time sliding window, a warehouse entity volatility index is calculated. In one embodiment, the system sets a 60-second preset time sliding window. Within this window, it counts the cumulative frequency of a specific warehouse entity being modified by a transaction in real time, and also counts the absolute value of the numerical change involved in each modification. The cumulative frequency is divided by 60 seconds to obtain the average modification frequency per second. The sum of the absolute values ​​of the numerical changes of each transaction is divided by the cumulative frequency to obtain the average modification magnitude per transaction. Subsequently, the average modification frequency per second is multiplied by a first weighting coefficient of 10, and the average modification magnitude per transaction is divided by the base inventory unit and then multiplied by a second weighting coefficient of 20. The two weighted results are then added together and multiplied by an amplification factor of 50 to obtain a dimensionless warehouse entity volatility index, the value of which dynamically changes within the range of 100 to 800 with the modification frequency and modification magnitude.

[0029] The dynamic transaction queue scheduling module is based on relational formulas. Calculate priority score ,in, For warehouse entity volatility index The relative volatility coefficient obtained after normalization Synchronization delay estimate The relative delay coefficient obtained after normalization As a smoothing constant, with a value of 0.1, before calculating the priority score, the system performs dimension normalization on the input raw physical quantities. The synchronization delay estimate is in milliseconds (ms). Dividing the measured value by the baseline network delay reference value of 100ms yields a dimensionless relative delay coefficient with a corresponding value of 1.5. The original discrete values ​​of the warehouse entity fluctuation index are between 100 and 800. Dividing it by the baseline fluctuation dimension reference value of 500 yields a dimensionless relative fluctuation coefficient ranging from 0.2 to 1.6. After normalization, the dynamic transaction queue scheduling module... Divide by and The sum of these values ​​yields the priority score. In the preset calibration samples, the priority scores are concentrated in the range of 0.4 to 2.5 or higher. The priority scores and the preset splitting threshold of 2.5 are both dimensionless values ​​and can be directly compared.

[0030] When priority score Reaching the preset splitting threshold At that time, the dynamic transaction queue scheduling module writes the transaction log to the differential vector. The deterministic state vector channel is pushed in. The media routing allocation module in the hierarchical persistence management module receives the data output from this channel, directly submits it to non-volatile memory for persistence, and synchronizes it to the remote storage node through the cross-node network. When the priority score... Below the preset splitting threshold At that time, the dynamic transaction queue scheduling module writes the transaction log to the differential vector. Push in a speculative unlocked slice channel.

[0031] The bitmap mask parsing module receives the transaction log write difference vector. Then, extract the storage page identifier. Byte offset This involves modifying the binary data stream and generating a write mask bitmap based on the byte range occupied by the modified binary data stream in the target storage page. , from byte offset Initially, the mask bits corresponding to each byte of the changed data binary stream are set to 1, and the remaining mask bits are set to 0. Subsequently, the bitmap mask parsing module uses atomic comparison and swap instructions to offset the bytes. Write the mask bitmap And the local dynamic memory descriptor associated with the changed data binary stream, which is then written lock-free to the corresponding storage page identifier in the unidirectional lock-free ring slot buffer module. The slot node detects the storage page identifier. Same and increasing sequence number When incrementing, based on byte offset With write mask bitmap The binary stream of changed data is overwritten in situ in the memory slot to eliminate historical intermediate states. Multiple changes within the same storage page are merged into a single state difference vector, decoupling the transaction lock holding period from the physical disk flushing action.

[0032] Each slot node in the unidirectional lock-free ring slot buffer module is configured with a 64-bit wide atomic header information field. The high 32 bits store the incrementing sequence number associated with the current slot, and the low 32 bits store a physical address pointer to the local dynamic memory descriptor. The local dynamic memory descriptor records the byte offset, write mask bitmap, and the corresponding changed data binary stream. After the bitmap mask parsing module captures the transaction log write differential vector containing the target storage page identifier, it reads the 64-bit atomic header information to obtain the base sequence number of the current slot. If the incrementing sequence number in the transaction log write differential vector to be written is greater than the base sequence number, a temporary memory page is requested in the local working buffer, and the original binary data in the slot is copied byte by byte to the temporary memory page. Then, the specific change position is located according to the byte offset recorded in the transaction log write differential vector. According to the mask bits with a value of 1 in the write mask bitmap, the changed data binary stream is written byte by byte to the corresponding offset position of the temporary memory page, completing the in-situ overlay of memory data.

