IDC machine room intelligent management method based on big data

Abstract

The invention relates to the technical field of machine room management, in particular to an IDC machine room intelligent management method based on big data, and the method comprises the following steps: building an association relationship among a plurality of pieces of computer equipment in an IDC machine room, and setting a temporary storage area among the plurality of pieces of computer equipment; a cloud server is configured corresponding to the computer equipment, and the cloud server comprises a sub-server area, a service processing area and a data input area; synchronizing a data processing state in a cloud server corresponding to the fault equipment to a temporary storage area to determine data processing information; the target migration device is determined according to the incidence relation, the data processing information of the corresponding fault device in the temporary storage area is migrated to the target migration device and continues to be processed, freeze-frame can be conducted on the data processing information before the device breaks down, overall migration is conducted on the data processing information of the fault device, and continuous processing is conducted; and continuity of data processing and normal operation of services are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of machine room management, in particular to an IDC machine room intelligent management method based on big data. BACKGROUND

[0002] In the IDC machine room, numerous computer devices are cooperatively running to process massive data. Device failures occur from time to time, and once a device fails, the data processing process being processed by the device will be interrupted, affecting the normal development of business. The existing management method is difficult to efficiently and accurately synchronize the data processing information processed by the target migration device to the temporary storage area when dealing with device failures, and cannot smoothly migrate the data processing information back to the recovered fault device, resulting in low data processing efficiency and prolonged business interruption time.

[0003] Therefore, we propose an IDC machine room intelligent management method based on big data to solve the above problems. SUMMARY

[0004] The purpose of the present application is to provide an IDC machine room intelligent management method based on big data to solve the problems raised in the background.

[0005] To achieve the above purpose, the present application provides the following technical scheme: an IDC machine room intelligent management method based on big data, the method comprising the following steps:

[0006] Establishing the association relationship between the plurality of computer devices in the IDC machine room, and setting a temporary storage area between the plurality of computer devices;

[0007] Corresponding computer device configuration cloud server, wherein the cloud server includes a sub-server area, a business processing area and a data input area; synchronizing the data processing state of the cloud server corresponding to the fault device to the temporary storage area to determine the data processing information;

[0008] According to the association relationship, determine the target migration device, migrate the data processing information corresponding to the fault device in the temporary storage area to the target migration device and continue processing;

[0009] Synchronize the data processing information processed in the target migration device to the temporary storage area in real time; when the fault device recovers, migrate the data processing information from the temporary storage area to the recovered fault device.

[0010] Preferably, the step of establishing the association relationship between the plurality of computer devices in the IDC machine room and setting a temporary storage area between the plurality of computer devices comprises:

[0011] The IDC machine room is configured with a temporary storage area, and a communication channel is established between the temporary storage area and each of the plurality of computer devices.

[0012] The IDC machine room is configured with a temporary storage area, and a communication channel is established between the temporary storage area and each of the plurality of computer devices.

[0013] Preferably, the step of configuring the IDC machine room with a temporary storage area and establishing a communication channel between the temporary storage area and each of the plurality of computer devices comprises:

[0014] A plurality of storage board blocks are obtained by dividing the temporary storage area according to the plurality of computer devices.

[0015] A plurality of storage board blocks are obtained by dividing the temporary storage area according to the plurality of computer devices.

[0016] Preferably, the step of synchronizing the data processing information in the cloud server corresponding to the faulty device to the temporary storage area to determine the data processing information to be migrated comprises:

[0017] The cloud server is divided into a data input area, a business processing area and a sub-server area, wherein the data input area is used to transmit the demand data of the target business to the business processing area, the business processing area is used to process the received demand data and store the processed demand data to the sub-server area, and the sub-server area is used to store the processed demand data and record in time sequence;

[0018] The processing state of the demand data in the cloud server is collected in real time in time sequence to generate a state sequence and is synchronized on the corresponding storage board block in the temporary storage area;

[0019] The demand data is processed by the computer device, and in the process of processing, if the computer device fails, the last processing state before the computer device fails, the corresponding unprocessed demand data and the demand data after processing are taken as data processing information;

[0020] The computer device with the fault and the corresponding data processing information to be migrated are determined.

