Block chain-based integral shopping mall operation and maintenance management method and system

Abstract

The invention discloses an integral shopping mall operation and maintenance management method and system based on a block chain, and the method comprises the following steps: recording the issuing, use and exchange of an integral through the block chain, guaranteeing that transaction information is transparent and cannot be tampered, employing a quantum random number generation algorithm, randomly issuing the integral based on the transaction history and behavior data of a user, and carrying out the operation and maintenance of an integral shopping mall. Through a market regulation and control algorithm, the redemption value of the credits is dynamically adjusted, market supply and demand are balanced, a two-way compensation mechanism is built in the system, compensation calculation is carried out aiming at credits redemption operation which is not completed on time, a distributed monitoring module monitors credits transaction and a system state in real time, a parameter threshold value is set, and an alarm signal is triggered. The system supports cross-platform point sharing and synchronization, analyzes shopping mall flow data through the operation and maintenance management module, performs system maintenance and updating in a low-flow time period, and ensures stable operation of the shopping mall.

Description

Technical Field

[0001] The present invention relates to the field of blockchain technology, and in particular to a blockchain-based points mall operation and maintenance management method and system. Background Art

[0002] With the rapid development of e-commerce platforms, the points system has become an important tool for e-commerce platforms to maintain customer loyalty and motivate user behavior. The points system provides users with additional consumption benefits by rewarding users for their consumption, promotion and other behaviors on the platform. However, the traditional points system has some significant technical defects, which hinders its further development and application.

[0003] The trust issue of the traditional points system is a long-standing pain point. Since the points data is mostly stored on centralized servers, users and merchants cannot clearly and transparently track the issuance, redemption and use of points. This centralized management method is very likely to cause problems such as points tampering and abuse, which weakens users' trust in the platform. The centralized points management system has poor security and is easily targeted by attacks, resulting in users' points accounts being stolen or transaction records being tampered with.

[0004] Low efficiency of manual operation is another major shortcoming of the traditional points system. In the process of issuing, redeeming and settling points, a large amount of manual operation is usually required, which not only increases the operating costs of merchants, but also easily leads to human errors, affecting user experience. The operating procedures of the points system are usually complicated and cannot quickly and accurately complete the user's points redemption needs, thus affecting the user's experience; the instability of the value of points is also a problem faced by users and merchants. In the traditional system, the redemption value of points is often fixed and cannot be dynamically adjusted according to changes in market supply and demand, resulting in fluctuations in the value of points, affecting users' enthusiasm for using points. The system lacks effective management of market variables such as user transaction behavior and redemption frequency, and cannot promptly reflect changes in market demand, resulting in waste of resources.

[0005] The difficulty in sharing and synchronizing points across platforms and merchants also limits the widespread application of the points system. In the existing technology, points are mostly limited to a single platform or a single merchant, and users cannot use points freely between multiple platforms. This not only limits the scope of users' points usage, but also weakens the flexibility and attractiveness of points. In terms of operation and maintenance management, the maintenance efficiency of traditional points mall systems is low. Since it is impossible to intelligently analyze and adjust maintenance time based on the mall's real-time traffic data, system maintenance is often carried out during peak hours, resulting in a decline in user experience and a significant impact on mall operations. System status updates also rely heavily on manual intervention and lack automated processing capabilities, which can easily lead to data security issues or system crashes.

[0006] Therefore, how to provide a blockchain-based points mall operation and maintenance management method and system is a problem that technical personnel in this field urgently need to solve. Summary of the invention

[0007] One purpose of the present invention is to propose a blockchain-based points mall operation and maintenance management method and system. The present invention makes full use of blockchain technology, quantum random number algorithm, distributed market regulation and intelligent contract and other technologies, and describes in detail the implementation methods of transparent issuance of points, dynamic value adjustment, cross-platform sharing and automatic operation and maintenance of the system. It has the advantages of transparent transactions, high degree of automation, flexible use of points and efficient operation and maintenance.

[0008] A method and system for operation and maintenance management of a points mall based on blockchain according to an embodiment of the present invention comprises the following steps:

[0009] S1. Use blockchain technology to record the issuance, use and redemption of points. Point transaction information is stored on the blockchain. A segmented point recording method is adopted to store the points issuance, redemption and consumption records on different nodes to distribute the points data load and optimize the transaction processing speed.

[0010] S2. Use quantum random points issuance algorithm to generate unpredictable random numbers based on quantum bits, control the number of points obtained by users after completing specified operations, and automatically execute points issuance through smart contracts. The number of points is determined based on the weighted calculation of user transaction history, behavior data and quantum random numbers, so that each point issuance is independent, avoiding repetitive and patterned point issuance;

[0011] S3. Through the distributed multi-dimensional market value control algorithm, the redemption value of points is dynamically adjusted based on multiple variables such as user redemption requests, commodity inventory, transaction frequency, and point circulation speed. Combined with the data synchronization function of distributed nodes, the redemption conditions of points are balanced in real time according to changes in market supply and demand to prevent fluctuations in redemption value.

[0012] S4. Based on the generated points transaction records and market regulation results, the system automatically executes the points redemption process through smart contracts and sets a time limit for the redemption process. Points redemption that is not completed within the scheduled time will trigger a two-way compensation process based on smart contracts. The process calculates corresponding compensation for both parties based on the degree of timeout, and automatically deducts and compensates points through the contract;

[0013] S5. Through the distributed monitoring mechanism on the blockchain, real-time monitoring of points transactions and system status is carried out, transaction and system parameter thresholds are set, and the system automatically sends out an alarm signal when the threshold is exceeded, and records detailed logs of abnormal transactions and system status;

[0014] S6. Supports users to share and synchronize points between multiple platforms and merchants. Points synchronization is based on cross-chain protocols. Users’ points operations on one platform can be synchronized and used on another platform through blockchain protocols.

[0015] S7. The operation and maintenance management module automatically handles system status updates, notifies users and merchants before routine maintenance, selects low-traffic periods for maintenance through intelligent analysis of mall traffic data, and performs status updates.