[0033] After the overwrite is complete, the bitmap mask parsing module writes the byte offset, write mask bitmap, and the overwritten modified binary data stream into a new local dynamic memory descriptor. It constructs a 64-bit target header containing a new incrementing sequence number and a new physical address pointer to the descriptor. Then, it calls the word comparison and swap atomic instruction provided by the underlying hardware to attempt to replace the original 64-bit atomic header information of the slot node with the target header information. When the comparison and swap atomic instruction returns successfully, the byte offset and write mask bitmap are mapped to the corresponding slot node through the new physical address pointer. The in-situ overlay lock-free write is completed, and the original local dynamic memory descriptor is reclaimed. If concurrent write contention causes the comparison and swap atomic instruction to return failure, the temporary memory page is released, the updated 64-bit atomic header information is reread, and the overwrite and comparison process is repeated until the write operation is successfully committed. This ensures the eventual consistency and atomicity of variable-length binary modified data overwriting in a multi-threaded concurrent environment.

[0034] The alignment detection module in the hierarchical persistence management module periodically scans the continuous data volume of the stacked slots in the unidirectional unlocked ring slot buffer module. When the continuous data volume reaches the 4KB physical sector alignment boundary, the adaptive disk flushing trigger module is activated, and the media routing allocation module submits the page block data to the sequential append write area of ​​the solid-state drive contained in the local hierarchical storage medium. If the continuous data volume does not reach the 4KB physical sector alignment boundary, but the first write wait time of the slot data reaches the preset limit blocking time window of 10ms, the timeout supplement disk flushing trigger module adds zero padding bits to the end of the data. After aligning the 4KB physical sector boundary, the media routing allocation module submits the page block data to the sequential append write area of ​​the solid-state drive.

[0035] When the circuit breaker detection module detects more than 5 consecutive network acknowledgment packet losses, the dynamic threshold ballast module will preset a split threshold. The threshold is raised by 200%, limiting data flow into the deterministic state vector channel and shifting data containment pressure to the speculative lock-free slice channel. A prerequisite for transaction log write differential vectors to enter the deterministic state vector channel is that their priority score reaches or exceeds a preset split threshold. When network congestion or a circuit breaker occurs, resulting in the loss of network acknowledgments, the preset split threshold is raised by 200%, for example, from the initial 2.5 to 7.5. This increases the entry threshold for transaction log write differential vectors to enter the deterministic state vector channel. Transaction log write differential vectors with a priority score below 7.5 are temporarily stored in the speculative lock-free slice channel, which does not require waiting for network acknowledgments. This allows concurrent write traffic to bypass cross-border network waiting and be received by the speculative lock-free slice channel, preventing data from entering the deterministic state vector channel and causing a global lockout when the network is broken.

[0036] When the cache monitoring module detects that the memory usage of the online write cache data page has reached the safety limit of 85%, the local version tree construction module suspends receiving data from the speculative lock-free slice channel. It constructs a local version tree from the data slices in the dynamic append log based on the hash values ​​of the state before and after the change. After completing conflict cancellation and merging in memory, it sequentially writes the compressed write vector to the sequential append write area of ​​the solid-state drive. The tree node data structure of the local version tree includes the root node identifier, parent state hash pointer, child state hash pointer, update timestamp, field offset mapping table, and binary change load area. The local version tree construction module traverses each data slice in the dynamic append log, extracts the hash values ​​of the state before and after the change recorded in each data slice, uses the state hash value of the initial base page as the root node, and takes the data slices whose state hash values ​​before the change are consistent with the existing node's child state hash values ​​as child nodes, and attaches them to the corresponding parent node to form a multi-branch directed version tree structure.

[0037] When two different log slices are mounted under the same parent node and modify the same byte offset on the same storage page, the local version tree construction module performs conflict cancellation and merging. If the business field corresponding to the byte offset is a non-cumulative overwrite field, it is compared according to the incrementing sequence number in the data slice, retaining the latest changed data binary stream with the larger sequence number and pruning the old branch node with the smaller sequence number. If the business field corresponding to the byte offset is a numerical incremental field that satisfies the commutative law of algebraic addition, the numerical increment part in the two log slices is extracted, algebraically added, and a compressed write vector is generated. The merged new state hash value is then updated to the child state hash pointer of the node, so that multiple redundant modifications to the same field are converged into a single compressed write vector in memory.