[0021] Preferably, the step of transmitting the demand data of the target business to the business processing area comprises:

[0022] The demand data of the target business and the data processing sequence of the demand data are obtained, the demand data is divided into a plurality of data blocks according to the data processing sequence, and a plurality of corresponding labels are generated;

[0023] storing a plurality of tags in a data processing sequence to generate a tag cache area;

[0024] setting a guide path in the data input area, sequentially retrieving data blocks corresponding to the tags from the demand data according to the tag cache area, and inputting the data blocks to the business processing area through the guide path.

[0025] Preferably, the step of setting a guide path in the data input area, sequentially retrieving data blocks corresponding to the tags from the demand data according to the tag cache area, and inputting the data blocks to the business processing area through the guide path comprises:

[0026] uniformly setting a plurality of guide points on the guide path, each guide point storing one tag at a time;

[0027] the initial guide point is connected to the tag cache area, and the last guide point is connected to the tag recycling area;

[0028] one end of the guide path is connected to a database corresponding to the demand data, and the other end of the guide path is connected to the business processing area;

[0029] the initial guide point sequentially obtains tags from the tag cache area, and retrieves data blocks corresponding to the tags from the demand data according to the tags;

[0030] the tags sequentially move through each guide point and drive the corresponding data blocks to move synchronously;

[0031] When the tag enters the second guide point, the initial guide point obtains a second tag from the tag cache area and retrieves the corresponding data blocks for synchronous movement according to the second tag;

[0032] When the tag passes through the last guide point, the tag is stored in the tag recycling area, and the data blocks corresponding to the tag are input into the business processing area.

[0033] Preferably, the step of determining the target migration device according to the association relationship comprises:

[0034] determining whether there is another computer device having an association relationship with the faulty device in the IDC machine room;

[0035] If it is determined that there is none, the demand data is directly processed from the temporary storage area;

[0036] If it is determined that there is, a candidate migration device library is generated according to the pre-established association relationship between the computer devices, and the computer device closest to the faulty device is selected as the target migration device from the candidate migration device library.

[0037] Preferably, the step of migrating the data processing information corresponding to the faulty device in the temporary storage area to the target migration device and continuing processing comprises:

[0038] Extract data processing information from the storage module corresponding to the faulty device;

[0039] Based on the triggering conditions, the corresponding connection channel is activated to migrate the data processing information of the required data to the storage module corresponding to the target migration device;

[0040] The target migration device obtains the data processing information from the corresponding storage module through the communication channel and continues processing, and marks the faulty device and the target migration device separately.

[0041] Preferably, the step of synchronizing the processed data information in the target migration device to the temporary storage area in real time; and migrating the processed data information back from the temporary storage area to the restored faulty device when the faulty device recovers includes:

[0042] Obtain the status sequence of the processing requirements data of the target migration device and synchronize it to the storage module of the corresponding target migration device;

[0043] Monitor the operating status of faulty equipment in real time, and trigger the migration process when it returns to normal operation;

[0044] Based on the connection channel, the data processing status of the target migration device is migrated back to the storage module corresponding to the faulty device. The faulty device that has recovered can then continue to process the required data based on the data processing information in the storage module.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] During business processing, the required data is input sequentially. Data processing information is collected in real time through the storage status of the sub-server. The last record of the sub-server is used as the last processing status of the data before the equipment failure, along with the corresponding unprocessed and processed required data, as data processing information. The data processing information is frozen before the equipment failure, and the data processing information of the failed equipment is migrated as a whole according to the communication channel. When the equipment fails, other equipment can continue to process the data, ensuring the continuity of data processing and the normal operation of the business. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Fig. 1This is a schematic diagram of the method flow of the present invention;

[0049] Fig. 2 This is a system structure block diagram of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Example

