A cloud storage-based data storage method and system
By combining symmetric and asymmetric encryption with a load balancing algorithm, the problems of inadequate data preprocessing and unreasonable node allocation in cloud storage are solved, thereby improving the security and efficiency of data storage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- XIAN HUAQI INTERACTIVE INFORMATION TECHNOLOGY CO LTD
- Filing Date
- 2026-05-06
- Publication Date
- 2026-06-19
AI Technical Summary
Existing cloud storage-based data storage methods and systems suffer from inadequate data preprocessing and encryption mechanisms, leading to wasted storage resources and insufficient security. Furthermore, unreasonable allocation of cloud storage nodes affects data upload and access efficiency.
A dual encryption mechanism combining symmetric and asymmetric encryption is adopted to perform format verification, redundant data removal, and adaptive compression on the data. A multi-cloud storage node cluster is constructed, and a load balancing algorithm is used to allocate primary and backup storage nodes to achieve standardized data processing and load balancing.
It improves the security and efficiency of data storage, reduces redundant data usage, prevents data tampering and leakage, avoids data loss due to the failure of a single cloud service provider, and ensures data consistency and access speed.
Smart Images
Figure CN122248003A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a data storage method and system based on cloud storage, belonging to the field of data storage technology. Background Technology
[0002] With the rapid development of information technology, the amount of data generated by various terminals is growing exponentially. Cloud storage, as a new data storage model, is widely used in data storage scenarios for individuals, enterprises, and various organizations due to its advantages such as high scalability, high availability, and low cost. By storing data in remote cloud server clusters, cloud storage eliminates the dependence on hardware devices inherent in traditional local storage. Users can access data anytime, anywhere via the network, greatly improving the convenience of data storage and use. With its advantages of large storage capacity, convenient access, and low cost, it has become the mainstream method of data storage.
[0003] While existing cloud-based data storage methods and systems can meet normal usage needs, they still have many shortcomings: data preprocessing and encryption mechanisms are imperfect, resulting in excessive redundant data and inconsistent formats, leading to wasted storage resources. The reliance on single encryption methods poses risks of key leakage and data tampering, making it difficult to guarantee the security of data storage and transmission. Furthermore, unreasonable allocation of cloud storage nodes can easily lead to some nodes being overloaded while others are idle, affecting data upload and access efficiency. Therefore, this invention provides a cloud-based data storage method and system. Summary of the Invention
[0004] The technical problem this invention aims to solve is: imperfect data preprocessing and encryption mechanisms lead to wasted storage resources and difficulty in ensuring the security of data storage and transmission; and unreasonable allocation of cloud storage nodes affects the efficiency of data upload and access.
[0005] To address the aforementioned technical problems, this invention provides a data storage method based on cloud storage. The proposed technical solution includes the following steps:
[0006] S1: Data Acquisition and Preprocessing: Receive raw data sent by the terminal, perform format verification, redundant data removal and data compression on the raw data to obtain standardized processed data;
[0007] S2: Data encryption processing: A dual encryption mechanism combining symmetric and asymmetric encryption is used to encrypt standardized data, resulting in encrypted data;
[0008] S3: Cloud storage node allocation: Construct a multi-cloud storage node cluster, which includes a primary storage node and at least two backup storage nodes. Based on the type, size and access frequency of the encrypted data, a load balancing algorithm is used to allocate the corresponding primary and backup storage nodes to the encrypted data to ensure load balancing of each storage node.
[0009] S4: Data Upload and Backup: Upload the encrypted data to the assigned primary storage node and simultaneously back it up to the corresponding backup storage node. The primary storage node and the backup storage node synchronize data updates in real time to ensure data consistency.
[0010] S5: Data Access and Maintenance: Receives access requests from terminals, performs identity verification and permission checks on the access requests, and after successful verification, retrieves the decrypted target data from the corresponding storage node according to the access request and sends it back to the terminal; periodically performs integrity checks, defragmentation, and redundant backup updates on the data in the cloud storage nodes; if data corruption or loss is detected, it automatically retrieves backup data from the standby storage node for recovery.