[0038] The storage media wear sensing module reads the self-monitoring analysis and reporting technical parameters of the solid-state storage device, extracts the percentage of remaining erase / write cycles and the average block erase latency, and derives the media health index. When the media health index is lower than the preset health threshold, a dynamic blocking time window is calculated to block the hard disk flush command. The data is temporarily stored in a non-volatile memory buffer layer with independent power supply protection until the dirty page rate reaches the preset extreme value of 90% or the dynamic blocking time window expires. Then, a multi-page continuous merging and flush is triggered. After the cross-node network interruption is recovered, the in-situ incremental vector merging module in the state differential parsing module receives the deterministic state vector sent by the remote storage node. When the previous state hash value is detected to be inconsistent with the local current state hash value, the module searches backward along the directed acyclic graph of state changes to the common ancestor node, extracts the local write differential vector and the remote write differential vector, calculates the vector superposition value for the additivity commutative law numerical fields involving the increase or decrease of inventory quantity, and completes the in-situ incremental update on the online write cache data page to maintain the consistency of multi-node storage state and high-throughput write.

[0039] Example 2: The current physical test platform is set up with 4 cross-regional distributed storage nodes. Each node transmits data through a dedicated link superimposed with a network packet loss simulator. The measured physical round-trip latency fluctuates between 50ms and 300ms. The test data is taken from the real-time inventory deduction log and cross-warehouse transfer log of the cross-border e-commerce warehousing system. The data stream contains concurrent write requests with timestamps, storage page identifiers and byte offsets.

[0040] To generate controllable network disturbances, the test platform loads Gaussian white noise with a signal-to-noise ratio of 20dB and 50Hz power frequency harmonics through the software protocol driver of the network test simulation layer. The disturbance injection module is set in the network device driver layer of the operating system kernel, which maps the periodic fluctuation of the 50Hz power frequency harmonics to sinusoidal network transmission delay jitter with a period of 20ms, and maps the Gaussian white noise with a signal-to-noise ratio of 20dB to random bit flips and probabilistic packet loss during data packet transmission. Based on this, the network device driver layer outputs transmission delay changes and data packet corruption status to the digital network stack, so that the test data stream generates corresponding random delays and retransmission pressure.

[0041] The sampling period and scheduling depth are set based on the fluctuation of network round-trip latency and the growth rate of online write cache data page memory usage, within the estimated synchronization latency. 150ms, warehouse entity volatility index When the calibration range is between 100 and 800, the smoothing constant Set the value to 0.1, and set the preset splitting threshold. The value is set to 2.5, the physical sector alignment boundary is set to 4KB, the preset limit blocking time window is set to 10ms, and the smoothing constant is used to avoid the denominator in the priority score calculation approaching zero. Within the above test input range, the constant term of 0.1 also ensures that the subsequent proportional splitting calculation using the reciprocal of the priority score or the normalized result maintains a non-zero denominator. The 4KB physical sector alignment boundary is used to control the disk flushing boundary of page block data, and the 10ms preset limit blocking time window is used to limit the waiting time of slice overlay and prevent the continuous backlog of online write cache data pages.

[0042] In this embodiment and comparative test, the proposed solution employs a state differential parsing module, a dynamic transaction queue scheduling module, and a hierarchical persistence management module. Control group 1 disables the in-situ overlay and 4KB physical sector alignment processing of the bitmap mask parsing module and replaces it with a conventional queue asynchronous disk flushing. Control group 2 disables the splitting between the deterministic state vector channel and the speculative lock-free slice channel, and all transaction log write differential vectors are sent through the deterministic state vector channel to wait for cross-border confirmation packets to return. Control group 3 retains dual-channel splitting and in-situ overlay, and changes the preset limit blocking time windows to 1ms and 100ms, respectively.

[0043] The loading process uses three levels of input conditions in sequence. The first level has a transaction concurrency of 5000 QPS, a network latency of 50ms, and a packet loss rate of 2%; the second level has a transaction concurrency of 15000 QPS, a network latency of 150ms, and a packet loss rate of 5%; and the third level has a transaction concurrency of 30000 QPS, a network latency of 300ms, and a packet loss rate of 15%.

[0044] Under each input condition, the state differential parsing module captures data including storage page identifiers. Byte offset and incrementing sequence number Transaction log write difference vector Calculate the warehouse entity volatility index With synchronization delay estimate The priority score is obtained by the dynamic transaction queue scheduling module. The bitmap mask parsing module uses atomic compare and swap instructions to write the transaction log differential vector to the unidirectional lock-free circular slot buffer module; when the storage page identifier... Same and increasing sequence number During incrementing, the write mask bitmap is used as a reference. and byte offset The overlay changes the binary stream of data, completes in-situ overlay, and the alignment detection module continuously records the continuous data volume and disk flushing trigger status within the slot. The overlay rate is used to represent the proportion of data that has completed in-situ overlay in the data entering the speculative unlocked slice channel.