[0052] Please see Figs. 1-2 This invention provides a technical solution for intelligent management of IDC data centers based on big data: an intelligent management method for IDC data centers based on big data, comprising the following steps:

[0053] S1: Establish the association between multiple computer devices in the IDC data center and set up temporary storage areas among the multiple computer devices;

[0054] The steps for establishing the association between multiple computer devices in an IDC data center and setting up temporary storage areas among these devices include: obtaining the multiple computer devices in the IDC data center and the various target services that process resource data in the computer devices; defining the computer devices serving the same target service as the association between the multiple computer devices; configuring temporary storage areas in the IDC data center; and establishing communication channels between the temporary storage areas and the multiple computer devices.

[0055] The steps for configuring a temporary storage area in an IDC data center and establishing communication channels between the temporary storage area and multiple computer devices include: obtaining multiple computer devices in the IDC data center; dividing the temporary storage area into storage modules corresponding to the multiple computing devices to obtain multiple storage modules; setting up connection channels between each pair of storage modules; setting activation trigger conditions for each connection channel; and connecting each storage module to the corresponding computer device through a communication channel.

[0056] Specifically, relationships are established between multiple computer devices serving the same target business. These relationships mean that the multiple computer devices serving the same target business belong to the same type of computer device. If a target business originates from only one computer device, it is identified that there is no other computer device of the same type. A relationship is then established between a temporary storage area and the computer device. By synchronizing the data processing information of the computer devices to the temporary storage area, real-time data backup can be achieved. When data recovery is needed, the latest data processing information can be directly retrieved from the temporary storage area. In the event of a failure, business data can be quickly recovered based on the relationships and identity information, and business data can be automatically migrated to other associated computer devices, reducing business interruptions caused by single points of failure. Communication channels are set up between the temporary storage area and multiple computer devices. Data processing information from business data read on the computer devices can be directly synchronized to the corresponding storage modules in the temporary storage area through these communication channels. A connection channel and corresponding trigger conditions are set between any two storage modules. The trigger conditions refer to whether there is a relationship between the computer devices corresponding to the two storage modules, used to determine the target migration device corresponding to the data processing information of the failed device. For each target business and computing... Each computer device and its corresponding storage module is assigned a unique identity. The identity information is then bound between the computer device and its corresponding storage module. The identity information of the target business is also bound to the identity information of the storage module serving the target business. Through this identity binding, the computer devices in the data center are centrally monitored and managed, allowing for real-time monitoring of device operation status and data synchronization. When a computer device fails, the service can be quickly migrated to other available computer devices, ensuring the continuity of cloud services. When a device failure is detected, the target migration device can be quickly located based on the correlation, and fault recovery operations can be performed, reducing fault handling time.

[0057] S2: Configure a cloud server for the corresponding computer equipment. The cloud server includes a sub-server area, a business processing area, and a data input area. Synchronize the data processing status of the cloud server corresponding to the faulty equipment to the temporary storage area to determine the data processing information.

[0058] The steps to synchronize the data processing status of the cloud server corresponding to the faulty device to the temporary storage area and determine the data processing information include:

[0059] The cloud server is divided into three areas: a data input area, a business processing area, and a sub-server area. The data input area is used to transmit the target business requirements data to the business processing area. The business processing area is used to process the received requirements data and store the processed requirements data in the sub-server area. The sub-server area is used to store the processed requirements data and record it in chronological order.

[0060] The processing status of demand data in the cloud server is collected in real time according to the time sequence, and a status sequence is generated and synchronized on the corresponding storage module in the temporary storage area.

[0061] The demand data is processed by computer equipment. If the computer equipment malfunctions during the processing, the last processing state before the malfunction, the corresponding unprocessed demand data, and the processed demand data are used as data processing information.

[0062] Identify the faulty computer equipment and the corresponding data processing information to be migrated.