[0016] Optionally, the S2 specifically includes:

[0017] S21, quantum random number R q The generation is based on the superposition state of the qubit, which is |0>+|1>. When measured, the superposition state of the qubit randomly collapses to 0 and 1, and the generated random numbers are unpredictable and non-repeatable.

[0018] S22. When the user's transaction behavior reaches the predetermined conditions, the system triggers the quantum random number R q The generation of the conditions includes that the user's transaction amount and transaction frequency exceed the set threshold T u When the user's transaction behavior does not reach the threshold, the system uses a pseudo-random number R p Distribute points to optimize system resources;

[0019] S23, quantum random number R q The generation frequency depends on the user's activity A u Dynamic adjustment: the higher the user's activity, the faster the frequency of quantum random number generation. The system automatically increases the usage ratio of quantum random numbers based on the user's activity.

[0020] S24. The system chooses to use quantum random number R according to different transaction scenarios. q and the pseudo-random number R p Points are distributed, with quantum random numbers used for high-priority scenarios, including large-value transactions and continuous high-frequency transactions, and pseudo-random numbers used for low-priority scenarios;

[0021] S25, quantum random number R q Combined with the user's transaction history data H u and behavioral data B u Perform weighted calculation to determine the number of points P that the user should receive u :

[0022] Pu = α·Hu + β·Bu + γ·Rq;

[0023] Among them, the weighting coefficients α, β, and γ are dynamically adjusted according to the user's behavior and transaction pattern;

[0024] S26, dynamic adjustment of weighting coefficients α, β and γ based on user activity A u And the integral frequency F u :

[0025] α=α0+k1·Au;

[0026] β=β0+k2·Fu;

[0027] γ=γ0+k3·Rq;

[0028] Among them, α0, β0, γ0 are initial weighting coefficients, and k1, k2, k3 are adjustment coefficients.

[0029] Optionally, the S3 specifically includes:

[0030] S31, real-time collection of market data through five variables: user's exchange request, commodity inventory, transaction frequency, points circulation speed and user behavior data, the variables include the user's exchange request quantity R u 、The current inventory level of the product I s 、User's transaction frequency F u , the velocity of the integral in the system V p And the user's behavior data B u , data is transmitted synchronously through distributed nodes, so that each node receives the latest market data;

[0031] S32, the distributed nodes use encryption algorithms to encrypt and transmit market data, and the data synchronization between the nodes includes real-time processing and parsing of the collected variable data, and the data parsed by each node is fed back to other nodes in the system, so that all nodes have the same market data status;

[0032] S33. The system calculates the redemption value V of the points based on the collected market variables. e To make dynamic adjustments:

[0033]

[0034] Among them, V e is the exchange value of the integral, δ, η, ζ, θ are the coefficients regulating the influence of each variable;

[0035] S34. Through the distributed multi-dimensional market value control algorithm, the system adjusts the points redemption conditions according to real-time market supply and demand data and the speed of points circulation:

[0036]

[0037] Among them, P u Points redemption conditions, S uis the difference between supply and demand of the commodity, T u is the adjustment parameter used to control fluctuations in the difference between supply and demand;

[0038] S35. The system uses blockchain technology to process and store data through distributed nodes. Smart contracts automatically execute the adjustment steps of the points redemption value to prevent excessive fluctuations in the points redemption value.

[0039] Optionally, the S4 specifically includes:

[0040] S41. Based on the points transaction records and market control results, the system executes the points redemption process. The system automatically calculates the number of points required by the user according to the redemption request and determines the real-time redemption value according to the market control results. The redemption process needs to be completed within the set predetermined time T e Timeout will trigger the subsequent processing mechanism;

[0041] S42, the system sets a time limit T for the points redemption process e If the redemption operation is not completed within the time limit, the system will calculate the compensation points according to the timeout degree ΔT. The compensation points C p Consider the timeout period and the user's transaction frequency F u And historical transaction data H u Perform weighted calculation:

[0042]

[0043] Among them, κ is the basic compensation coefficient, μ is the control coefficient, and α is the nonlinear adjustment coefficient;

[0044] S43, the system is based on the timeout time ΔT and the time limit T e Dynamically adjust the compensation rules, compensation amount C d Related to the time ratio, integrated with the market transaction load L m And the user's points balance B u :

[0045]

[0046] Among them, B0 is the set integral base value, γ is the adjustment coefficient, which reflects the impact of the integral balance on compensation, and β is the weighted adjustment coefficient of compensation;

[0047] S44. The triggering condition for compensation processing includes that the points redemption request is not received within the scheduled time T e The network interruption exceeds the set time threshold T n , the system performs compensation processing based on these conditions;

[0048] S45. The system automatically executes the deduction and compensation of compensation points, and the processing results are updated to the points transaction record and synchronized to the distributed nodes of the blockchain.

[0049] Optionally, the S5 specifically includes:

[0050] S51. Through the distributed monitoring mechanism on the blockchain, the system monitors the points transaction and system status in real time. The key parameters monitored include the number of transactions, transaction frequency, points circulation speed, system load and user behavior data, which are collected and synchronized through distributed nodes;

[0051] S52, the system based on historical transaction data H t and user behavior data B u Dynamically set the threshold of monitoring parameters. The threshold calculation formula is combined with the transaction volatility σ t and user activity A u :

[0052]

[0053] Among them, T th is the transaction upper limit threshold, λ is the basic control coefficient, A0 is the baseline value of user activity, δ is the activity control index, and N is the total number of transactions;

[0054] S53. When the monitored parameters exceed the set threshold, the system automatically triggers an alarm signal. The alarm conditions include the transaction quantity T n Exceeding the set upper limit T th and system load L m Exceeding the upper load limit L th :

[0055] Et=∑(Tn-Tth), if Tn>Tth;

[0056] El=∑(Lm-Lth), if Lm>Lth;

[0057] Among them, E t and E l They are alarm signals for abnormal transactions and load respectively;

[0058] S54, the system dynamically adjusts the monitoring time interval Δt according to the monitoring results. The standard time interval is to collect data every Δt seconds. If the system load L m If the upper limit is exceeded, the monitoring frequency is accelerated to every Δt / 2 seconds. This time interval is adaptively adjusted according to the changes in system load to match the monitoring frequency with the system status;

[0059] S55. After the alarm signal is triggered, the system automatically generates an abnormal log to record abnormal transactions. t and abnormal system load El The exception logs are synchronized through distributed nodes of the blockchain so that all nodes can obtain the latest exception records.

