Data processing method and device, equipment, storage medium and program product

Abstract

The invention provides a data processing method and device, equipment, a storage medium and a program product, and relates to the technical field of block chains. The method is applied to an intelligent contract of a block chain network. The block chain network comprises at least one hierarchy, each hierarchy comprises a plurality of departments, and each department comprises a smart contract, a first synchronization node and a second synchronization node; the method comprises the following steps: processing received monitoring data according to a preset early warning mechanism to generate processing information for the monitoring data; and when the processing information is early warning information, synchronizing the early warning information to a first synchronization node and a second synchronization node, so that the first synchronization node updates a local data account book of a department by using the early warning information, and the second synchronization node updates a shared database account book of the block chain network by using the early warning information. According to the invention, the transparency and security of abnormal data monitoring of the data center can be improved.

Description

Technical Field

[0001] This application relates to the field of blockchain technology, and in particular to a data processing method, device, equipment, storage medium and program product. Background Art

[0002] In recent years, with the increase in the amount of monitoring data in each unit, the application of data centers has become more and more extensive. A data center is a facility specifically used for centralized storage, processing, and management of a large amount of data.

[0003] Currently, based on the architecture design of existing data centers, data centers focus on vertical transmission and lack horizontal information sharing. This easily leads to non-transparency in the automated reporting of various monitoring data and early warning of abnormal data, and the security and risk of being tampered with of the monitoring data itself are relatively high. Summary of the Invention

[0004] This application provides a data processing method, device, equipment, storage medium and program product, which is used to provide a technical solution that can improve the transparency and security of abnormal data monitoring in a data center.

[0005] In a first aspect, this application provides a data processing method, which is applied to a smart contract in a blockchain network; the blockchain network includes at least one level, each level includes multiple departments, and each department includes the smart contract, a first synchronization node and a second synchronization node; the method includes:

[0006] Processing the received monitoring data according to a preset early warning mechanism to generate processing information for the monitoring data;

[0007] When the processing information is early warning information, synchronize the early warning information to the first synchronization node and the second synchronization node, so that the first synchronization node uses the early warning information to update the local data ledger of the department, and the second synchronization node uses the early warning information to update the shared database ledger of the blockchain.

[0008] In a second aspect, this application provides a data processing device, which is applied to a smart contract in a blockchain network; the blockchain network includes at least one level, each level includes multiple departments, and each department includes the smart contract, a first synchronization node and a second synchronization node; the device includes: a processing module;

[0009] The processing module is used for:

[0010] Processing the received monitoring data according to a preset early warning mechanism to generate processing information for the monitoring data;

[0011] When the processed information is a warning message, synchronize the warning message to a first synchronization node and a second synchronization node, so that the first synchronization node uses the warning message to update the local data ledger of the department, and the second synchronization node uses the warning message to update the shared database ledger of the blockchain.

[0012] In a third aspect, the present application further provides a data processing device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the program is executed by the processor, it implements the method described in any one of the first aspects.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the method described in any one of the first aspects.

[0014] In a fifth aspect, the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the method described in any one of the first aspects.

[0015] The technical solution provided by the present application monitors and processes the monitoring data of the data center using a blockchain network. In the embodiments of the present application, the blockchain network includes at least one level, each level includes multiple departments, and each department includes a smart contract, a first synchronization node, and a second synchronization node. In each level, each department maintains and updates a shared database ledger, and each department owns and updates a local data ledger. The smart contract of each department is used to process the received monitoring data according to a preset warning mechanism to generate processed information for the monitoring data, and when the processed information is a warning message, synchronize the warning message to the first synchronization node and the second synchronization node, so that the first synchronization node uses the warning message to update the local data ledger of the department, and the second synchronization node uses the warning message to update the shared database ledger of the blockchain. Based on this, when the processed information of the monitoring data in each department is a warning message, write the warning message into the shared database ledger to synchronize the monitoring results through the blockchain network, which can improve the transparency of abnormal data monitoring, and based on the characteristics of the blockchain itself, the warning messages in the shared database ledger are not easily tampered with. Therefore, the security of abnormal data monitoring can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0017] Figure 1 It is a flowchart of the steps of the data processing method provided by the embodiments of the present application;

[0018] Figure 2 Schematic diagram of the smart contract provided by the embodiment of the present application;

[0019] Figure 3 Schematic structural diagram of a data processing device provided by the embodiment of the present application;

[0020] Figure 4 Schematic structural diagram of a data processing device provided by the embodiment of the present application.

