Credit repair business collaborative management system

Abstract

This invention discloses a collaborative management system for credit repair business. The system consists of an initiating node, collaborating nodes, and a consistency control and compensation layer. The initiating node analyzes task characteristics, generates a state vector containing trigger probability, lifecycle, resource quota, and source hash, and broadcasts speculative execution communication frames. Collaborating nodes parse the frames and, when a threshold is met, lock physical memory pages in an isolated environment and start thread preprocessing. Data changes are recorded in an offset mapping table without overwriting the original physical blocks. The control and compensation layer receives the result signal; if it is a confirmation, it submits and solidifies the state; if it is a withdrawal, it performs constant-time complexity resource rollback and memory zeroing based on the hash index. This invention, through distributed speculative execution, transforms the serial waiting of cross-departmental approvals into parallel preprocessing, greatly reducing system blocking caused by long transactions while ensuring data consistency, and significantly improving collaborative efficiency and resource utilization.

Description

Technical Field

[0001] This invention relates to the field of distributed computing and system architecture, specifically to a collaborative management system for credit repair business. Background Technology

[0002] Currently, credit repair services in cross-departmental collaborative processing generally adopt a serial triggering mode based on transaction atomicity, consistency, isolation, and durability. In this mode, after a user initiates a credit repair application, the system must wait for the original penalty authority to complete the final administrative approval and update the underlying database before the collaborating nodes can receive a confirmation signal and initiate the internal repair process.

[0003] Due to differences in approval cycles and data synchronization frequencies among different departments, this serial waiting mechanism leads to significant business cycle delays. Furthermore, the system's long transaction suspension state while awaiting final confirmation consumes substantial system I / O resources. Current technical concepts typically hold that credit data should only be transferred across nodes after the final approval result is determined to avoid generating dirty data or causing system inconsistencies. This technical bias limits further improvements in the efficiency of credit repair processing. Summary of the Invention

[0004] The present invention aims to solve the problems of low processing efficiency, long business cycle, unreasonable system resource consumption, and high latency in data synchronization in a distributed environment in existing credit repair systems when there is cross-departmental collaboration.

[0005] The above-mentioned technical objective of the present invention is achieved through the following technical solution: a credit repair business collaborative management system, comprising:

[0006] The initiating node is used to extract features of the credit repair task and generate a multi-dimensional state vector containing trigger probability, resource quota, and source hash. and broadcasts the multidimensional state vector to the collaborating nodes. The inferred execution of communication frames; The collaborative node is used to parse the communication frame and determine whether the speculative execution condition is met based on the trigger probability. If it is met, the physical memory page is locked in the isolated execution environment according to the resource quota and a preprocessing thread is started to perform business logic preprocessing. A consistency control and compensation layer is used to receive the final approval result signal. If the signal is a confirmation submission, an in-memory submission is performed to solidify the preprocessed state. If the signal is an invalid withdrawal, physical resource rollback and release are performed according to the traceability hash.

[0007] Furthermore, the multidimensional state vector Represented as ,in: To enable the trigger probability threshold for speculative execution; The lifespan of the pre-occupied resources; The physical resource quota allocated to the speculative execution thread; This is a source hash index used to locate the resources used by the speculative execution task.

[0008] Furthermore, the initiating node includes: A metadata extraction engine is used to quantify the success probability of the credit repair task by performing entropy reduction analysis on the input evidence. The vector generation module is used to generate the multidimensional state vector based on the repair success probability and a preset resource scheduling strategy. .

[0009] Furthermore, the collaborative nodes include: The threshold determination module is used to compare the multidimensional state vector. The trigger probability and preset water level are used to determine the timing of starting the speculative execution thread; The physical resource locking module is used to allocate a temporary buffer in the physical memory of the cooperating node and lock the data pages related to the speculative execution task.

[0010] Furthermore, the data changes generated during the business logic preprocessing are recorded in the memory offset mapping table, rather than directly overwriting the original physical storage block of the collaborating node.

[0011] Furthermore, the consistency control and compensation layer includes: An atomic rollback module is used to perform a resource index retrieval with constant-time complexity using the source hash when a failure withdrawal signal is received. The physical resource release module is used to perform memory zeroing and asynchronous truncation of the preprocessing instruction stream based on the retrieval results.