[0060] Optionally, the S6 specifically includes:

[0061] S61. Users share and generate points synchronously between multiple platforms and merchants. Points data is synchronized between platforms through cross-chain protocols. The transaction frequency and points operation rules of different platforms affect the configuration of synchronization operations.

[0062] S62. Points synchronization is performed through smart contracts, and points operations are recorded and synchronized through blockchain protocols:

[0063]

[0064] Among them, S p The number of points generated for the target platform, S u is the number of points operations performed by the user on the source platform, ΔP i is the weight increment of the target platform, P t is the sum of the weights of each platform;

[0065] S63, the points data is transmitted between distributed nodes, and the nodes use a multi-signature and hash verification mechanism. After the transmission is completed, the points data is recorded on the blockchain;

[0066] S64. The consensus algorithm plays a role in the synchronization of points data on each platform. The successful synchronization of points needs to be confirmed by at least N consensus nodes;

[0067] S65. The merchant type and platform agreement type determine the rules for points sharing. The rules include the scope of application of the points type and the operating permissions between platforms. Merchants can adjust the points sharing strategy according to specific needs.

[0068] Optionally, the S7 specifically includes:

[0069] S71, the operation and maintenance management module automatically processes the status update of the mall system. The system selects low-traffic periods for maintenance operations by analyzing the mall's traffic data;

[0070] S72. The system uses time series algorithm to analyze the historical traffic of the mall. f and real-time traffic R f , and select the low flow period T based on the predicted flow change l Perform maintenance operations;

[0071] S73. The system performs status update operations based on the analysis results of the low-traffic period. The update content includes database backup, cache cleaning, and server performance optimization to ensure the stable operation of the mall system.

[0072] S74, the frequency of system status update is adjusted according to the mall traffic data, and the update frequency is U f According to the average flow F avg and flow peak F peak To make dynamic adjustments:

[0073]

[0074] Among them, U f is the update frequency, U0 is the basic update frequency;

[0075] S75. The system notifies users and merchants in advance before executing the status update. The notification time is determined based on the expected maintenance duration and traffic change trend. The log of the maintenance operation is recorded through distributed nodes and synchronized to the blockchain.

[0076] Optional modules include:

[0077] Blockchain points management module: records the issuance, use and redemption of points through blockchain, stores the issuance and consumption records of points on different nodes, distributes the data processing load and optimizes the transaction processing speed;

[0078] Quantum random points issuance module: uses quantum random number algorithm to generate unpredictable points, issues points through smart contracts, and achieves fairness and randomness in points issuance based on user transaction history, behavior data and quantum random number weighted calculation, avoiding repetitive and patterned points issuance;

[0079] Distributed multi-dimensional market value regulation module: dynamically adjusts the points redemption value based on multiple variables such as user redemption requests, commodity inventory, transaction frequency, and points circulation speed. Combined with the data synchronization function of distributed nodes, it balances the points redemption conditions in real time according to changes in market supply and demand;

[0080] Two-way compensation processing module: In the points redemption process, the system sets a time limit. If the redemption is not completed within the scheduled time, the two-way compensation mechanism will be triggered, the compensation points will be calculated, and the deduction and compensation of points will be automatically executed through smart contracts;

[0081] Distributed monitoring and alarm module: Through the distributed monitoring mechanism on the blockchain, real-time monitoring of points transactions and system status is carried out, transaction and system parameter thresholds are set, and alarm signals are automatically issued when the thresholds are exceeded, and logs of abnormal transactions and system status are recorded;

[0082] Points cross-platform synchronization module: points sharing and synchronization are achieved through cross-chain protocols. Users’ points operations on one platform can be synchronized to other platforms through blockchain protocols, and the synchronization rules of points on each platform can be dynamically adjusted;

[0083] Intelligent operation and maintenance management module: automatically processes mall system status updates, intelligently analyzes mall traffic data, selects low-traffic periods for maintenance operations, including database backup, cache cleanup, and performance optimization, and synchronizes maintenance logs to distributed nodes through blockchain.

[0084] The beneficial effects of the present invention are:

[0085] The present invention solves the trust problems, low efficiency, fluctuation of point value and cross-platform sharing problems in the existing technology of point management through the operation and maintenance management method of the point mall based on blockchain, and has significant beneficial effects. The application of blockchain technology ensures the transparency and security of point issuance, use and redemption. All transaction information is stored on the blockchain and is tamper-proof. Users and merchants can clearly trace the flow of points, which enhances the trust of the system and avoids the abuse and tampering of points. The quantum random number algorithm is combined with the smart contract to automate the issuance and redemption process of points, greatly reducing human intervention, improving the operating efficiency and fairness of the system, and reducing the risk of errors in human operations.

[0086] The distributed multi-dimensional market value regulation algorithm in the present invention can dynamically adjust the redemption value of points according to multi-dimensional variables such as user behavior, market demand and commodity inventory, and will not be affected by market fluctuations, thereby improving user satisfaction with the use of points. Through the cross-chain protocol, points can be shared and synchronized among multiple platforms and merchants, so that users' points can be used freely between different platforms, breaking the limitations of the traditional points system and expanding the scope of application and flexibility of use of points.

[0087] In terms of system maintenance, the present invention introduces an intelligent operation and maintenance management module. By analyzing the traffic data of the mall, the system can automatically update the status and perform maintenance operations during low-traffic periods to ensure that the normal operation of the mall will not be affected by maintenance. All maintenance operations are recorded through the blockchain, and the maintenance logs are transparent, further improving the security and stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0089] Figure 1 This is a flowchart of a blockchain-based points mall operation and maintenance management method and system proposed by the present invention;

[0090] Figure 2 This is a flow chart of quantum random integral issuance in the present invention;

[0091] Figure 3 Schematic diagram of the distributed multi-dimensional market value regulation algorithm of the present invention. DETAILED DESCRIPTION

[0092] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0093] refer to Figure 1-3 , a blockchain-based points mall operation and maintenance management method and system, comprising the following steps:

[0094] S1. Use blockchain technology to record the issuance, use and redemption of points. Point transaction information is stored on the blockchain. A segmented point recording method is adopted to store the points issuance, redemption and consumption records on different nodes to distribute the points data load and optimize the transaction processing speed.