[0021] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be given later. These drawings and written descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed implementation manners

[0022] Exemplary embodiments will be described in detail herein, and examples thereof are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0023] It should be noted that the data processing methods, devices, equipment, storage media, and products provided by the present application can be used in the blockchain field or any field other than the blockchain. The application fields of the data processing methods, systems, equipment, storage media, and products in the present application are not limited.

[0024] The application scenario of the present application is the monitoring of data in a data center, which is a facility specifically used for centralized storage, processing, and management of a large amount of data. However, the current non-transparent and lagging status of the automated reporting of various detection data and the early warning of abnormal data in the data center are specifically manifested as follows: it is difficult to detect unknown abnormal conditions, with a long cycle, many links, and poor transparency; the monitoring data focuses on vertical transmission, lacking horizontal information sharing, and it is easy to have disputes caused by data inconsistency; the security of the data itself and the risk of being tampered with are relatively large, etc.

[0025] Based on this, the inventive concept of the present application is: using the blockchain network to monitor and process the data in the data center, so as to use blockchain technology to achieve horizontal information sharing and improve the consistency of the monitoring data in the data center. And based on the inherent attributes of blockchain technology, prevent data from being tampered with to improve the security of the data itself.

[0026] The following uses specific embodiments to elaborate in detail on the technical solution of this application and how the technical solution of this application solves the above technical problems. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will be described below in conjunction with the accompanying drawings.

[0027] In a first aspect, an embodiment of this application provides a data processing method, which is applied to a smart contract in a blockchain network.

[0028] It should be understood that a blockchain network is a system composed of a group of interconnected nodes that jointly maintain and update the blockchain ledger. Each node usually has a complete copy of the blockchain and participates in the consensus process to verify and record new transactions.

[0029] A smart contract is a computer program that automatically executes, controls, or documents relevant rules on the blockchain.

[0030] The blockchain network in the embodiment of this application includes at least one layer, each layer includes multiple departments, and each department includes a smart contract, a first synchronization node, and a second synchronization node.

[0031] In the embodiment of this application, each layer can represent a different organizational structure; for example, when the blockchain network includes three layers, it can be divided into a top layer, a middle layer, and a bottom layer. Among them, the top layer can represent the highest management level of the organization, responsible for formulating strategies and making decisions. The middle layer can act as the organization's operation department, responsible for implementing the management's decisions and supervising daily operations. The bottom layer can represent specific execution departments, such as production, sales, or customer service. It should be understood that the above explanation of the blockchain network in the embodiment of this application is only an example and does not limit the blockchain network in the embodiment of this application.

[0032] In this embodiment, the processing rules for detecting abnormal data in the monitoring data are preset in the smart contract. The first synchronization node and the second synchronization node are used to ensure data consistency and reliability in the blockchain network, and are responsible for synchronizing data between different departments or layers to ensure the stability and security of the entire blockchain.

[0033] Based on this, the data processing method provided by the embodiment of this application can be applied to enterprises or organizational structures with multiple layers. For example, when applied to large enterprises, different departments and layers can achieve efficient collaboration and data sharing through the blockchain network, while maintaining their respective independence and security. Another example is when applied to the collaboration of multiple organizations, different organizations can interact as different layers or departments to ensure transparency and trust.

[0034] It should be understood here that the application scenarios of the embodiments of the present application described above are only examples and do not limit the application scenarios of the embodiments of the present application. The embodiments of the present application can also be applied to other suitable scenarios.

[0035] Referring to Figure 1 , the above method may include:

[0036] S101, processing the received monitoring data according to a preset warning mechanism to generate processing information for the monitoring data.

[0037] Among them, the monitoring data can be the monitoring data provided by the data center. It should be understood that in different application scenarios, the monitoring data provided by the data center is not the same.