[0011] Furthermore, in step S1, the format verification is used to verify whether the format of the original data conforms to the preset cloud storage standard, the redundant data removal is used to delete duplicate and invalid redundant information in the original data, and the data compression adopts an adaptive compression algorithm, which automatically matches the corresponding compression strategy according to the type of the original data.
[0012] Furthermore, in step S2, the symmetric encryption uses the AES-256 algorithm, the asymmetric encryption uses the RSA-2048 algorithm, and the symmetric encryption key is encrypted and transmitted and stored using the asymmetric encryption algorithm.
[0013] Furthermore, in step S3, the primary storage node and the backup storage node belong to different cloud service providers. The load balancing algorithm includes the following steps: obtaining the real-time load status of each cloud storage node; calculating the load weight of each storage node, where the load weight is negatively correlated with the real-time value of each load status parameter; determining the storage priority of the data based on the access frequency of the encrypted data, where the higher the access frequency, the higher the storage priority; allocating high-priority data to the primary storage node with the lowest load weight and low-priority data to the primary storage node with a higher load weight, ensuring that the load difference between each storage node does not exceed a preset threshold.
[0014] Furthermore, in step S5, the identity verification adopts a dual verification method of account password plus dynamic verification code, the permission verification is set in levels according to user roles, and different roles correspond to different data access ranges, and the integrity detection adopts a hash verification algorithm to periodically calculate the hash value of the data and compare it with the preset hash value. If they are inconsistent, it is determined that the data is corrupted.
[0015] A cloud storage-based data storage system for implementing the above-mentioned data storage method, the system comprising:
[0016] The data preprocessing module is used to receive raw data sent by the terminal and obtain standardized processed data;
[0017] The data encryption module is used to encrypt standardized data using a dual encryption mechanism that combines symmetric and asymmetric encryption, and output encrypted data.
[0018] The node allocation module is used to construct a multi-cloud storage node cluster, which includes a primary storage node and at least two backup storage nodes, with the primary and backup storage nodes belonging to different cloud service providers; and uses a load balancing algorithm to allocate corresponding primary and backup storage nodes to the encrypted data based on the type, size and access frequency of the encrypted data.
[0019] The data upload and backup module is used to upload encrypted data to the assigned primary storage node and simultaneously back it up to the corresponding backup storage node, so as to achieve real-time data synchronization between the primary storage node and the backup storage node.
[0020] The access maintenance module is used to receive access requests from terminals, perform identity verification and permission checks on the access requests, retrieve the target data after successful verification and send it back to the terminal; at the same time, it regularly performs integrity checks, defragmentation and redundant backup updates on the data in the cloud storage nodes to achieve automatic recovery after data corruption.
[0021] The control module is electrically connected to the data preprocessing module, data encryption module, node allocation module, data upload and backup module, and access and maintenance module, respectively, and is used to control the coordinated work of each module to ensure the orderly progress of data storage.
[0022] Furthermore, the data preprocessing module includes a format verification unit for verifying the format of the original data, a redundancy removal unit for removing redundant data from the original data, and an adaptive compression unit for compressing the original data.
[0023] Furthermore, the data encryption module includes a symmetric encryption unit, an asymmetric encryption unit, and a key management unit to encrypt standardized data.
[0024] Furthermore, the node allocation module includes a cluster construction unit, a load monitoring unit, and a node allocation unit to construct a multi-cloud storage node cluster, calculate the load weight of each node, and allocate corresponding primary storage nodes and backup storage nodes to the data based on the load weight.
[0025] Furthermore, the access maintenance module includes an identity verification unit, a permission verification unit, a data retrieval unit, and a data maintenance unit to perform identity verification and permission verification. After successful verification, the target data is retrieved and fed back to the terminal. The module also periodically performs integrity checks, defragmentation, and redundant backup updates on the data in the cloud storage nodes.