[0095] S2. Use quantum random points issuance algorithm to generate unpredictable random numbers based on quantum bits, control the number of points obtained by users after completing specified operations, and automatically execute points issuance through smart contracts. The number of points is determined based on the weighted calculation of user transaction history, behavior data and quantum random numbers, so that each point issuance is independent, avoiding repetitive and patterned point issuance;

[0096] S3. Through the distributed multi-dimensional market value control algorithm, the redemption value of points is dynamically adjusted based on multiple variables such as user redemption requests, commodity inventory, transaction frequency, and point circulation speed. Combined with the data synchronization function of distributed nodes, the redemption conditions of points are balanced in real time according to changes in market supply and demand to prevent fluctuations in redemption value.

[0097] S4. Based on the generated points transaction records and market regulation results, the system automatically executes the points redemption process through smart contracts and sets a time limit for the redemption process. Points redemption that is not completed within the scheduled time will trigger a two-way compensation process based on smart contracts. The process calculates corresponding compensation for both parties based on the degree of timeout, and automatically deducts and compensates points through the contract;

[0098] S5. Through the distributed monitoring mechanism on the blockchain, real-time monitoring of points transactions and system status is carried out, transaction and system parameter thresholds are set, and the system automatically sends out an alarm signal when the threshold is exceeded, and records detailed logs of abnormal transactions and system status;

[0099] S6. Supports users to share and synchronize points between multiple platforms and merchants. Points synchronization is based on cross-chain protocols. Users’ points operations on one platform can be synchronized and used on another platform through blockchain protocols.

[0100] S7. The operation and maintenance management module automatically handles system status updates, notifies users and merchants before routine maintenance, selects low-traffic periods for maintenance through intelligent analysis of mall traffic data, and performs status updates.

[0101] In this implementation, S2 specifically includes:

[0102] S21, quantum random number R q The generation is based on the superposition state of the qubit, which is |0>+|1>. When measured, the superposition state of the qubit randomly collapses to 0 and 1, and the generated random numbers are unpredictable and non-repeatable.

[0103] S22. When the user's transaction behavior reaches the predetermined conditions, the system triggers the quantum random number R q The generation of the conditions includes that the user's transaction amount and transaction frequency exceed the set threshold T u When the user's transaction behavior does not reach the threshold, the system uses a pseudo-random number R p Distribute points to optimize system resources;

[0104] S23, quantum random number R q The generation frequency depends on the user's activity A u Dynamic adjustment: the higher the user's activity, the faster the frequency of quantum random number generation. The system automatically increases the usage ratio of quantum random numbers based on the user's activity.

[0105] S24. The system chooses to use quantum random number R according to different transaction scenarios. q and the pseudo-random number R p Points are distributed, with quantum random numbers used for high-priority scenarios, including large-value transactions and continuous high-frequency transactions, and pseudo-random numbers used for low-priority scenarios;

[0106] S25, quantum random number R q Combined with the user's transaction history data H u and behavioral data B u Perform weighted calculation to determine the number of points P that the user should receive u :

[0107] Pu = α·Hu + β·Bu + γ·Rq;

[0108] Among them, the weighting coefficients α, β, and γ are dynamically adjusted according to the user's behavior and transaction pattern;

[0109] S26, dynamic adjustment of weighting coefficients α, β and γ based on user activity A u And the integral frequency F u :

[0110] α=α0+k1·Au;

[0111] β=β0+k2·Fu;

[0112] γ=γ0+k3·Rq;

[0113] Among them, α0, β0, γ0 are initial weighting coefficients, and k1, k2, k3 are adjustment coefficients.

[0114] In this implementation, S3 specifically includes:

[0115] S31, real-time collection of market data through five variables: user's exchange request, commodity inventory, transaction frequency, points circulation speed and user behavior data, the variables include the user's exchange request quantity R u 、The current inventory level of the product I s 、User's transaction frequency F u , the velocity of the integral in the system V p And the user's behavior data B u , data is transmitted synchronously through distributed nodes, so that each node receives the latest market data;

[0116] S32, the distributed nodes use encryption algorithms to encrypt and transmit market data, and the data synchronization between the nodes includes real-time processing and parsing of the collected variable data, and the data parsed by each node is fed back to other nodes in the system, so that all nodes have the same market data status;

[0117] S33. The system calculates the redemption value V of the points based on the collected market variables. e To make dynamic adjustments:

[0118]

[0119] Among them, V e is the exchange value of the integral, δ, η, ζ, θ are the coefficients regulating the influence of each variable;

[0120] S34. Through the distributed multi-dimensional market value control algorithm, the system adjusts the points redemption conditions according to real-time market supply and demand data and the speed of points circulation:

[0121]

[0122] Among them, P u Points redemption conditions, S u is the difference between supply and demand of the commodity, T u is the adjustment parameter used to control fluctuations in the difference between supply and demand;

[0123] S35. The system uses blockchain technology to process and store data through distributed nodes. Smart contracts automatically execute the adjustment steps of the points redemption value to prevent excessive fluctuations in the points redemption value.