[0038] Optionally, the above monitoring data may include environmental monitoring data, power monitoring data, network monitoring data, device monitoring data, security monitoring data, etc.

[0039] Among them, the environmental monitoring data may include temperature data, humidity data, air circulation data, etc. The power monitoring data may include power supply data, voltage and current data, etc. The network monitoring data may include data for monitoring network traffic and bandwidth usage, data for detecting network latency and packet loss, data for monitoring the connection status and health of network devices. The device monitoring data may include data for monitoring the CPU, memory, storage, and I / O usage of the device, data for monitoring the capacity and utilization rate of storage devices, data for monitoring hardware failures or abnormal behaviors of the device. The security monitoring data includes data for monitoring network and physical security, detecting potential intrusion behaviors, recording and analyzing the logs of the access control system, and regularly scanning the system to identify security vulnerabilities.

[0040] It should be noted that the above types of monitoring data are only examples and do not limit the embodiments of the present application. The monitoring data in the embodiments of the present application may also include other types of data.

[0041] Referring to Figure 2 , the preset warning mechanism in the embodiments of the present application includes multiple warning rules, and the warning rules can be set according to the abnormal range of the above monitoring data. Specifically, preset trigger conditions and corresponding preset response rules can be generated according to the abnormal range of the above monitoring data, and the smart contract can generate corresponding response rules according to the trigger conditions. If the trigger condition is condition 1, the response determined according to response condition 1 is response 1. If the trigger condition is condition 2, the response determined according to response condition 2 is response 2. That is to say, different trigger conditions result in different corresponding responses.

[0042] For example, the trigger condition is that the CPU usage rate exceeds 80%, and the corresponding response rule is to notify the system administrator to check the load, and it may be necessary to optimize or increase resources.

[0043] Another example, the trigger condition is that the network latency exceeds 200 ms. The corresponding response rule is to check the network connection and router configuration, and it may be necessary to reconfigure or upgrade the device.

[0044] Before setting the abnormal range of the monitored data, first determine the key parameters to be monitored, such as temperature data, network traffic data, CPU usage rate data, etc. Then, based on historical data, industry standards or device specifications, etc., set the normal range or abnormal range for each parameter. When setting the normal range, the range outside the normal range can be set as the abnormal range.

[0045] S102, when the processed information is a warning message, synchronize the warning message to the first synchronization node and the second synchronization node, so that the first synchronization node uses the warning message to update the local data ledger of the department, and the second synchronization node uses the warning message to update the shared database ledger of the blockchain network.

[0046] When the monitored data triggers the warning rule, the smart contract generates a warning message. The warning message may include the warning object and the abnormal data corresponding to the warning object. The warning object can be the object involved in the warning, such as a server, CPU, etc. The abnormal data corresponding to the warning object may include information such as the abnormal data range and the timestamp when the abnormal data occurred.

[0047] The first synchronization node is used to synchronize the warning message to the local data ledger of the department. Specifically, it can include: updating the local database or log file based on the warning message to record the warning message, and can also notify the relevant systems or personnel within the department according to the warning message so that they can take appropriate actions.

[0048] The second synchronization node is used to synchronize the warning message to the shared database ledger of the blockchain network. This process ensures that all participants in the blockchain network can access the latest warning message.

[0049] Based on the above description, the embodiments of the present application can use a blockchain network to monitor and process information of a data center. In the embodiments of the present application, the blockchain network includes at least one layer, each layer includes multiple departments, and each department includes a smart contract, a first synchronization node, and a second synchronization node. In each layer, each department maintains and updates a shared database ledger, and each department has and updates a local data ledger. The smart contract of each department is used to process the received monitoring data according to a preset warning mechanism to generate processing information for the monitoring data, and when the processing information is warning information, synchronize the warning information to the first synchronization node and the second synchronization node, so that the first synchronization node uses the warning information to update the local data ledger of the department, and the second synchronization node uses the warning information to update the shared database ledger of the blockchain. Based on this, when the processing information for the monitoring data in each department is warning information, write the warning information into the shared database ledger to synchronize the monitoring results through the blockchain network, which can improve the transparency of abnormal data monitoring, and based on the characteristics of the blockchain itself, the warning information in the shared database ledger is not easily tampered with. Therefore, the security of abnormal data monitoring can be improved.