[0012] The present invention also provides a management method for the above-mentioned credit repair business collaborative management system, comprising: The initiating node generates a multi-dimensional state vector containing trigger probability, resource quota, and source hash. And broadcast speculative execution communication frames to the collaborating nodes; The cooperating node parses the communication frame and, when the trigger probability condition is met, locks the physical memory page and starts the preprocessing thread in the isolated execution environment; Based on the received final approval result signal, the consistency control and compensation layer selects to perform a memory commit operation or a physical resource rollback operation based on the traceability hash.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention introduces multi-dimensional state vectors to predict task achievement trends, enabling collaborative nodes to shift from passive waiting to proactive preprocessing, thus shortening the overall business cycle of cross-departmental collaboration.

[0014] 2. By setting up an isolated execution environment and a physical memory locking mechanism at the collaborative nodes, this invention enables business preprocessing without interfering with the main production environment data, thus ensuring the security and isolation of system data.

[0015] 3. This invention utilizes source hashing to establish a distributed resource index, enabling constant-time rollback of physical memory and thread resources in the event of prediction failure, thus ensuring the consistency of data in the distributed system.

[0016] 4. This invention achieves fine-grained allocation of computing resources through resource quota parameters in the state vector, avoiding excessive resource consumption during speculative execution and improving the overall throughput of the system.

[0017] 5. This invention reduces system I / O blocking and solves the communication latency problem in long transaction processing by converting the final confirmation mechanism into a predictive execution + asynchronous hedging mechanism. Attached Figure Description

[0018] Figure 1 This is a logical architecture diagram of the credit repair business collaborative management system according to an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] like Figure 1 The diagram illustrates the interaction logic between the initiating node (credit processing center), collaborating nodes (banks / bidding offices / market supervision departments), and the consistency control and compensation layer. Specifically, the initiating node performs feature extraction and vector generation; the collaborating nodes perform frame parsing, threshold determination, and task preprocessing in an isolated environment; and the consistency control and compensation layer performs final state solidification or atomic rollback.

[0021] This invention provides a collaborative management system for credit repair services, whose overall architecture logically consists of three core layers: an initiating node, collaborating nodes, and a consistency control and compensation layer. The initiating node, serving as the entry point for task processing logic, integrates application reception and data upload functional modules. When the system receives a target task application and related supporting materials (such as case closure certificates, performance vouchers, etc.) submitted by the applicant, the metadata extraction engine is activated. This engine performs feature quantification processing on key dimensions in the uploaded materials using preset feature extraction rules. The extraction scope includes, but is not limited to, execution amount, performance time limit, case type level, and material completeness indicators. Based on the extracted feature quantification data, the vector generation module initiates the calculation process, generating a multi-dimensional state vector by performing feature matching processing between the current task features and the preset task feature space. The state vector Includes trigger probability Survival time cycle Resource quotas and source hash After vector construction is complete, it is presumably assumed that the communication frame distribution module encapsulates the vector into an asynchronous communication frame and distributes it non-blockingly to the distributed cooperative node group via an asynchronous communication protocol. The state vector... Resource scheduling strategies and execution path selection are used to drive collaborative nodes.

[0022] The collaborating node receives a multi-dimensional state vector. After receiving the asynchronous communication frame, the internal frame parsing and arbitration engine unpacks the frame content. The threshold determination module receives the state vector. Trigger probability in It then performs real-time verification against the locally set dynamic security threshold. If the trigger probability... If the preset water level is not reached, the system determines that the expected completion rate of the task is insufficient to offset the preprocessing overhead, and the task will be placed in a regular pending queue and suspended. If the trigger probability... If the preset conditions are met, the system initiates the speculative execution mechanism. At this time, the collaborating nodes, based on the vector... Resource quotas The parameters are used by the physical resource locking module to request and lock a buffer of a specific size in the physical memory space, while thread preemption is performed according to task priority. The locked memory page is marked as a "speculated" data area at this time, and the system's memory management mechanism ensures that data in this area will not be swapped out to the swap partition.

[0023] Within the isolated execution environment (Sandbox), the target task processing logic module performs pre-computation. This isolated execution environment employs process-level isolation or lightweight container isolation technology, possessing an independent memory address space and task scheduling identifier. This ensures that all data write operations generated during preprocessing only affect the previously locked memory offset mapping table. Because data changes are strictly confined to a controlled temporary buffer and are not merged with the physical blocks of the main production database, the original system state of the collaborating nodes remains consistent even when the speculative path is running, eliminating interference from dirty data caused by preprocessing. During this period, the preprocessing thread can complete complex computational tasks, such as state recalculation, indicator pre-simulation, and prediction of associated admission conditions, and temporarily store the results in the isolated environment.