[0045] When the test group uses the first level of input conditions, the priority score is... With a priority score between 1.82 and 6.15 and a stacking rate of 68.5%, after dual-channel splitting, in-situ stacking, and disk flushing, the average local transaction response latency is 4.2ms, the disk write amplification ratio is 1.25, and the storage throughput is 4820 IOPS. After increasing the input to the second priority level, both network latency and packet loss rate increase. The dynamic transaction queue scheduling module adjusts the number of differential vectors for transaction log writes in the two channels based on the priority score. At this point, the priority score... The stacking ratio is between 0.85 and 4.42, and the stacking ratio increases to 72.1%. After the change data is merged by the unidirectional lockless ring slot buffer module, the average local transaction response latency is 8.6ms, the disk write amplification ratio is 1.38, and the storage throughput is 14210 IOPS.

[0046] When using the third level of input conditions, the priority score is... Between 0.31 and 2.10, more transaction log write differential vectors enter the speculative lock-free slice channel, with a stacking rate of 78.4%. After the continuous data volume reaches the 4KB physical sector alignment boundary, the hierarchical persistence management module sequentially submits the page block data to the sequential append write area of ​​the solid-state drive. The average local transaction response latency is 11.4ms, the disk write amplification ratio is 1.62, and the storage throughput is 26850 IOPS.

[0047] When the control group adopted the second input condition, the overlay rate was 0% because in-situ overlay and 4KB physical sector alignment were not performed. The scattered changed data was written to the storage medium asynchronously through the regular queue. The average local transaction response latency was 38.5ms, the disk write amplification ratio was 8.45, and the storage throughput was 6120 IOPS. After the input was increased to the third level, the overlay rate was still 0%. Unaligned small data blocks continued to generate random writes. The average local transaction response latency increased to 95.2ms, the disk write amplification ratio increased to 12.80, and the storage throughput decreased to 4150 IOPS.

[0048] When the second set of input conditions is used in control group 2, all transaction log write differential vectors enter the deterministic state vector channel and maintain strong synchronization waiting before the cross-node acknowledgment packet returns, with a 0% overlap rate. Under this processing method, the average local transaction response latency is 462.0ms, the disk write amplification ratio is 2.15, and the storage throughput is 2100 IOPS. When the third set of input conditions is used, the cross-node waiting time increases with the increase of network latency and packet loss rate, the average local transaction response latency reaches 1250.0ms, the disk write amplification ratio is 2.40, and the storage throughput is 780 IOPS.

[0049] In control group three, using the second input condition and shortening the preset limit blocking time window to 1ms, the slot data triggered a timeout and disk flush before it was fully stacked and reached the 4KB physical sector alignment boundary, with a stacking rate of 31.2%. The submitted data was in an unaligned state, the average local transaction response latency was 18.2ms, the disk write amplification ratio was 4.85, and the storage throughput was 8900 IOPS. After extending the preset limit blocking time window to 100ms, the slot data waiting time increased, and the memory utilization rate of the online write cache data page reached the 85% safety limit. The local version tree construction module then stopped receiving data from the speculative lock-free slice channel. At this time, the average local transaction response latency was 45.6ms, the disk write amplification ratio was 1.55, and the storage throughput was 9200 IOPS.

[0050] During the above tests, as network latency and packet loss rate increased, the experimental group allocated more transaction log write differential vectors to the speculative lock-free slice channel and converted scattered writes into sequential append writes of contiguous page blocks through in-situ overlay and 4KB physical sector alignment. Control group 1 did not perform in-situ overlay and physical sector alignment, and random small block writes accumulated with the increase of concurrency. Control group 2 placed cross-border acknowledgment packet waiting in the commit path of all transactions, and the local response time was extended with changes in network conditions. Control group 3 triggered unaligned flushing in advance when using a shorter preset limit blocking time window, and made the memory occupancy rate of online write cache data pages reach the safe limit when using a longer preset limit blocking time window.

[0051] Example 3: After a long period of high-concurrency writing to the tiered storage medium, the storage medium wear sensing module reads the operating parameters of the solid-state storage device through the self-monitoring analysis and reporting technology interface, and extracts the percentage of remaining erase / write cycles. Average delay of block erase The medium health index is calculated according to the following formula. : ,in, The erase delay for the reference block is set to 1.2ms; This is the first weighting coefficient, with a value of 0.6; The second weighting factor, with a value of 0.4, is used before the remaining write cycles percentage is included in the calculation. It is first converted to a dimensionless decimal between 0.00 and 1.00. For example, when the remaining write cycles percentage of a solid-state storage device is 80%, The value is set to 0.80. The base block erase delay is 1.2ms. The first weighting coefficient is 0.6 and the second weighting coefficient is 0.4. These factors are used together in the calculation to make the media health index range from 0.00 to 1.00, which is dimensionless and can be directly compared with the preset health threshold of 0.70.