[0050] In some examples, the preset warning mechanism includes warning rules generated according to the normal index range and / or abnormal index range corresponding to each data and log monitored by the data monitoring center of the department.

[0051] In the embodiments of the present application, the warning mechanism is used to monitor the monitoring data and logs so as to trigger an alarm when abnormal data is detected.

[0052] The normal index range corresponding to each data and log monitored by the monitoring center can be defined according to historical data, industry standards, and business requirements. The abnormal index range is the index value that exceeds the normal index range and is used to indicate potential problems and abnormal situations in the monitoring data.

[0053] Optionally, the normal and abnormal index ranges corresponding to each data and log monitored by the monitoring center are used to determine specific warning rules to indicate under which conditions warning information will be generated.

[0054] For example: When the CPU usage rate exceeds 80%, a performance warning message will be generated.

[0055] Another example: When the network latency exceeds 200ms, a network performance warning message will be generated.

[0056] Based on this, the embodiments of the present application can use the smart contract in the blockchain network to automatically monitor and process the new real-time monitoring data and logs in the monitoring center. When the monitoring data or logs exceed the preset normal range, an alarm will be automatically triggered, and relevant personnel or systems can also be notified according to the warning information so as to take appropriate response measures.

[0057] In the embodiments of the present application, an early warning rule is preset in the smart contract, that is, code capable of implementing anomaly detection is stored on the blockchain. This code is written to and read from the blockchain database and is triggered by blockchain transactions. Once the rule requirements are met, an early warning will be generated to form a full-process closed-loop of the abnormal pre-alarm behavior of "data (log) collection - automatically detecting monitoring data using a preset early warning rule model - problem reporting - intelligent processing", improving the execution efficiency of the smart contract and realizing a technical solution for full-process recording of data and behavior, full-link trust, full-node witness, and all-round collaboration.

[0058] In some examples, the method further includes: the smart contract determines the priority level of the corresponding early warning rule according to the type of the monitoring data;

[0059] According to the priority levels of multiple early warning rules, at least two generated early warning messages are processed in sequence.

[0060] That is to say, the smart contract can also set priorities for multiple early warning rules according to the type of the monitoring data, so as to be able to effectively respond when multiple early warning rules are triggered simultaneously.

[0061] For example: if the monitoring data is related to the core server, the early warning rule corresponding to the monitoring data can be set to a high priority level, so that when the monitoring data of the core server shows an abnormal situation, a response can be made as soon as possible.

[0062] It should be understood that with the application of the data center, the scope or type of the data monitored by the data center may change. Based on this, the early warning mechanism in the smart contract can be updated to ensure that the smart contract can continuously and effectively monitor and respond to abnormal data.

[0063] Optionally, the above-mentioned smart contract is further configured to update the preset early warning mechanism in response to an adjustment instruction for the monitoring data of the department.

[0064] The department generates an adjustment instruction according to the latest monitoring data, business requirements or environmental changes. The adjustment instruction may include updating the threshold of the early warning rule, modifying the early warning response measure or adding new monitoring data.

[0065] The adjustment instruction is sent to the smart contract, and the smart contract updates the early warning mechanism according to the adjustment instruction. Specifically, it may include: modifying the early warning rule logic in the smart contract to reflect the new abnormal threshold or abnormal condition. Updating the early warning response measure to ensure appropriate actions are taken when an early warning is triggered. Adding or removing monitoring data to adapt to the new business requirements or environmental changes.

[0066] Based on this, the embodiments of the present application can ensure that the early warning mechanism can adapt to the changing environment and business requirements.

[0067] In some possible implementation manners, the above adjustment instruction is generated according to the newly added monitoring data of the department or the index adjustment of the existing monitoring data.

[0068] Among them, the adjustment instruction may include early warning rules, thresholds, response measures, etc. that need to be updated. It should be understood that the adjustment instruction is used to ensure that the early warning mechanism can adapt to the new monitoring data or the adjusted index, so as to improve the flexibility and response ability of the smart contract.

[0069] The above newly added monitoring data of the department may include monitoring data obtained by using newly installed sensors, monitoring data involved in new business requirements or technology upgrades.