[0024] The target task maintains a speculative execution state on the collaborating nodes until its lifetime expires. The system either resets to zero or receives a clear final confirmation instruction. The consistency control and compensation layer monitors the administrative processing flow status of the initiating node in real time. When the final result signal receiver receives a confirmation signal indicating that processing has passed, the system triggers the Commit path. At this point, the memory commit and state solidification module intervenes, and the system atomically merges the preprocessed results originally recorded in the memory offset mapping table with the main storage space of the collaborating nodes at the physical block level. This process only involves pointer redirection or synchronization of a small amount of data, avoiding the response delay caused by starting processing logic calculations after obtaining the final result.

[0025] If the final result signal received by the receiver indicates a failed withdrawal, the system triggers the Abort path and enters the compensation process. The atomic rollback module based on hash indexes utilizes state vectors. Source hash in A globally unique resource link is established, and a fast retrieval operation with constant-time complexity is performed to accurately locate all physical resources occupied by the task in the distributed cluster. The physical resource release module then immediately performs a memory zeroing operation, erasing the corresponding temporary buffer data and forcibly terminating the relevant preprocessing threads. Thanks to the introduction of a source hashing mechanism, the system can achieve instantaneous resource release without traversing the global log or executing complex hedging transaction flows. This mechanism ensures that in the event of prediction failure, the system can quickly eliminate the side effects of speculative execution, guaranteeing the dynamic balance of resources and data consistency among collaborating nodes.

[0026] This implementation uses credit repair as an example, but the invention is also applicable to other distributed systems that require long-term cross-node collaborative processing. By deeply coupling the prediction vector at the initiating end with the isolated speculative execution at the collaborating end, the system achieves accelerated processing of cross-departmental collaborative business without relying on the immediate delivery of external final results.

[0027] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A collaborative management system for credit repair business, characterized in that, include: The initiating node is used to extract features of the credit repair task and generate a multi-dimensional state vector containing trigger probability, resource quota, and source hash. and broadcasts the multidimensional state vector to the collaborating nodes. The inferred execution of communication frames; The collaborative node is used to parse the communication frame and determine whether the speculative execution condition is met based on the trigger probability. If it is met, the physical memory page is locked in the isolated execution environment according to the resource quota and a preprocessing thread is started to perform business logic preprocessing. A consistency control and compensation layer is used to receive the final approval result signal. If the signal is a confirmation submission, an in-memory submission is performed to solidify the preprocessed state. If the signal is a failed withdrawal, then physical resource rollback and release are performed based on the source hash.

2. The credit repair business collaborative management system according to claim 1, characterized in that, The multidimensional state vector Represented as ,in: To enable the trigger probability threshold for speculative execution; The lifespan of the pre-occupied resources; The physical resource quota allocated to the speculative execution thread; This is a source hash index used to locate the resources used by the speculative execution task.

3. The credit repair business collaborative management system according to claim 1, characterized in that, The initiating node includes: A metadata extraction engine is used to quantify the success probability of the credit repair task by performing entropy reduction analysis on the input evidence. The vector generation module is used to generate the multidimensional state vector based on the repair success probability and a preset resource scheduling strategy. .

4. The credit repair business collaborative management system according to claim 1, characterized in that, The collaborative nodes include: The threshold determination module is used to compare the multidimensional state vector. The trigger probability and preset water level are used to determine the timing of starting the speculative execution thread; The physical resource locking module is used to allocate a temporary buffer in the physical memory of the cooperating node and lock the data pages related to the speculative execution task.

5. The credit repair business collaborative management system according to claim 4, characterized in that, Data changes generated during the business logic preprocessing process are recorded in a memory offset mapping table, rather than directly overwriting the original physical storage block of the collaborating node.

6. The credit repair business collaborative management system according to claim 1, characterized in that, The consistency control and compensation layer includes: An atomic rollback module is used to perform a resource index retrieval with constant-time complexity using the source hash when a failure withdrawal signal is received. The physical resource release module is used to perform memory zeroing and asynchronous truncation of the preprocessing instruction stream based on the retrieval results.

7. A management method for a credit repair business collaborative management system as described in any one of claims 1 to 6, characterized in that, include: The initiating node generates a multi-dimensional state vector containing trigger probability, resource quota, and source hash. And broadcast speculative execution communication frames to the collaborating nodes; The cooperating node parses the communication frame and, when the trigger probability condition is met, locks the physical memory page and starts the preprocessing thread in the isolated execution environment; Based on the received final approval result signal, the consistency control and compensation layer selects to perform a memory commit operation or a physical resource rollback operation based on the traceability hash.

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