[0052] When the media health index When the temperature drops below the preset health threshold of 0.70, the storage medium wear sensing module calculates the dynamic blocking time window according to the following formula. : ,in, The baseline blocking time is set to 5ms; The blocking adjustment coefficient is set to 3.0, within the dynamic blocking time window. Internally, the layered persistence management module blocks synchronous hard disk flushing commands submitted by upper-layer applications, temporarily storing the data to be persisted in a non-volatile memory buffer layer with independent power supply protection. When the dirty page rate of the online write cache data pages reaches a preset extreme value of 90%, or a dynamic blocking time window is reached... When the deadline is reached, the tiered persistence management module triggers a multi-page continuous merging and flushing, submitting the continuous page block data in non-volatile memory to the sequential append write area of ​​the solid-state drive in one go, so as to reduce the number of read, modify, write and physical erase / write operations of the solid-state storage device.

[0053] During the blocking wait period, the non-volatile memory buffer layer with independent power supply protection is powered by a supercapacitor backup power system. In the event of an external power failure or hardware failure, the supercapacitor backup power system will automatically start and maintain power supply to the buffer layer for at least 30 seconds. At the same time, the hardware power failure detection circuit triggers an emergency disk flushing interrupt, and writes all dirty page data in the non-volatile memory to the non-volatile append area of ​​the solid-state drive in the form of contiguous page blocks through the direct memory access channel, saving the transaction logs that have been responded to and committed.

[0054] If the dynamic blocking time window has not expired, and the dirty page occupancy rate of the non-volatile memory buffer layer reaches the warning level of 85%, the system wakes up the background multi-page continuous merging and flushing thread and puts it into a waiting state; when the dirty page rate continues to reach 90% or the dynamic blocking time window expires, the hierarchical persistence management module releases the hard disk flushing blocking, and the thread sequentially writes the buffered data to the sequential append write area of ​​the solid-state drive and releases the corresponding memory.

[0055] After a cross-node network outage is recovered, concurrent writes by multiple master nodes during the outage may cause conflicts between the remote state and the local state. The state differential resolution module initiates the in-situ incremental vector merging module to receive the deterministic state vector sent by the remote storage node and extract the preceding state hash value. , and the local current state hash value The matching process is performed, and when the two are inconsistent, the in-situ incremental vector merging module searches backward along the directed acyclic graph of the state change to find the common ancestor node. Extract the local write difference vector generated after extracting the common ancestor node. Write the difference vector at the far end .

[0056] The in-situ incremental vector merging module parses the algebraic attributes of the change fields in the two write difference vectors, including additive commutative numerical fields involving increases or decreases in inventory quantity. The vector superposition value is calculated according to the following formula, and the composite difference vector is generated. : After generating the composite difference vector, the in-situ incremental vector merging module completes the in-situ incremental update on the corresponding storage page of the online write cache data page, for restricted fields involving the ownership status of goods and belonging to mutually exclusive attributes. Extract the network-wide logical timestamps contained in the local transaction log write difference vector and the remote transaction log write difference vector. The valid status is determined based on the order of timestamps, and the valid status overwrites the historical fields.

[0057] The state-change directed acyclic graph (DAG) construction module maintains the DAG in memory in the form of an adjacency list. The adjacency list consists of vertices and directed edges. The vertex table nodes store deterministic global state hash values, and the directed edge table nodes store the transaction log write difference vectors and transaction commit sequence numbers associated with two state vertices. The in-situ incremental vector merging module uses the transaction commit relationships recorded by each directed edge to search backward from the vertex corresponding to the current local state until it finds the common ancestor node that the local state path and the remote state path both point to.

[0058] When parsing a transaction write request, the state differential parsing module reads the pattern dictionary descriptor loaded with the warehouse storage page header information. This descriptor records the mapping relationship between physical byte offsets and business semantic fields. Specifically, the four-byte interval from byte 0 to byte 3 within the storage page is mapped to the inventory quantity increase / decrease value field, and the four-byte interval from byte 4 to byte 7 is mapped to the goods ownership restriction status field. After receiving the deterministic status vector sent by the remote warehouse node, the in-situ incremental vector merging module parses the binary data slices at the corresponding byte offsets in the write differential vector into the corresponding business field values ​​or enumerated statuses according to the pattern dictionary descriptor. For the inventory quantity increase / decrease value field, algebraic overlay is performed, and for the goods ownership restriction status field, time-series overlay based on the network-wide logical timestamp is performed.