[0124] In this implementation manner, the S4 specifically includes:

[0125] S41. Based on the points transaction records and market control results, the system executes the points redemption process. The system automatically calculates the number of points required by the user according to the redemption request and determines the real-time redemption value according to the market control results. The redemption process needs to be completed within the set predetermined time T e Timeout will trigger the subsequent processing mechanism;

[0126] S42, the system sets a time limit T for the points redemption process e If the redemption operation is not completed within the time limit, the system will calculate the compensation points according to the timeout degree ΔT. The compensation points C p Consider the timeout period and the user's transaction frequency F u And historical transaction data H u Perform weighted calculation:

[0127]

[0128] Among them, κ is the basic compensation coefficient, μ is the control coefficient, and α is the nonlinear adjustment coefficient;

[0129] S43, the system is based on the timeout time ΔT and the time limit T e Dynamically adjust the compensation rules, compensation amount C d Related to the time ratio, integrated with the market transaction load L m And the user's points balance B u :

[0130]

[0131] Among them, B0 is the set integral base value, γ is the adjustment coefficient, which reflects the impact of the integral balance on compensation, and β is the weighted adjustment coefficient of compensation;

[0132] S44. The triggering condition for compensation processing includes that the points redemption request is not received within the scheduled time T e The network interruption exceeds the set time threshold T n , the system performs compensation processing based on these conditions;

[0133] S45. The system automatically executes the deduction and compensation of compensation points, and the processing results are updated to the points transaction record and synchronized to the distributed nodes of the blockchain.

[0134] In this implementation manner, S5 specifically includes:

[0135] S51. Through the distributed monitoring mechanism on the blockchain, the system monitors the points transaction and system status in real time. The key parameters monitored include the number of transactions, transaction frequency, points circulation speed, system load and user behavior data, which are collected and synchronized through distributed nodes;

[0136] S52, the system based on historical transaction data H t and user behavior data B u Dynamically set the threshold of monitoring parameters. The threshold calculation formula is combined with the transaction volatility σ t and user activity A u :

[0137]

[0138] Among them, T th is the transaction upper limit threshold, λ is the basic control coefficient, A0 is the baseline value of user activity, δ is the activity control index, and N is the total number of transactions;

[0139] S53. When the monitored parameters exceed the set threshold, the system automatically triggers an alarm signal. The alarm conditions include the transaction quantity T n Exceeding the set upper limit T th and system load L m Exceeding the upper load limit L th :

[0140] Et=∑(Tn-Tth), if Tn>Tth;

[0141] El=∑(Lm-Lth), if Lm>Lth;

[0142] Among them, E t and E l They are alarm signals for abnormal transactions and load respectively;

[0143] S54, the system dynamically adjusts the monitoring time interval Δt according to the monitoring results. The standard time interval is to collect data every Δt seconds. If the system load L m If the upper limit is exceeded, the monitoring frequency is accelerated to every Δt / 2 seconds. This time interval is adaptively adjusted according to the changes in system load to match the monitoring frequency with the system status;

[0144] S55. After the alarm signal is triggered, the system automatically generates an abnormal log to record abnormal transactions. t and abnormal system load E l The exception logs are synchronized through distributed nodes of the blockchain so that all nodes can obtain the latest exception records.

[0145] In this implementation manner, S6 specifically includes:

[0146] S61. Users share and generate points synchronously between multiple platforms and merchants. Points data is synchronized between platforms through cross-chain protocols. The transaction frequency and points operation rules of different platforms affect the configuration of synchronization operations.

[0147] S62. Points synchronization is performed through smart contracts, and points operations are recorded and synchronized through blockchain protocols:

[0148]

[0149] Among them, S p The number of points generated for the target platform, S u is the number of points operations performed by the user on the source platform, ΔP i is the weight increment of the target platform, P t is the sum of the weights of each platform;

[0150] S63, the points data is transmitted between distributed nodes, and the nodes use a multi-signature and hash verification mechanism. After the transmission is completed, the points data is recorded on the blockchain;

[0151] S64. The consensus algorithm plays a role in the synchronization of points data on each platform. The successful synchronization of points needs to be confirmed by at least N consensus nodes;

[0152] S65. The merchant type and platform agreement type determine the rules for points sharing. The rules include the scope of application of the points type and the operating permissions between platforms. Merchants can adjust the points sharing strategy according to specific needs.

[0153] In this implementation manner, the S7 specifically includes:

[0154] S71, the operation and maintenance management module automatically processes the status update of the mall system. The system selects low-traffic periods for maintenance operations by analyzing the mall's traffic data;

[0155] S72. The system uses time series algorithm to analyze the historical traffic of the mall. f and real-time traffic R f , and select the low flow period T based on the predicted flow change l Perform maintenance operations;

[0156] S73. The system performs status update operations based on the analysis results of the low-traffic period. The update content includes database backup, cache cleaning, and server performance optimization to ensure the stable operation of the mall system.

[0157] S74, the frequency of system status update is adjusted according to the mall traffic data, and the update frequency is U fAccording to the average flow F avg and flow peak F peak To make dynamic adjustments:

[0158]

[0159] Among them, U f is the update frequency, U0 is the basic update frequency;

[0160] S75. The system notifies users and merchants in advance before executing the status update. The notification time is determined based on the expected maintenance duration and traffic change trend. The log of the maintenance operation is recorded through distributed nodes and synchronized to the blockchain.

[0161] In this embodiment, the following modules are included:

[0162] Blockchain points management module: records the issuance, use and redemption of points through blockchain, stores the issuance and consumption records of points on different nodes, distributes the data processing load and optimizes the transaction processing speed;

[0163] Quantum random points issuance module: uses quantum random number algorithm to generate unpredictable points, issues points through smart contracts, and achieves fairness and randomness in points issuance based on user transaction history, behavior data and quantum random number weighted calculation, avoiding repetitive and patterned points issuance;

[0164] Distributed multi-dimensional market value regulation module: dynamically adjusts the points redemption value based on multiple variables such as user redemption requests, commodity inventory, transaction frequency, and points circulation speed. Combined with the data synchronization function of distributed nodes, it balances the points redemption conditions in real time according to changes in market supply and demand;

[0165] Two-way compensation processing module: In the points redemption process, the system sets a time limit. If the redemption is not completed within the scheduled time, the two-way compensation mechanism will be triggered, the compensation points will be calculated, and the deduction and compensation of points will be automatically executed through smart contracts;

[0166] Distributed monitoring and alarm module: Through the distributed monitoring mechanism on the blockchain, real-time monitoring of points transactions and system status is carried out, transaction and system parameter thresholds are set, and alarm signals are automatically issued when the thresholds are exceeded, and logs of abnormal transactions and system status are recorded;

[0167] Points cross-platform synchronization module: points sharing and synchronization are achieved through cross-chain protocols. Users’ points operations on one platform can be synchronized to other platforms through blockchain protocols, and the synchronization rules of points on each platform can be dynamically adjusted;

[0168] Intelligent operation and maintenance management module: automatically processes mall system status updates, intelligently analyzes mall traffic data, selects low-traffic periods for maintenance operations, including database backup, cache cleanup, and performance optimization, and synchronizes maintenance logs to distributed nodes through blockchain.