[0026] The beneficial effects of this invention are:
[0027] To improve the integrity of data preprocessing and encryption mechanisms, the raw data undergoes format verification, redundancy removal, and adaptive compression to achieve data standardization, reduce the occupation of storage resources by redundant data, improve storage efficiency, and avoid storage resource waste. A dual encryption mechanism combining symmetric and asymmetric encryption is adopted to effectively prevent data tampering and leakage, thereby enhancing the security of data storage and transmission. A multi-cloud storage node cluster is constructed, with primary and backup nodes belonging to different cloud service providers. At the same time, a load balancing algorithm is used to allocate storage nodes, which not only avoids the risk of data loss due to the failure of a single cloud service provider, but also achieves load balancing among nodes, improving the efficiency of data upload and access. Attached Figure Description
[0028] Figure 1 This is a flowchart illustrating the overall process of the cloud storage-based data storage method of the present invention.
[0029] Figure 2 This is a detailed flowchart of the data preprocessing process of the present invention.
[0030] Figure 3 This is a flowchart of the dual encryption mechanism of the present invention.
[0031] Figure 4 This is a block diagram showing the connection of the data storage system modules based on cloud storage according to the present invention. Detailed Implementation
[0032] 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. Example 1
[0033] like Figure 1 , 2 As shown in Figure 3: This embodiment provides a data storage method based on cloud storage, specifically including the following steps:
[0034] S1: Data Acquisition and Preprocessing: Receives raw data sent by terminals (such as mobile phones, computers, IoT devices, etc.). The raw data type can include various types such as text, images, and videos. Performs format verification, redundant data removal, and data compression on the raw data to obtain standardized processed data. Format verification verifies whether the format of the raw data conforms to the preset cloud storage standard. For example, text data uses UTF-8 encoding, image data uses JPG / PNG format, and video data uses MP4 format. For data with incorrect formats, a format correction prompt is sent to the terminal to remind the user to correct the data format. Redundant data removal removes duplicate and invalid redundant information from the raw data to reduce storage resource consumption. Data compression uses an adaptive compression algorithm, automatically matching the corresponding compression strategy according to the type of raw data. The adaptive compression algorithm includes the following steps: identifying the type of raw data; if the raw data is text data, the LZ77 compression algorithm is used; if the raw data is image data, the JPEG compression algorithm is used; if the raw data is video data, the H.265 compression algorithm is used. During the compression process, the compression rate is monitored in real time. If the compression rate is lower than the preset threshold, the compression parameters are automatically adjusted to ensure a balance between the size and integrity of the compressed data.
[0035] S2: Data Encryption Processing: A dual encryption mechanism combining symmetric and asymmetric encryption is employed to encrypt standardized data, resulting in encrypted data. Symmetric encryption uses the AES-256 algorithm, which boasts high encryption strength and fast processing speed, and is used for batch encryption of standardized data to generate encrypted data. Asymmetric encryption uses the RSA-2048 algorithm, which offers high security and is used to encrypt the AES-256 key. The symmetric encryption key is transmitted and stored using the asymmetric encryption algorithm. During the encryption process, the standardized data is first encrypted using the AES-256 algorithm, and then the AES key is encrypted using the RSA-2048 algorithm, ensuring dual security for both data and key.
[0036] S3: Cloud Storage Node Allocation: Construct a multi-cloud storage node cluster, including a primary storage node and at least two backup storage nodes. Storage nodes from three different cloud service providers—Alibaba Cloud, Tencent Cloud, and Huawei Cloud—are selected, with one serving as the primary storage node and two as backup storage nodes. The primary and backup storage nodes belong to different cloud service providers to avoid data loss due to a single cloud service provider failure. Based on the type, size, and access frequency of the encrypted data, a load balancing algorithm is used to allocate corresponding primary and backup storage nodes to the encrypted data, ensuring load balancing across all storage nodes. The load balancing algorithm includes the following steps: Obtain the real-time load status of each cloud storage node, including CPU utilization, memory usage, storage space utilization, and network bandwidth utilization. For example, node A has a CPU utilization of 30%, a memory usage of 40%, a storage space utilization of 50%, and a network bandwidth utilization of... The utilization rate is 25%. Node B's CPU utilization is 60%, memory utilization is 70%, storage space utilization is 65%, and network bandwidth utilization is 55%. Node C's CPU utilization is 45%, memory utilization is 55%, storage space utilization is 55%, and network bandwidth utilization is 40%. The load weight of each storage node is calculated. The load weight is negatively correlated with the real-time values of each load status parameter; the lower the load status parameter value, the lower the load weight. Node A has the lowest load weight, and Node B has the highest load weight. The storage priority of the encrypted data is determined based on its access frequency; the higher the access frequency, the higher the storage priority. High-priority data is allocated to the primary storage node with the lowest load weight, such as frequently used office documents and frequently accessed images and videos. Low-priority data is allocated to the primary storage node with a higher load weight, such as historical backup data and infrequently used files, ensuring that the load difference between each storage node does not exceed a preset threshold.