[0059] Example 4: This example combines Figures 1 to 2 The document describes a dynamic scheduling system used for cross-border warehousing data management, such as... Figure 1As shown, the dynamic scheduling system for cross-border warehousing data management includes a local storage acceleration module, a state differential parsing module, a dynamic transaction queue scheduling module, a speculative lock-free slicing channel, a deterministic state vector channel, a hierarchical persistence management module, and local hierarchical storage media. The local storage acceleration module receives transaction requests and generates online write cache data pages and dynamically appended logs. The state differential parsing module, connected to the local storage acceleration module, extracts the transaction log write differential vector, parses the warehousing entity volatility index and synchronization delay estimate, and is connected to an acknowledgment packet tracking module. The packet tracking module captures cross-border acknowledgment packets, calculates round-trip time, and derives a synchronization delay estimate. The dynamic transaction queue scheduling module, connected to the state differential parsing module, derives priority scores based on the volatility index and delay estimate, compares these scores to a preset split threshold, and performs dynamic traffic splitting. The dynamic transaction queue scheduling module is also connected to a dynamic threshold ballast module, which detects network acknowledgment packet loss and limits traffic and raises the preset split threshold when the state is abnormal. A speculative lock-free slicing channel, connected to the dynamic transaction queue scheduling module, pushes transactions into the log when the priority score falls below the preset split threshold. The write differential vector overwrites the changed data in the lock-free slot to complete in-situ overlay. The speculative lock-free slicing channel contains a bitmap mask parsing module and a one-way lock-free ring slot buffer module. The bitmap mask parsing module is used to generate a write mask bitmap and perform lock-free mapping write. The one-way lock-free ring slot buffer module is connected to the bitmap mask parsing module and is used to overwrite the binary stream according to the mask and achieve lock-free overlay through atomic comparison. The deterministic state vector channel is connected to the dynamic transaction queue scheduling module and is used to push the transaction log write differential vector when the priority score is not lower than the preset splitting threshold, providing strong synchronization routing for cross-node data. The hierarchical persistence management module is connected to both the speculative lock-free slicing channel and the deterministic state vector channel. It is used to trigger adaptive disk flushing and commit when the data reaches the 4KB physical sector alignment boundary. The hierarchical persistence management module contains an alignment detection module and an adaptive disk flushing triggering module. The alignment detection module is used to periodically scan the stacking slots and detect the continuous data volume. The adaptive disk flushing triggering module is connected to the alignment detection module and is used to activate and commit to the hierarchical storage medium when the physical sector boundary is met. The local hierarchical storage medium is connected to the hierarchical persistence management module and is used to contain non-volatile memory and solid-state drive append areas.

[0060] like Figure 2As shown, the dynamic scheduling system for cross-border warehouse data management includes a local storage acceleration module, a state differential resolution module, a dynamic transaction queue scheduling module, a hierarchical persistence management module, and a local hierarchical storage medium connected in sequence. The local storage acceleration module is used to transmit data with the state differential resolution module, the state differential resolution module is used to transmit data with the dynamic transaction queue scheduling module, the dynamic transaction queue scheduling module is used to transmit data with the hierarchical persistence management module, and the hierarchical persistence management module is used to transmit data with the local hierarchical storage medium.

[0061] Example 5: Before a new node connects to the cross-border warehouse data management network, the local storage acceleration module sends an idle probe packet to the target remote warehouse node, collects 500 consecutive round-trip delays and calculates the arithmetic mean, and uses this average value to establish a synchronization delay estimate. The initial baseline is established, and then the local generator injects test transaction flows covering all field offsets into the online write cache data pages, gradually increasing the frequency and magnitude of transaction modifications, and calculating the warehouse entity volatility index. Before calculating the priority score, the estimated synchronization delay and the warehouse entity volatility index are processed according to the established dimensional normalization standard within the range of values. Then, the normalized values ​​are substituted into the following formula: The dynamic transaction queue scheduling module calculates priority scores under different loads based on this. Draw priority scores The cumulative probability distribution curve was obtained, and the priority score corresponding to the 80th percentile was selected. As the initial preset splitting threshold Complete parameter calibration and baseline setting in the initial operating environment of the new node.