[0169] Embodiment 1:

[0170] In order to verify the feasibility of the present invention in implementation, the present invention is applied to a large e-commerce platform, which operates a points mall. Users can obtain points by shopping, recommending friends, etc., and use these points to redeem goods and services. The traditional points system faces multiple problems, such as opaque points transactions, complicated redemption procedures, and unstable actual value of points with market fluctuations. Since the e-commerce platform has points intercommunication needs with many cooperating merchants, how to achieve cross-platform points sharing and synchronization is also a problem to be solved. More importantly, the operation and maintenance of the mall is usually carried out during peak traffic periods, which leads to a damaged user experience.

[0171] The present invention solves these problems by introducing a blockchain-based points mall operation and maintenance management method. Assuming that during the annual promotion period of the e-commerce platform, the daily user traffic of the platform reaches three times the usual level, and points transactions are frequent, the system faces higher pressure and a larger transaction volume. The blockchain points management module of the present invention records the issuance, use and redemption of each point, ensuring the transparency of all transaction information. Due to the tamper-proof nature of the blockchain, users can clearly trace back to each use record of their points, solving the problem of users' distrust of the issuance and use of points in the traditional points system.

[0172] A user bought a smartphone worth 1,000 yuan on the platform. The user received 100 points according to the shopping rules. The system automatically generated points for the user through a quantum random number algorithm, avoiding the fixed pattern problem that may exist in the traditional point issuance. The user's points issuance is not only based on the purchase amount, but also combined with his historical shopping behavior data and current market conditions for weighted calculation. The system completed the issuance of points in just 5 seconds, greatly improving efficiency, and users do not need to wait for manual processing. Users can view the issuance record of these 100 points in real time through the platform. The platform displays the transaction hash value on the blockchain to ensure that the points data is transparent and secure.

[0173] During the promotion period, the demand for user points increased sharply, and many users hoped to redeem points for gift cards, electronic products and other products on the platform. In order to balance the supply and demand relationship, the system dynamically adjusted the redemption value of points through a distributed multi-dimensional market value regulation algorithm. For a gift card that originally required 100 points to redeem, due to tight inventory and increased redemption frequency during the event, the system adjusted the redemption value of the gift card to 120 points through algorithm calculation. This process is dynamic and real-time, ensuring that user redemption behavior can be consistent with market supply and demand, and preventing excessive fluctuations in the value of points. The entire redemption process is automatically carried out in the system background, and through data synchronization of distributed nodes, it is ensured that each node can update the latest market data in real time.

[0174] During the event, the operation and maintenance management module of the mall system also began to play a role. The system intelligently analyzed the mall's traffic data and predicted in advance that there would be a sharp drop in user traffic during a certain period of time. Based on this analysis result, the operation and maintenance management module chose to perform database backup and cache cleaning operations during the low-traffic period from 2 am to 4 am, ensuring the efficient operation of the system. The operation and maintenance operations are fully automated, and the entire process has almost no impact on the normal use of users. After the maintenance operation is completed, the system will synchronize the update logs through the blockchain distributed nodes to ensure the transparency and non-tamperability of the data. Compared with the previous maintenance method of manual intervention, automated operation and maintenance management improves operation and maintenance efficiency and reduces the impact of maintenance operations on user experience.

[0175] The platform and multiple partner merchants have achieved point sharing and synchronization through cross-chain protocols. For example, a user obtains 200 points on merchant platform A, and then the user wants to use these points to purchase goods on merchant platform B. Through the cross-chain protocol, the point operation of platform A is synchronized to platform B through the blockchain protocol. The user completes the point synchronization and product purchase operations on platform B in just 10 seconds. The platform also automatically adjusts the points exchange rules through smart contracts to ensure that the points conversion between different platforms complies with the platform's weight and exchange rules.

[0176] By comparing and analyzing the actual operating data of the e-commerce platform during the annual promotion period, the results show that the system of the present invention significantly improves the operation and maintenance efficiency and user satisfaction of the platform. The points issuance and redemption operations of the traditional system during the promotion period usually take 2-5 minutes to complete, and the operation and maintenance operations may cause the risk of excessive server load. The blockchain points management module and the intelligent operation and maintenance management module in the present invention shorten the time for points issuance and redemption to 5-10 seconds, reduce the overall system load by 20%, and reduce the system failure rate from the previous 5% to less than 1%. In addition, the operation and maintenance operations are completed during low traffic periods to avoid affecting peak users. The maintenance process is automated, reducing the error rate of manual intervention.

[0177] Table 1 Related data table

[0178]

[0179] It can be seen from the table data that, according to the summary of the table data, the system of the present invention significantly shortens the time for issuing and redeeming points compared to the traditional points system, from 180 seconds and 300 seconds to 5 seconds and 10 seconds respectively. In addition, the traditional system has a greater impact on users during high-traffic periods, while the present invention automatically performs operation and maintenance during low-traffic periods, with minimal impact, reducing system load pressure by 20%, and the failure rate from 5% to less than 1%. User satisfaction has been significantly improved from 70 points to 90 points, and the overall system operating efficiency and user experience have been significantly improved.

[0180] In summary, the present invention successfully solves the problems of opaque points transactions, unstable redemption conditions, complex cross-platform points usage, and low system operation and maintenance efficiency in the big promotion scenario of the e-commerce platform. Through blockchain technology, quantum random number algorithm, cross-chain protocol and intelligent operation and maintenance management module, it greatly improves the platform's operating efficiency and user experience, and has broad practical application value.