[0063] It should be noted that the specific process of processing the demand data using computer equipment involves the following: The computer equipment first receives demand data from the front-end or external systems through the data input area. This data may include order data, user requests, transaction information, sensor data, etc., and then performs necessary calculations and processing based on business requirements. For example, the received order data is verified, including checking the completeness of user information, the existence of goods, and whether the purchase quantity is positive and does not exceed inventory. Based on the product information and purchase quantity in the order, the computer equipment queries the product database for the unit price of each product and calculates the total price of the order, including the total price of goods and shipping costs. Based on the product information and purchase quantity in the order, the computer equipment updates the product inventory database, reducing the inventory of the corresponding products. If the inventory of a certain product is insufficient, the order is marked as "insufficient inventory" and the user is notified. For successfully paid orders, the computer equipment generates a logistics order, including recipient information, product information, logistics company, and tracking number. Throughout the entire process, the computer equipment records the order processing status in real time, such as "received," "verifying," "calculating total price," "updating inventory," "generating logistics order," and "completed." These processing statuses are stored in the sub-server area and updated in real time. The data is recorded sequentially to form a state sequence. This state sequence records not only the final processing result but also key state changes during the processing. For example, if a computer malfunctions while processing an order, and before the malfunction, the computer had completed some order processing operations such as data verification and total price calculation, but had not yet completed updating inventory and generating logistics orders, the last processing state before the malfunction (e.g., "Total price calculation completed"), the corresponding unprocessed demand data (e.g., unupdated inventory), and the processed demand data (e.g., the calculated total price) will be synchronized to a temporary storage area as data processing information. Subsequently, a target migration device will be determined based on the correlation, and this data processing information will be migrated to the target migration device for continued processing to ensure the continuity of order processing and the normal operation of the business. This demonstrates how to ensure the continuity of data processing and the normal operation of the business even when equipment malfunctions.

[0064] Specifically, the area division here refers to the virtual spatial division of the cloud server, dividing it into a data input area, a business processing area, and a sub-server area. The data input area is used to acquire the requirement data corresponding to the target business and transmit the requirement data to the business processing area. The business processing area is used to process the requirement data of the target business through the application and transmit the processed requirement data to the sub-server area in real time. The sub-server area is used to freeze the processing progress of the requirement data and synchronize the frozen content to the corresponding storage module in the temporary storage area in a timely manner. When the computer equipment fails, the last data processing status is extracted from the status sequence on the storage module as data processing information, which is used for subsequent migration to the corresponding target migration device, thereby continuing business processing, improving the continuity of business data processing, and avoiding business interruption due to data center equipment failure.

[0065] The steps for transferring the target business requirement data to the business processing area include: obtaining the target business requirement data and the data processing order of the requirement data; dividing the requirement data into multiple data blocks according to the data processing order and generating multiple corresponding tags; storing the multiple tags according to the data processing order to generate a tag cache area; setting a guide path in the data input area; retrieving the data blocks of the corresponding tags from the requirement data in sequence according to the tag cache area; and inputting the data blocks into the business processing area via the guide path.

[0066] It should be noted that the acquisition of target business requirement data and the order of data processing of requirement data are as follows: The target business requirement data is first stored in the database of the corresponding computer device itself. The database contains a lot of raw data. Requirement data refers to the raw data used for the target business. Requirement data corresponding to the target business is extracted from the raw data and used to generate corresponding data blocks according to the business processing order. The tag corresponding to the data block is similar to a unique identifier for that data block. The corresponding data block is retrieved from the database based on the tag, and then enters the guide path in the data input area. Multiple tags extracted from the corresponding data block in the computer device itself are stored in the tag cache area of ​​the data input area.

[0067] The steps of setting a guide path in the data input area, retrieving data blocks of the corresponding tags from the required data according to the tag cache area, and inputting the data blocks into the business processing area via the guide path include:

[0068] Multiple guide points are evenly distributed along the guide path, and each guide point stores one tag at a time.

[0069] The initial guide point connects to the tag cache area, and the final guide point connects to the tag recycling area;

[0070] One end of the guidance path connects to the database corresponding to the required data, and the other end of the guidance path connects to the business processing area.