[0070] The adjusted index may include adjusting the index of the existing monitoring data according to business requirements, environmental changes or historical data analysis. Among them, the index of the existing monitoring data includes the threshold of the existing monitoring data.

[0071] In some examples, when the adjustment instruction is generated according to the newly added monitoring data of the department, the update of the preset early warning mechanism by the smart contract includes:

[0072] Generating a new early warning rule according to the newly added monitoring data;

[0073] Among them, the newly added monitoring data may come from monitoring data obtained by newly installed sensors, new business requirements or other data sources; the new early warning rule should clearly define the threshold of the newly added monitoring data and the corresponding response measures. And it should be ensured that the format and logic of the new early warning rule are consistent with the existing early warning rules for easy integration.

[0074] Adding the new early warning rule to the preset early warning mechanism to update the preset early warning mechanism.

[0075] Optionally, the code of the smart contract can be modified to include the new early warning rule.

[0076] Based on this, the present application can add new early warning rules according to the actual operation situation to improve the adaptability and flexibility of the smart contract.

[0077] In other examples, when the adjustment instruction is generated according to the index adjustment of the existing monitoring data, the update of the preset early warning mechanism by the smart contract includes:

[0078] Determining the new index range in the corresponding existing early warning rule according to the index adjustment of the existing monitoring data;

[0079] In this example, the adjustment instructions can be generated according to changes in business requirements, changes in environmental conditions, or the results of historical data analysis. According to the adjustment instructions, it is determined which warning rules in the existing warning mechanism need to be adjusted, and then the new index range of the warning rule is determined, which may specifically include: recalculating thresholds or conditions to adapt to changes in business requirements or environmental conditions.

[0080] According to the new index range, the existing index range in the existing warning rule is updated to update the preset warning mechanism.

[0081] Based on this, in this embodiment, the index range in the existing warning rule is dynamically adjusted, so that the smart contract can quickly adapt to changes, improve the accuracy of monitoring and the response speed of warnings.

[0082] In the embodiment of the present application, the shared database ledger of the blockchain network includes a first shared database ledger in the level where the department is located, and a second shared database ledger in the target level;

[0083] Among them, the target level is higher than the level where the department is located.

[0084] Based on this, the second synchronization node can be used to synchronize the data of the first shared database ledger at the same level, and can also synchronize the data of the second shared database ledger at a higher level to achieve the synchronization of warning information at each level.

[0085] Based on the above description, the embodiment of the present application utilizes the sharding mechanism of the blockchain network to establish a department-level-blockchain automated data synchronization network, collects monitoring data using the data centers of each department at the level, and uses smart contracts to monitor and give real-time warnings to the monitoring data.

[0086] The embodiment of the present application uses the second synchronization node as the data exchange node for each level of data to form a real-time automated data exchange mechanism. The second synchronization node is used to realize the synchronization of warning information between departments on the monitoring chain of the upper level; the warning information between each upper level is synchronized on the monitoring chain of a higher level. The specific measures are as follows:

[0087] The second synchronization node is used to realize the real-time synchronization of hierarchical monitoring data, and a warning mechanism is established through the smart contract of the blockchain network; the automatic warning function of the monitoring data of the current data center is integrated into the monitoring chains of each hierarchical department.

[0088] Based on this, the embodiment of the present application constructs a hierarchical blockchain monitoring chain to realize the automated synchronization ability of cross-departmental abnormal monitoring data, and realizes cross-departmental and hierarchical data exchange through the second synchronization node in the hierarchical monitoring chain.

[0089] Data synchronization is achieved through the data synchronization ability of the first synchronization node within the department; the hierarchical monitoring chain can achieve a certain early warning ability through smart contracts, and can capture abnormal situations in a certain department at the budding stage of abnormal situations.

[0090] Based on the traceable characteristics of the data in the blockchain network, the embodiments of this application form a complete tamper-proof data chain to ensure the traceability and security of the data.