[0181] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A blockchain-based points mall operation and maintenance management method, characterized in that: The steps include: S1. Use blockchain technology to record the issuance, use and redemption of points. Point transaction information is stored on the blockchain. A segmented point recording method is adopted to store the points issuance, redemption and consumption records on different nodes to distribute the points data load and optimize the transaction processing speed. S2. Use quantum random points issuance algorithm to generate unpredictable random numbers based on quantum bits, control the number of points obtained by users after completing specified operations, and automatically execute points issuance through smart contracts. The number of points is determined based on the weighted calculation of user transaction history, behavior data and quantum random numbers, so that each point issuance is independent, avoiding repetitive and patterned point issuance; S3. Through the distributed multi-dimensional market value control algorithm, the redemption value of points is dynamically adjusted based on multiple variables such as user redemption requests, commodity inventory, transaction frequency, and point circulation speed. Combined with the data synchronization function of distributed nodes, the redemption conditions of points are balanced in real time according to changes in market supply and demand to prevent fluctuations in redemption value. S4. Based on the generated points transaction records and market regulation results, the system automatically executes the points redemption process through smart contracts and sets a time limit for the redemption process. Points redemption that is not completed within the scheduled time will trigger a two-way compensation process based on smart contracts. The process calculates corresponding compensation for both parties based on the degree of timeout, and automatically deducts and compensates points through the contract; S5. Through the distributed monitoring mechanism on the blockchain, real-time monitoring of points transactions and system status is carried out, transaction and system parameter thresholds are set, and the system automatically sends out an alarm signal when the threshold is exceeded, and records detailed logs of abnormal transactions and system status; S6. Supports users to share and synchronize points between multiple platforms and merchants. Points synchronization is based on cross-chain protocols. Users’ points operations on one platform can be synchronized and used on another platform through blockchain protocols. S7. The operation and maintenance management module automatically handles system status updates, notifies users and merchants before routine maintenance, selects low-traffic periods for maintenance through intelligent analysis of mall traffic data, and performs status updates.

2. According to a blockchain-based points mall operation and maintenance management method according to claim 1, it is characterized in that: The S2 specifically includes: S21, quantum random number R q The generation is based on the superposition state of the qubit, which is |0>+|1>. When measured, the superposition state of the qubit randomly collapses to 0 and 1, and the generated random numbers are unpredictable and non-repeatable. S22. When the user's transaction behavior reaches the predetermined conditions, the system triggers the quantum random number R q The generation of the conditions includes that the user's transaction amount and transaction frequency exceed the set threshold T u When the user's transaction behavior does not reach the threshold, the system uses a pseudo-random number R p Distribute points to optimize system resources; S23, quantum random number R q The generation frequency depends on the user's activity A u Dynamic adjustment: the higher the user's activity, the faster the frequency of quantum random number generation. The system automatically increases the usage ratio of quantum random numbers based on the user's activity. S24. The system chooses to use quantum random number R according to different transaction scenarios. q and the pseudo-random number R p Points are distributed, with quantum random numbers used for high-priority scenarios, including large-value transactions and continuous high-frequency transactions, and pseudo-random numbers used for low-priority scenarios; S25, quantum random number R q Combined with the user's transaction history data H u and behavioral data B u Perform weighted calculation to determine the number of points P that the user should receive u : Pu = α·Hu + β·Bu + γ·Rq; Among them, the weighting coefficients α, β and γ are dynamically adjusted according to the user's behavior and transaction pattern; S26, dynamic adjustment of weighting coefficients α, β and γ based on user activity A u And the integral frequency F u : α=α0+k1·Au; β=β0+k2·Fu; γ=γ0+k3·Rq; Among them, α0, β0, γ0 are initial weighting coefficients, and k1, k2, k3 are adjustment coefficients.

3. According to a blockchain-based points mall operation and maintenance management method according to claim 1, it is characterized in that: The S3 specifically includes: S31, real-time collection of market data through five variables: user's exchange request, commodity inventory, transaction frequency, points circulation speed and user behavior data, the variables include the user's exchange request quantity R u 、The current inventory level of the product I s 、User's transaction frequency F u , the velocity of the integral in the system V p And the user's behavior data B u , data is transmitted synchronously through distributed nodes, so that each node receives the latest market data; S32, the distributed nodes use encryption algorithms to encrypt and transmit market data, and the data synchronization between the nodes includes real-time processing and parsing of the collected variable data, and the data parsed by each node is fed back to other nodes in the system, so that all nodes have the same market data status; S33. The system calculates the redemption value V of the points based on the collected market variables. e To make dynamic adjustments: Among them, V e is the exchange value of the integral, δ, η, ζ, θ are the coefficients regulating the influence of each variable; S34. Through the distributed multi-dimensional market value control algorithm, the system adjusts the points redemption conditions according to real-time market supply and demand data and the speed of points circulation: Among them, P u Points redemption conditions, S u is the difference between supply and demand of the commodity, T u is the adjustment parameter used to control fluctuations in the difference between supply and demand; S35. The system uses blockchain technology to process and store data through distributed nodes. Smart contracts automatically execute the adjustment steps of the points redemption value to prevent excessive fluctuations in the points redemption value.

4. According to a blockchain-based points mall operation and maintenance management method according to claim 1, it is characterized in that: The S4 specifically includes: S41. Based on the points transaction records and market control results, the system executes the points redemption process. The system automatically calculates the number of points required by the user according to the redemption request and determines the real-time redemption value according to the market control results. The redemption process needs to be completed within the set predetermined time T e Timeout will trigger the subsequent processing mechanism; S42, the system sets a time limit T for the points redemption process e If the redemption operation is not completed within the time limit, the system will calculate the compensation points according to the timeout degree ΔT. The compensation points C p Consider the timeout period and the user's transaction frequency F u And historical transaction data H u Perform weighted calculation: Among them, κ is the basic compensation coefficient, μ is the control coefficient, and α is the nonlinear adjustment coefficient; S43, the system is based on the timeout time ΔT and the time limit T e Dynamically adjust the compensation rules, compensation amount C d Related to the time ratio, integrated with the market transaction load L m And the user's points balance B u : Among them, B0 is the set integral base value, γ is the adjustment coefficient, which reflects the impact of the integral balance on compensation, and β is the weighted adjustment coefficient of compensation; S44. The triggering condition for compensation processing includes that the points redemption request is not received within the scheduled time T e The network interruption exceeds the set time threshold T n , the system performs compensation processing based on these conditions; S45. The system automatically executes the deduction and compensation of compensation points, and the processing results are updated to the points transaction record and synchronized to the distributed nodes of the blockchain.