[0037] S4: Data Upload and Backup: Uploads encrypted data to the assigned primary storage node. During the upload process, the upload status, such as upload speed and network connection status, is monitored in real time. If the upload is interrupted, the breakpoint resume mechanism is automatically triggered, the interruption position is recorded, and the upload continues from the interruption position after the network is restored or the device is normalized, avoiding duplicate data uploads. At the same time, the data is backed up to the corresponding backup storage node. The primary storage node and the backup storage node synchronize data updates in real time. When the data on the primary storage node is modified or deleted, the backup storage node performs the same operation synchronously to ensure data consistency.
[0038] S5: Data Access and Maintenance: Receives access requests from terminals, performs identity verification and permission checks on the requests. Upon successful verification, it retrieves the decrypted target data from the corresponding storage node according to the access request and sends it back to the terminal. It periodically performs integrity checks, defragmentation, and redundant backup updates on the data in cloud storage nodes. If data corruption or loss is detected, it automatically retrieves backup data from the standby storage node for recovery. Identity verification uses a dual authentication method of account password plus dynamic verification code. Permission checks are tiered according to user roles, with different roles corresponding to different data access ranges. Integrity checks use a hash verification algorithm, periodically calculating the hash value of the data and comparing it with a preset hash value; if they do not match, the data is considered corrupted. Specifically, first, dual authentication is performed through the identity verification unit. After the user enters their account password, the system sends a dynamic verification code to the user's bound mobile phone or email address. After the user enters the correct dynamic verification code, identity verification is successful. Subsequently, the permission verification unit performs permission verification based on user roles. For example, administrators can access all data, while ordinary users can only access the data they themselves uploaded. After the permission verification is successful, the data retrieval unit retrieves the encrypted data from the corresponding storage node, decrypts it using the AES-256 algorithm, and sends it back to the terminal. The data in the cloud storage nodes is maintained periodically (e.g., every morning). The data maintenance unit uses a hash verification algorithm (e.g., MD5) to calculate the hash value of each data item and compares it with a preset hash value (generated and stored during data upload). If the hash values are inconsistent, the data is considered corrupted. Simultaneously, the data in the storage nodes is defragmented, merging scattered storage fragments to improve storage efficiency. Redundant backups are updated, expired backup data is deleted, and new backup data is added. If data corruption or loss is detected, the corresponding backup data is automatically retrieved from the standby storage node and restored to the primary storage node to ensure no data loss. Example 2
[0039] like Figure 4 As shown: This embodiment provides a cloud storage-based data storage system to implement the data storage method in Embodiment 1 above. The system includes a data preprocessing module, a data encryption module, a node allocation module, a data upload and backup module, an access and maintenance module, and a control module. The specific structure of each module is as follows:
[0040] The data preprocessing module, electrically connected to the control module, receives raw data sent by the terminal and performs format verification, redundant data removal, and data compression on the raw data to obtain standardized processed data. The data preprocessing module includes a format verification unit, a redundancy removal unit, and an adaptive compression unit. The format verification unit verifies whether the format of the raw data conforms to the preset cloud storage standard and sends a format correction prompt to the terminal for data that does not conform to the format. The redundancy removal unit scans the raw data and deletes duplicate and invalid redundant information. The adaptive compression unit identifies the type of raw data, automatically matches the corresponding compression algorithm, and performs data compression. Its workflow is consistent with the adaptive compression algorithm in the embodiment.