[0071] The initial guiding point retrieves tags sequentially from the tag cache and retrieves the data block corresponding to the tag from the required data based on the tag.

[0072] The labels move sequentially along each guide point, causing the corresponding data blocks to move synchronously.

[0073] When a tag enters the second guide point, the initial guide point retrieves the second tag from the tag cache and moves synchronously according to the corresponding data block based on the second tag.

[0074] After the tag passes the end guide point, the tag is stored in the tag recycling area, and the data block corresponding to the tag enters the business processing area.

[0075] It should be noted that the data input area is connected to the database corresponding to the demand data, used to obtain the original demand data for the corresponding target business. The guidance path is a virtual channel for data transmission. The tag cache is used to temporarily store tags for the data to be retrieved; the tag recycling area is used to store used tags; and the business processing area further processes and analyzes the retrieved data blocks. The guidance path is implemented using a circular linked list structure, with each guidance point acting as a linked list node, capable of storing one tag. The initial guidance point is connected to the tag cache through a data interface, and the last guidance point is connected to the tag recycling area through a data interface. One end of the guidance path is connected to the database corresponding to the demand data, and the other end is connected to the business processing area through the data transmission channel. Tags for multiple data blocks to be retrieved are stored in the tag cache in a certain order. For example, in an e-commerce system, if the purchasing behavior of a batch of users needs to be analyzed, the IDs of these users can be stored sequentially in the tag cache as tags, and the initial guidance point retrieves tags sequentially from the tag cache. After retrieving the first tag, a database query statement is generated based on that tag. For example, if the tag is user ID "12345", the generated SQL query is "SELECT * FROM orders WHERE user_id='12345'". This query is sent to the database corresponding to the required data, retrieving the data block corresponding to the tag. The retrieved tag is stored in the initial guide point, and the retrieved data block is associated with the tag. Following the order of the circular linked list, the tags move sequentially along each guide point. During this movement, the tag and data block move synchronously. When the first tag enters the second guide point, the initial guide point retrieves the second tag from the tag cache, generates a corresponding database query based on the second tag, retrieves the corresponding data block, and moves it synchronously with the second tag. When the tag passes the last guide point, it is read from the last guide point and stored in the tag recycling area through the data interface. Simultaneously, the data block corresponding to the tag is transmitted to the business processing area through the data transmission channel. A loop is started, continuously retrieving tags from the tag cache, retrieving the corresponding data blocks, and placing the tags and data blocks into the guide path for synchronous movement. After the tag passes the end guide point, the tag is stored in the tag recycling area, and the data block is transmitted to the business processing area. By setting the tag and data block to move synchronously on the guide path, the data block is transmitted in an orderly manner according to the movement of the tag, which ensures the integrity and accuracy of the data during the transmission process and avoids the problem of data loss or disorder. The number and layout of guide points on the guide path can be adjusted according to actual needs to adapt to data processing tasks of different scales and types.

[0076] Specifically, based on the business processing order of the required data, the required data is divided into multiple data blocks. A tag cache is then generated based on the data blocks. Multiple data blocks are sequentially input into the data input area according to the processing order of the required data. The input order of each data block is determined by the storage order of the tags in the tag cache. Thus, multiple data blocks are sequentially transmitted to the business processing area via a guiding path in the data input area. Each tag contains the identification information of the data block and its processing order. The storage order of the tags is consistent with the data processing order, ensuring that the data blocks retrieved based on the tags are consistent with the data required for processing in the business processing area. A guiding path is set in the data input area; this guiding path is a virtual data transfer channel based on a memory-mapped file. This system is used to locate and access data blocks corresponding to the corresponding tags in the data input area. Guide points are set on the guide path. When the initial guide point retrieves the data block corresponding to the first tag and enters the second guide point, it continues to retrieve the data block corresponding to the second tag through the initial guide point. Tags that have passed through the guide points are stored in the tag recycling area until all tags in the tag cache have entered the tag recycling area. This indicates that the data blocks corresponding to each tag have been sequentially transmitted and processed, and also indicates that the target business has completed processing the required data. Based on the processing order of the required data in the business processing area, the system can divide the required data into multiple data blocks and generate corresponding tags. By sequentially retrieving and transmitting the corresponding data blocks for multiple tags, the system guides the data blocks from the data input area to the business processing area in an orderly manner, thereby improving the efficiency and accuracy of data processing.