5. According to a blockchain-based points mall operation and maintenance management method according to claim 1, it is characterized in that: The S5 specifically includes: S51. Through the distributed monitoring mechanism on the blockchain, the system monitors the points transaction and system status in real time. The key parameters monitored include the number of transactions, transaction frequency, points circulation speed, system load and user behavior data, which are collected and synchronized through distributed nodes; S52, the system based on historical transaction data H t and user behavior data B u Dynamically set the threshold of monitoring parameters. The threshold calculation formula combines the transaction volatility σ t and user activity A u : Among them, T th is the transaction upper limit threshold, λ is the basic control coefficient, A0 is the baseline value of user activity, δ is the activity control index, and N is the total number of transactions; S53. When the monitored parameters exceed the set threshold, the system automatically triggers an alarm signal. The alarm conditions include the transaction quantity T n Exceeding the set upper limit T th and system load L m Exceeding the upper load limit L th : Et=∑(Tn-Tth), if Tn>Tth; El=∑(Lm-Lth), if Lm>Lth; Among them, E t and E l They are alarm signals for abnormal transactions and load respectively; S54, the system dynamically adjusts the monitoring time interval Δt according to the monitoring results. The standard time interval is to collect data every Δt seconds. If the system load L m If the upper limit is exceeded, the monitoring frequency is accelerated to every Δt / 2 seconds. This time interval is adaptively adjusted according to the changes in system load to match the monitoring frequency with the system status; S55. After the alarm signal is triggered, the system automatically generates an abnormal log to record abnormal transactions. t and abnormal system load E l The exception logs are synchronized through distributed nodes of the blockchain so that all nodes can obtain the latest exception records.

6. According to a blockchain-based points mall operation and maintenance management method according to claim 1, it is characterized in that: The S6 specifically includes: S61. Users share and generate points synchronously between multiple platforms and merchants. Points data is synchronized between platforms through cross-chain protocols. The transaction frequency and points operation rules of different platforms affect the configuration of synchronization operations. S62. Points synchronization is performed through smart contracts, and points operations are recorded and synchronized through blockchain protocols: Among them, S p The number of points generated for the target platform, S u is the number of points operations performed by the user on the source platform, ΔP i is the weight increment of the target platform, P t is the sum of the weights of each platform; S63, the points data is transmitted between distributed nodes, and the nodes use a multi-signature and hash verification mechanism. After the transmission is completed, the points data is recorded on the blockchain; S64. The consensus algorithm plays a role in the synchronization of points data on each platform. The successful synchronization of points needs to be confirmed by at least N consensus nodes; S65. The merchant type and platform agreement type determine the rules for points sharing. The rules include the scope of application of the points type and the operating permissions between platforms. Merchants can adjust the points sharing strategy according to specific needs.

7. According to a blockchain-based points mall operation and maintenance management method according to claim 1, it is characterized in that: The S7 specifically includes: S71, the operation and maintenance management module automatically processes the status update of the mall system. The system selects low-traffic periods for maintenance operations by analyzing the mall's traffic data; S72. The system uses time series algorithm to analyze the historical traffic of the mall. f and real-time traffic R f , and select the low flow period T based on the predicted flow change l Perform maintenance operations; S73. The system performs status update operations based on the analysis results of the low-traffic period. The update content includes database backup, cache cleaning, and server performance optimization to ensure the stable operation of the mall system. S74, the frequency of system status update is adjusted according to the mall traffic data, and the update frequency is U f According to the average flow F avg and flow peak F peak To make dynamic adjustments: Among them, U f is the update frequency, U0 is the basic update frequency; S75. The system notifies users and merchants in advance before executing the status update. The notification time is determined based on the expected maintenance duration and traffic change trend. The log of the maintenance operation is recorded through distributed nodes and synchronized to the blockchain.

8. A point mall operation and maintenance management system based on blockchain, characterized in that: Includes the following modules: Blockchain points management module: records the issuance, use and redemption of points through blockchain, stores the issuance and consumption records of points on different nodes, distributes the data processing load and optimizes the transaction processing speed; Quantum random points issuance module: uses quantum random number algorithm to generate unpredictable points, issues points through smart contracts, and achieves fairness and randomness in points issuance based on user transaction history, behavior data and quantum random number weighted calculation, avoiding repetitive and patterned points issuance; Distributed multi-dimensional market value regulation module: dynamically adjusts the points redemption value based on multiple variables such as user redemption requests, commodity inventory, transaction frequency, and points circulation speed. Combined with the data synchronization function of distributed nodes, it balances the points redemption conditions in real time according to changes in market supply and demand; Two-way compensation processing module: In the points redemption process, the system sets a time limit. If the redemption is not completed within the scheduled time, the two-way compensation mechanism will be triggered, the compensation points will be calculated, and the deduction and compensation of points will be automatically executed through smart contracts; Distributed monitoring and alarm module: Through the distributed monitoring mechanism on the blockchain, real-time monitoring of points transactions and system status is carried out, transaction and system parameter thresholds are set, and alarm signals are automatically issued when the thresholds are exceeded, and logs of abnormal transactions and system status are recorded; Points cross-platform synchronization module: points sharing and synchronization are achieved through cross-chain protocols. Users’ points operations on one platform can be synchronized to other platforms through blockchain protocols, and the synchronization rules of points on each platform can be dynamically adjusted; Intelligent operation and maintenance management module: automatically processes mall system status updates, intelligently analyzes mall traffic data, selects low-traffic periods for maintenance operations, including database backup, cache cleanup, and performance optimization, and synchronizes maintenance logs to distributed nodes through blockchain.

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