[0041] The data encryption module, electrically connected to the control module, is used to encrypt standardized data using a dual encryption mechanism combining symmetric and asymmetric encryption, and output encrypted data. The data encryption module includes a symmetric encryption unit, an asymmetric encryption unit, and a key management unit. The symmetric encryption unit uses the AES-256 algorithm to encrypt the standardized data and generate encrypted data. The asymmetric encryption unit uses the RSA-2048 algorithm to encrypt the symmetric encryption key, ensuring the security of key transmission and storage. The key management unit is used for key generation, storage, updating, and destruction, and adopts a hierarchical key management mechanism to update keys regularly (e.g., monthly) to prevent key leakage.
[0042] The node allocation module, electrically connected to the control module, is used to construct a multi-cloud storage node cluster. The cloud storage node cluster includes a primary storage node and at least two standby storage nodes, which belong to different cloud service providers. Based on the type, size, and access frequency of the encrypted data, a load balancing algorithm is used to allocate corresponding primary and standby storage nodes to the encrypted data. The node allocation module includes a cluster construction unit, a load monitoring unit, and a node allocation unit. The cluster construction unit is used to construct the multi-cloud storage node cluster and associate storage nodes from different cloud service providers. The load monitoring unit is used to monitor the CPU utilization, memory usage, storage space utilization, and network bandwidth utilization of each storage node in real time and calculate the load weight of each node. The node allocation unit is used to determine storage priority based on the data access frequency and, combined with the load weight, allocate corresponding primary and standby storage nodes to the data. Its workflow is consistent with the load balancing algorithm in the embodiment.
[0043] The data upload and backup module is electrically connected to the control module. It is used to upload encrypted data to the assigned primary storage node and simultaneously back it up to the corresponding backup storage node, realizing real-time data synchronization between the primary and backup storage nodes. During the upload process, it monitors the upload status and triggers the breakpoint resume mechanism to ensure the continuity of data upload.
[0044] The access maintenance module, electrically connected to the control module, receives access requests from terminals, performs identity verification and permission checks on the requests, retrieves the target data after successful verification, and sends it back to the terminal. Simultaneously, it periodically performs integrity checks, defragmentation, and redundant backup updates on the data in the cloud storage nodes to achieve automatic recovery in case of data corruption. The access maintenance module includes an identity verification unit, a permission verification unit, a data retrieval unit, and a data maintenance unit. The identity verification unit verifies the terminal's access requests (using a dual verification method of account password plus dynamic verification code). The permission verification unit sets hierarchical settings according to user roles, with different roles corresponding to different data access ranges. The data retrieval unit retrieves the decrypted target data from the corresponding storage node after successful verification and sends it back to the terminal. The data maintenance unit periodically performs data integrity checks, defragmentation, and redundant backup updates to achieve automatic data recovery.
[0045] The control module is electrically connected to the data preprocessing module, data encryption module, node allocation module, data upload and backup module, and access and maintenance module, respectively. It uses a microcontroller or PLC controller to control the coordinated work of each module, receive feedback on the working status of each module, and adjust the working parameters of each module in a timely manner to ensure the orderly progress of the data storage process.
[0046] In summary, compared with the prior art, the present invention has the following advantages:
[0047] Through data acquisition and preprocessing steps, the raw data undergoes format verification, redundancy removal, and adaptive compression. This not only standardizes the data and reduces the storage resource consumption of redundant data, but also automatically matches compression algorithms according to data type. Under the premise of ensuring data integrity, it minimizes data volume and improves storage efficiency.
[0048] It adopts a dual encryption mechanism that combines symmetric and asymmetric encryption. Symmetric encryption ensures the efficiency of data encryption and decryption, while asymmetric encryption ensures the secure transmission and storage of keys, effectively preventing data from being tampered with or leaked, and improving the security of data storage and transmission.
[0049] A multi-cloud storage node cluster is constructed, with primary and backup nodes belonging to different cloud service providers. At the same time, a load balancing algorithm is used to allocate storage nodes, which not only avoids the risk of data loss due to the failure of a single cloud service provider, but also achieves load balancing among nodes, improving the efficiency of data upload and access.
[0050] During the data upload process, the primary and backup nodes are synchronized and updated in real time to ensure data consistency. At the same time, dual authentication and hierarchical permission verification ensure data access security. Regular data maintenance and automatic recovery mechanisms further improve the reliability of data storage.