[0077] S3: Determine the target migration device based on the association relationship, migrate the data processing information of the corresponding faulty device in the temporary storage area to the target migration device and continue processing;

[0078] The steps for determining the target migration device based on the association relationship include:

[0079] Determine if there are other computer devices in the IDC data center that are related to the faulty device;

[0080] If it is determined that the data does not exist, the required data will be processed directly from the temporary storage area.

[0081] If it is determined that the faulty device exists, a candidate migration device library is generated based on the pre-established association relationship between computer devices, and the computer device closest to the faulty device is selected from the candidate migration device library as the target migration device.

[0082] It should be noted that if there is no candidate migration device in the candidate migration device library, the required data will be processed directly from the temporary storage area; if there is only one candidate migration device in the candidate migration device library, it will be directly used as the target migration device; if there are multiple candidate migration devices in the candidate migration device library, the computer device closest to the faulty device will be selected as the target migration device.

[0083] The steps for migrating the data processing information of the corresponding faulty device in the temporary storage area to the target migration device and continuing processing include:

[0084] Extract data processing information from the storage module corresponding to the faulty device;

[0085] Based on the triggering conditions, the corresponding connection channel is activated to migrate the data processing information of the required data to the storage module corresponding to the target migration device;

[0086] The target migration device obtains the data processing information from the corresponding storage module through the communication channel and continues processing, and marks the faulty device and the target migration device separately.

[0087] Specifically, relationships are established between computer devices serving the same target business. For example, in an IDC data center processing financial transaction data, servers X, Y, and Z jointly handle the transaction business of a certain bank. These three servers are associated, and the temporary storage area is divided into storage modules based on the number of computer devices and the business type in the data center. The computer device with the shortest transmission distance is selected. For example, if Y and Z can both be candidate migration devices for X, the one with the fastest transmission speed is the closest in terms of transmission distance and is thus selected as the target migration device. Each storage module corresponds to one computer device, and a communication channel is established between the storage module and the computer device. For example, storage modules x, y, and z are assigned to servers X, Y, and Z respectively, and communication connections are established between them. When a computer device fails, the target migration device is determined from other computer devices associated with the failed device. For example, if server X fails, server Y is selected as the target migration device. The target migration device begins processing the demand data that was originally processed by the failed device and synchronizes the generated state sequence to the storage module of the target migration device in the temporary storage area. This involves synchronizing the status sequence of financial transaction data processed by server Y to storage module Y; separately marking faulty devices and target migration devices means binding faulty devices and target migration devices together, and also marking whether the processing of the required data is currently in the faulty device or the target migration device, so as to reflect which computer device is the target migration device corresponding to the faulty device. This allows managers to monitor the operating status of the devices and the data migration in real time, improving the management efficiency of the IDC data center.

[0088] S4: The data processing information processed in the target migration device will be synchronized to the temporary storage area in real time; when the faulty device recovers, the data processing information will be migrated back from the temporary storage area to the recovered faulty device.

[0089] The data processing information processed in the target migration device is synchronized to the temporary storage area in real time. When the faulty device recovers, the steps to migrate the data processing information from the temporary storage area back to the recovered faulty device include: obtaining the status sequence of the data processing requirements of the target migration device and synchronizing it to the storage module of the corresponding target migration device; monitoring the operating status of the faulty device in real time, and triggering the migration process when it recovers to normal operation, migrating the data processing status of the target migration device back to the storage module corresponding to the faulty device according to the connection channel, and the recovered faulty device continues to process the required data according to the data processing information in the storage module.