[0062] When a physical memory bit flip or page check anomaly occurs in the unidirectional lockless ring slot buffer module, the bitmap mask parsing module parses the transaction log and writes the differential vector. Extract storage page identifier With byte offset Before updating the memory slot, the integrity of the changed data binary stream is verified using a cyclic redundancy check (CRC) code. If the data verification fails or a byte offset occurs... When the memory page boundary is exceeded, the bitmap mask parsing module stops executing the atomic overwrite in the unidirectional lock-free circular slot buffer module and writes the transaction log to the differential vector. Forward to the dynamic append log area of ​​the solid-state drive in the local tiered storage medium for sequential appending.

[0063] The state differential parsing module simultaneously receives the verification anomaly signal, reads the previous deterministic state page along the directed acyclic graph of state changes, and reloads it into the online write cache data page. After the state page loading is completed, the state differential parsing module performs verification recovery and state correction on the memory slot data structure, and the speculative lock-free slice channel continues to receive concurrent writes.

[0064] Example 6: When cross-border network routes change or physical link performance degrades, the round-trip delay distribution drifts accordingly. The state difference resolution module initiates a baseline reconstruction procedure within a preset time window. For each sampling period, round-trip time delay data of cross-border confirmation packets are continuously captured, and the time-domain variance of the round-trip time delay is calculated. The deviation threshold is based on a 15ms time delay deviation, which is converted into the square of the same dimension as the time domain variance before being compared; when the time domain variance within 3 consecutive sampling periods... When all deviations exceed the threshold, the state difference analysis module introduces a decay factor. Update the synchronization delay estimate.

[0065] The state differential parsing module will update the synchronization delay estimate before the update. Arithmetic mean of round-trip delay within the current sampling period Substituting into the following formula, we obtain the updated synchronization delay estimate. : Among them, attenuation factor The value is 0.85, which is the updated synchronization delay estimate used by the dynamic transaction queue scheduling module. Recalculate the existing transaction log write differential vector in the online write cache data pages. Priority score Draw priority scores The cumulative probability distribution curve, and the priority score corresponding to the 80th percentile. Assign a value to the preset splitting threshold Based on this, the network latency baseline and dynamic scheduling parameters are updated.

[0066] During multi-node cluster deployment, the local storage acceleration modules deployed on each node monitor the memory usage of online write cache data pages in real time through the cluster coordination unit. When the memory usage of a certain node The preset traffic splitting threshold of 75% is reached, and the memory usage of adjacent nodes is... When the percentage is below 40%, the local storage acceleration module of that node extracts a priority score. Below the preset splitting threshold Transaction log write difference vector It forwards the data to the online write cache of adjacent nodes via the internal high-speed bus, thereby reducing the memory growth rate of the online write cache data pages of this node and delaying the time when its memory usage reaches the 85% safety limit.

[0067] When the average memory usage of online write cache data pages on each node in the cluster reaches 70% or more, the tiered persistence management module initiates the cluster adaptive disk flushing procedure, adjusting the baseline blocking time. The blocking time is gradually reduced to a preset minimum of 2ms, which enables the unidirectional lock-free ring slot buffer module to accelerate the submission of page block data that has been aligned with the physical sector boundary to the local hierarchical storage medium. The hierarchical persistence management module records the data flushing success signal and releases the memory slots that have been persisted in the online write cache data pages, so as to adjust the cache usage and data flushing progress of each node when the cluster expands and the write traffic increases.

[0068] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A dynamic scheduling system for cross-border warehousing data management, characterized in that, include: The local storage acceleration module is used to receive transaction write requests, generate online write cache data pages and dynamically append logs; The state differential parsing module is used to extract the transaction log write differential vector containing storage page identifier, byte offset, changed data binary stream, incrementing sequence number and write mask bitmap, and to parse the warehouse entity volatility index and synchronization delay estimate. The dynamic transaction queue scheduling module includes a deterministic state vector channel and a speculative lock-free slice channel. It is used to derive priority scores based on the warehouse entity volatility index and the synchronization delay estimate. When the priority score is lower than the preset splitting threshold, the transaction log write differential vector is pushed into the speculative lock-free slice channel, and vice versa. The hierarchical persistence management module is connected to the dynamic transaction queue scheduling module and the local hierarchical storage medium; The speculative lockless slicing channel includes a one-way lockless ring slot buffer module and a bitmap mask parsing module. It is used to write the transaction log write differential vector into the one-way lockless ring slot buffer module using atomic comparison and exchange instructions. When the storage page identifier is the same and the incrementing sequence number is incremented, the in-situ overlay is completed by overwriting the changed data binary stream according to the byte offset and the write mask bitmap. The tiered persistence management module includes an alignment detection module and an adaptive flush triggering module. The adaptive flush triggering module is activated and the data is submitted to the local tiered storage medium when the data volume reaches the 4KB physical sector alignment boundary.