[0091] Based on the blockchain and smart contracts, the embodiments of this application enable the process of abnormal data detection to achieve trusted collaboration between different departments, reduce the interference of human factors and uncontrollable factors, and are fully automated and irreversible, thereby saving time, reducing costs, and improving the efficiency and accuracy of monitoring. And the use of smart contracts eliminates any third-party interference and further enhances the degree of decentralization.

[0092] Second, referring to Figure 3 This application also provides a data processing device, which is applied to the smart contract of the blockchain; the blockchain network includes at least one level, each level includes multiple departments, and each department includes the smart contract, the first synchronization node, and the second synchronization node; the device includes: a processing module;

[0093] The processing module 301 is used for:

[0094] Processing the received monitoring data according to a preset early warning mechanism to generate processing information for the monitoring data;

[0095] When the processing information is early warning information, synchronize the early warning information to the first synchronization node and the second synchronization node, so that the first synchronization node uses the early warning information to update the local data ledger of the department, and the second synchronization node uses the early warning information to update the shared database ledger of the blockchain network.

[0096] Optionally, the processing module 301 is further used for:

[0097] Updating the preset early warning mechanism in response to an adjustment instruction for the monitoring data of the department.

[0098] Optionally, the adjustment instruction is generated according to the newly added monitoring data of the department or the index adjustment of the existing monitoring data.

[0099] Optionally, when the adjustment instruction is generated according to the newly added monitoring data of the department, the processing module 301 is specifically used for:

[0100] Generating a new early warning rule according to the newly added monitoring data;

[0101] Add the new warning rule to the preset warning mechanism to update the preset warning mechanism.

[0102] Optionally, when the adjustment instruction is generated according to the adjustment of the indicators of the existing monitoring data, the processing module 301 is specifically configured to:

[0103] Determine the new indicator range in the corresponding existing warning rule according to the adjustment of the indicators of the existing monitoring data;

[0104] Update the original indicator range in the existing warning rule according to the new indicator range to update the preset warning mechanism.

[0105] Optionally, the preset warning mechanism includes warning rules generated according to the normal indicator range and / or abnormal indicator range corresponding to each data and log monitored by the data monitoring center of the department.

[0106] Optionally, the processing module 301 is further configured to:

[0107] Determine the priority level corresponding to the warning rule according to the type of the monitoring data;

[0108] Process at least two generated warning messages in sequence according to the priority levels of the multiple warning rules.

[0109] Optionally, the warning message includes a warning object and abnormal data corresponding to the warning object.

[0110] Optionally, the shared database ledger of the blockchain network includes a first shared database ledger in the level where the department is located and a second shared database ledger in the target level;

[0111] Wherein, the target level is higher than the level where the department is located.

[0112] It should be understood that the beneficial effects of the data processing device are the same as those of the data processing method in the first aspect, and will not be elaborated here.

[0113] In a third aspect, the present application further provides a data processing device, Figure 4 which is a schematic structural diagram of the data processing device provided in the embodiments of the present application. As Figure 4 shown, the data processing device may include: a transceiver 121, a processor 122, and a memory 123.

[0114] The processor 122 executes the computer-executable instructions stored in the memory, enabling the processor 122 to execute the solutions in the above-described embodiments of the data processing method. The processor 122 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0115] The memory 123 is connected to the processor 122 via the system bus and completes the communication therebetween. The memory 123 is used to store computer program instructions.

[0116] The transceiver 121 can be used to obtain the task to be run and the configuration information of the task to be run.

[0117] The system bus can be a peripheral component interconnect (PCI) bus, an extended industry standard architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus. The transceiver is used to implement the communication between the database access device and other computers (such as clients, read-write libraries, and read-only libraries). The memory may include a random access memory (RAM), and may also include a non-volatile memory.

[0118] The embodiment of the present application further provides a chip for running instructions, and the chip is used to execute the technical solution of the data processing method in the above embodiment.

[0119] The embodiment of the present application further provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are run on a computer, the computer is enabled to execute the technical solution of the data processing method in the above embodiment.

[0120] The embodiment of the present application further provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when at least one processor executes the computer program, the technical solution of the data processing method in the above embodiment can be implemented.

[0121] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of devices or modules can be in electrical, mechanical or other forms.

[0122] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to implement the solution of this embodiment.