[0090] Specifically, the operational status of faulty equipment is monitored in real time. When the faulty equipment returns to normal operation, a migration process is triggered, migrating the data processing status of the target migration equipment from the temporary storage area to the storage module corresponding to the faulty equipment. That is, the data processing status of server Y in storage module y is migrated back to storage module x, and the restored faulty equipment retrieves the data processing information from its corresponding storage module. For example, server X retrieves the data processing status previously processed by server Y from storage module x. Based on the retrieved data processing information, the faulty equipment continues to process the required data, completing the remaining data processing tasks and ensuring business continuity. Storing the data processing information in the temporary storage area avoids data loss due to equipment failure, ensuring data security and integrity. The status sequence is continuously synchronized through the communication channel to ensure the data in the temporary storage area is up-to-date. The binding relationship between the equipment and the storage module is updated during migration and migration, preventing data corruption. The "breakpoint resume" mechanism of the status sequence ensures business continuity.

[0091] During business processing, the required data is input sequentially. Data processing information is collected in real time through the storage status of the sub-server. The last record of the sub-server is used as the last processing status of the data before the equipment failure, along with the corresponding unprocessed and processed required data, as data processing information. The data processing information is frozen before the equipment failure, and the data processing information of the failed equipment is migrated as a whole according to the communication channel. When the equipment fails, other equipment can continue to process the data, ensuring the continuity of data processing and the normal operation of the business.

[0092] First, identify similar computer equipment in the data center to determine the migration targets. Then, determine the data processing information to be migrated based on the target business's requirements. Set up a cloud server for each device in the data center, with sub-servers within each cloud server. The sub-servers act as windows to capture and process the data, processing the required data sequentially. This facilitates subsequent data processing information freezing and migration. Establish connections between each cloud server and a temporary storage area, storing all data processing information in the temporary storage area. Connect the contents of the temporary storage area to other devices. After fault recovery, migrate the data processing information back to the initial device. This effectively prevents disruption to target business data processing during device failures, ensuring business continuity.

[0093] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0094] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent management of IDC (Internet Data Center) data centers based on big data, characterized in that: Includes the following steps: Establish relationships between multiple computer devices in an IDC data center and set up temporary storage areas among these devices; Configure a cloud server for the corresponding computer equipment. The cloud server includes a sub-server area, a business processing area, and a data input area. Synchronize the data processing information in the cloud server corresponding to the faulty equipment to the temporary storage area to determine the data processing information to be migrated. Based on the correlation, the target migration device is determined, and the data processing information of the corresponding faulty device in the temporary storage area is migrated to the target migration device for further processing. The data processing information processed in the target migration device will be synchronized to the temporary storage area in real time; when the faulty device recovers, the data processing information will be migrated back from the temporary storage area to the faulty device that has recovered.

2. The intelligent management method for IDC data centers based on big data according to claim 1, characterized in that: The steps of establishing the association between multiple computer devices in the IDC data center and setting up temporary storage areas among the multiple computer devices include: The system identifies multiple computer devices in an IDC data center and various target services that process resource data within those devices, defining the relationships between computer devices that serve the same target service. Configure temporary storage areas in the IDC data center and establish communication channels between the temporary storage areas and multiple computer devices.

3. The intelligent management method for IDC data centers based on big data according to claim 1, characterized in that: The steps of configuring temporary storage areas in the IDC data center and establishing communication channels between the temporary storage areas and multiple computer devices include: Obtain multiple computer devices in the IDC data center, and divide the temporary storage area into storage modules corresponding to the multiple computing devices to obtain multiple storage modules; Multiple storage modules are connected to each other through a channel. Each channel has a trigger condition for activation. Each storage module is connected to its corresponding computer device through a communication channel.