2. The dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The transaction log write differential vector also includes the changed field identifier, the state hash value before the change, and the state hash value after the change; After receiving the transaction log write differential vector corresponding to the transaction write request, the bitmap mask parsing module extracts the storage page identifier, byte offset, and changed data binary stream and generates a write mask bitmap. It then uses atomic comparison and exchange instructions to write the byte offset and write the write mask bitmap into the slot node of the corresponding storage page identifier in the unidirectional lock-free ring slot buffer module.

3. The dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The state differential parsing module includes an acknowledgment packet tracking module. The acknowledgment packet tracking module is connected to the cross-node network and is used to capture cross-border acknowledgment packets sent to the historical transaction log write differential vector of the remote storage node, calculate the round-trip time of the cross-border acknowledgment packets, calculate the moving average of the round-trip time for a preset number of round-trip times, and input the derived moving average as the synchronization delay estimate into the dynamic transaction queue scheduling module.

4. A dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The dynamic transaction queue scheduling module includes a dynamic threshold ballast module and a circuit breaker detection module; the circuit breaker detection module is used to monitor the response status of data packets sent to remote storage nodes in real time. When the circuit breaker detection module detects that the number of network acknowledgment packet losses exceeds the preset loss threshold of 5 times, the dynamic threshold ballast module is activated, raising the preset splitting threshold by 200% to restrict the data flow into the deterministic state vector channel and transfer the data containment pressure to the speculative unlocked slicing channel.

5. A dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The hierarchical persistence management module includes a local version tree construction module and a cache monitoring module. The cache monitoring module is used to detect the memory usage of online write cache data pages in the local storage acceleration module in real time. When the memory usage reaches the preset safety limit of 85%, the hierarchical persistence management module stops receiving data from speculative lock-free slice channels, starts the local version tree construction module, constructs a local version tree from the data slices in the dynamically appended log based on the hash values ​​of the state before and after the change, and performs conflict cancellation and merging of multiple modifications to the same field in memory. After generating a compressed write vector, it is sequentially written to the solid-state drive append area of ​​the local hierarchical storage medium.

6. A dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The tiered persistence management module includes a storage media wear detection module; the storage media wear detection module is used to read the self-monitoring analysis and reporting technical parameters of solid-state storage devices in the local tiered storage media, extract the percentage of remaining erase / write cycles and the average block erase latency, and export the media health index. When the media health index is lower than the preset health threshold, the storage media wear sensing module calculates the dynamic blocking time window based on the media health index and blocks the hard disk flushing command within the dynamic blocking time window, temporarily storing the data in a non-volatile memory buffer layer with independent power supply protection until the dirty page rate reaches the preset extreme value of 90% or the dynamic blocking time window expires, triggering multi-page continuous merging and disk flushing.

7. A dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The state difference analysis module includes an in-situ incremental vector merging module and a directed acyclic graph construction module for state changes; The state-change directed acyclic graph (DAG) construction module is used to construct the state-change DAG. After the cross-node network interruption is recovered, the in-situ incremental vector merging module receives the deterministic state vector sent by the remote storage node. When the previous state hash value is detected to be inconsistent with the local current state hash value, the in-situ incremental vector merging module searches backward along the state-change DAG to the common ancestor node, extracts the local write difference vector and the remote write difference vector, calculates the vector superposition value for the additivity commutative law numerical fields involving the increase or decrease of inventory quantity, generates a synthetic difference vector, and completes the in-situ incremental update on the online write cache data page.

8. A dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The tiered persistence management module also includes a timeout-filled disk flushing trigger module. This module monitors the first write latency of slot data in the unidirectional unlocked ring slot buffer module. When the data volume of the stacked slots in the unidirectional unlocked ring slot buffer module does not reach the 4KB physical sector alignment boundary, but the first write latency reaches the preset limit blocking time window of 10ms, the timeout-filled disk flushing trigger module adds zero padding bits to the end of the data to align with the 4KB physical sector boundary and submits the aligned page block data to the local tiered storage medium.

9. A dynamic scheduling system for cross-border warehousing data management according to claim 1, characterized in that, The local tiered storage media includes non-volatile memory, solid-state drives (SSDs), and hard disk drives (HDDs). The tiered persistence management module includes a media routing allocation module, which is used to directly submit the data output from the deterministic state vector channel to the non-volatile memory for persistence, and to submit the data pages in the speculative lock-free slice channel that have been overlaid and stacked and have reached the 4KB physical sector alignment boundary to the sequential append write area of ​​the SSD.

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