[0123] In addition, each functional module in various embodiments of the present application can be integrated in a processing unit, or each module can exist physically alone, or two or more modules can be integrated in a unit. The unit formed by the above modules can be implemented in the form of hardware or in the form of a hardware plus software functional unit.

[0124] The integrated modules implemented in the form of software functional modules can be stored in a computer-readable storage medium. The above software functional modules are stored in a storage medium and include several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute some steps of the methods in various embodiments of the present application.

[0125] It should be understood that the above processor can be a Central Processing Unit (CPU for short), and can also be other general-purpose processors, Digital Signal Processors (DSP for short), Application Specific Integrated Circuits (ASIC for short), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly implemented by the execution of the hardware processor or can be implemented by the combination of hardware and software modules in the processor.

[0126] The memory may include high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory, and can also be a USB flash drive, a mobile hard disk, a read-only memory, a disk or an optical disc, etc.

[0127] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, the buses in the attached drawings of this application are not limited to only one bus or one type of bus.

[0128] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk or an optical disc. The storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0129] An exemplary storage medium is coupled to the processor, enabling the processor to read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic control unit or a master control device.

Claims

1. A data processing method, characterized in that: Applied to a smart contract of a blockchain network; the blockchain network includes at least one level, each level includes multiple departments, and each department includes the smart contract, a first synchronization node and a second synchronization node; The method comprises: Processing the received monitoring data according to a preset early warning mechanism to generate processing information for the monitoring data; In the case where the processed information is warning information, the warning information is synchronized to the first synchronization node and the second synchronization node, so that the first synchronization node uses the warning information to update the local data ledger of the department, and the second synchronization node uses the warning information to update the shared database ledger of the blockchain network.

2. The method according to claim 1, characterized in that The method further comprises: In response to the adjustment instruction of the monitoring data of the department, the preset early warning mechanism is updated.

3. The method according to claim 2, characterized in that The adjustment instruction is generated based on the newly added monitoring data of the department or the indicator adjustment of the existing monitoring data.

4. The method according to claim 3, characterized in that In the case where the adjustment instruction is generated according to the newly added monitoring data of the department, updating the preset early warning mechanism includes: Generate new early warning rules according to the newly added monitoring data; The new warning rule is added to the preset warning mechanism to update the preset warning mechanism.

5. The method according to claim 3, characterized in that: In the case where the adjustment instruction is generated based on the index adjustment of the existing monitoring data, updating the preset early warning mechanism includes: According to the indicator adjustment of the existing monitoring data, a new indicator range in the corresponding existing early warning rules is determined; According to the new indicator range, the original indicator range in the existing warning rule is updated to update the preset warning mechanism.

6. The method according to any one of claims 1 to 5, characterized in that: The preset early warning mechanism includes a plurality of early warning rules generated according to a normal indicator range and / or an abnormal indicator range corresponding to each data and log monitored by the data monitoring center of the department.

7. The method according to claim 6, characterized in that The method further comprises: Determining the priority of the corresponding warning rule according to the type of the monitoring data; According to the priority of the plurality of warning rules, the generated at least two warning information are processed in sequence.

8. The method according to any one of claims 1 to 5, characterized in that: The warning information includes a warning object and abnormal data corresponding to the warning object.

9. The method according to any one of claims 1 to 5, characterized in that: The shared database ledger of the blockchain network includes a first shared database ledger in the level where the department is located, and a second shared database ledger in the target level; The target level is higher than the level at which the department is located.

10. A data processing device, characterized in that: Applied to a smart contract of a blockchain; the blockchain network includes at least one level, each level includes multiple departments, each department includes the smart contract, a first synchronization node and a second synchronization node; the device includes: a processing module; The processing module is used for: Processing the received monitoring data according to a preset early warning mechanism to generate processing information for the monitoring data; In the case where the processed information is warning information, the warning information is synchronized to the first synchronization node and the second synchronization node, so that the first synchronization node uses the warning information to update the local data ledger of the department, and the second synchronization node uses the warning information to update the shared database ledger of the blockchain network.

11. A data processing device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the program implements the method according to any one of claims 1 to 9 when executed by the processor.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

13. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 9 when being executed by a processor.

Images