4. The intelligent management method for IDC data centers based on big data according to claim 1, characterized in that: The step of synchronizing the data processing information in the cloud server corresponding to the faulty device to the temporary storage area to determine the data processing information to be migrated includes: The cloud server is divided into three areas: a data input area, a business processing area, and a sub-server area. The data input area is used to transmit the target business requirements data to the business processing area. The business processing area is used to process the received requirements data and store the processed requirements data in the sub-server area. The sub-server area is used to store the processed requirements data and record it in chronological order. The processing status of demand data in the cloud server is collected in real time according to the time sequence, and a status sequence is generated and synchronized on the corresponding storage module in the temporary storage area. The demand data is processed by computer equipment. If the computer equipment malfunctions during the processing, the last processing state before the malfunction, the corresponding unprocessed demand data, and the processed demand data are used as data processing information. Identify the faulty computer equipment and the corresponding data processing information to be migrated.

5. The intelligent management method for IDC data centers based on big data according to claim 4, characterized in that: The step of transmitting the target service's requirement data to the service processing area includes: Obtain the target business's requirement data and the data processing order for the requirement data; divide the requirement data into multiple data blocks according to the data processing order; and generate multiple corresponding tags. Multiple tags are stored in the order of data processing to generate a tag cache area; Set a guide path in the data input area, and retrieve the data blocks of the corresponding tags from the required data in sequence according to the tag cache area, and input the data blocks into the business processing area through the guide path.

6. The intelligent management method for IDC data centers based on big data according to claim 5, characterized in that: The steps of setting a guidance path in the data input area, retrieving data blocks of the corresponding tags from the required data sequentially according to the tag cache area, and inputting the data blocks into the business processing area via the guidance path include: Multiple guide points are evenly distributed along the guide path, and each guide point stores one tag at a time. The initial guide point connects to the tag cache area, and the final guide point connects to the tag recycling area; One end of the guidance path connects to the database corresponding to the required data, and the other end of the guidance path connects to the business processing area. The initial guiding point retrieves tags sequentially from the tag cache and retrieves the data block corresponding to the tag from the required data based on the tag. The labels move sequentially along each guide point, causing the corresponding data blocks to move synchronously. When a tag enters the second guide point, the initial guide point retrieves the second tag from the tag cache and moves synchronously according to the corresponding data block based on the second tag. After the tag passes the end guide point, the tag is stored in the tag recycling area, and the data block corresponding to the tag enters the business processing area.

7. The intelligent management method for IDC data centers based on big data according to claim 1, characterized in that: The step of determining the target migration device based on the association relationship includes: Determine if there are other computer devices in the IDC data center that are related to the faulty device; If it is determined that the data does not exist, the required data will be processed directly from the temporary storage area. If it is determined that the faulty device exists, a candidate migration device library is generated based on the pre-established association relationship between computer devices, and the computer device closest to the faulty device is selected from the candidate migration device library as the target migration device.

8. The intelligent management method for IDC data centers based on big data according to claim 7, characterized in that: The step of migrating the data processing information of the corresponding faulty device in the temporary storage area to the target migration device and continuing processing includes: Extract data processing information from the storage module corresponding to the faulty device; Based on the triggering conditions, the corresponding connection channel is activated to migrate the data processing information of the required data to the storage module corresponding to the target migration device; The target migration device obtains the data processing information from the corresponding storage module through the communication channel and continues processing, and marks the faulty device and the target migration device separately.

9. The intelligent management method for IDC data centers based on big data according to claim 1, characterized in that: The data processing information, after being processed in the target migration device, will be synchronized to the temporary storage area in real time. When a faulty device recovers and resumes operation, the steps for migrating data processing information from the temporary storage area back to the recovered faulty device include: Obtain the status sequence of the processing requirements data of the target migration device and synchronize it to the storage module of the corresponding target migration device; Monitor the operating status of faulty equipment in real time, and trigger the migration process when it returns to normal operation; Based on the connection channel, the data processing status of the target migration device is migrated back to the storage module corresponding to the faulty device. The faulty device that has recovered can then continue to process the required data based on the data processing information in the storage module.

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