[0051] The system's modules have clear division of labor and work collaboratively, with a reasonable structure. It can quickly realize full-process data storage management, adapt to the data storage needs of various terminals, is highly practical, and is easy to promote and apply.
[0052] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.
Claims
1. A data storage method based on cloud storage, characterized in that: Includes the following steps: S1: Data Acquisition and Preprocessing: Receive raw data sent by the terminal, perform format verification, redundant data removal and data compression on the raw data to obtain standardized processed data; S2: Data encryption processing: A dual encryption mechanism combining symmetric and asymmetric encryption is used to encrypt standardized data, resulting in encrypted data; S3: Cloud storage node allocation: Construct a multi-cloud storage node cluster, which includes a primary storage node and at least two backup storage nodes. Based on the type, size and access frequency of the encrypted data, a load balancing algorithm is used to allocate the corresponding primary and backup storage nodes to the encrypted data to ensure load balancing of each storage node. S4: Data Upload and Backup: Upload the encrypted data to the assigned primary storage node and simultaneously back it up to the corresponding backup storage node. The primary storage node and the backup storage node synchronize data updates in real time to ensure data consistency. S5: Data Access and Maintenance: Receives access requests from terminals, performs identity verification and permission checks on the access requests, and after successful verification, retrieves the decrypted target data from the corresponding storage node according to the access request and sends it back to the terminal; periodically performs integrity checks, defragmentation, and redundant backup updates on the data in the cloud storage nodes; if data corruption or loss is detected, it automatically retrieves backup data from the standby storage node for recovery.
2. The data storage method based on cloud storage according to claim 1, characterized in that: In step S1, the format verification is used to verify whether the format of the original data conforms to the preset cloud storage standard, the redundant data removal is used to delete duplicate and invalid redundant information in the original data, and the data compression adopts an adaptive compression algorithm, which automatically matches the corresponding compression strategy according to the type of the original data.
3. The data storage method based on cloud storage according to claim 1, characterized in that: In step S2, the symmetric encryption uses the AES-256 algorithm, the asymmetric encryption uses the RSA-2048 algorithm, and the symmetric encryption key is encrypted and transmitted and stored using the asymmetric encryption algorithm.
4. The data storage method based on cloud storage according to claim 1, characterized in that: In step S3, the primary storage node and the backup storage node belong to different cloud service providers, and the load balancing algorithm includes the following steps: Obtain the real-time load status of each cloud storage node; Calculate the load weight of each storage node. The load weight is negatively correlated with the real-time values of each load status parameter. The storage priority of the encrypted data is determined by the frequency of access to the encrypted data; the higher the access frequency, the higher the storage priority. High-priority data is assigned to the primary storage node with the lowest load weight, while low-priority data is assigned to the primary storage node with a higher load weight, ensuring that the load difference between the storage nodes does not exceed a preset threshold.
5. The data storage method based on cloud storage according to claim 1, characterized in that: In step S5, the identity verification adopts a dual verification method of account password plus dynamic verification code. The permission verification is set in levels according to user roles, with different roles corresponding to different data access ranges. The integrity detection adopts a hash verification algorithm, which periodically calculates the hash value of the data and compares it with the preset hash value. If they are inconsistent, the data is determined to be corrupted.
6. A data storage system based on cloud storage, characterized in that, The system includes: The data preprocessing module is used to receive raw data sent by the terminal and obtain standardized processed data; The data encryption module is used to encrypt standardized data using a dual encryption mechanism that combines symmetric and asymmetric encryption, and output encrypted data. The node allocation module is used to construct a multi-cloud storage node cluster, which includes a primary storage node and at least two backup storage nodes. The primary storage node and the backup storage nodes belong to different cloud service providers. Based on the type, size and access frequency of the encrypted data, a load balancing algorithm is used to allocate corresponding primary and backup storage nodes to the encrypted data. The data upload and backup module is used to upload encrypted data to the assigned primary storage node and simultaneously back it up to the corresponding backup storage node, so as to achieve real-time data synchronization between the primary storage node and the backup storage node. The access maintenance module is used to receive access requests from terminals, perform identity verification and permission checks on the access requests, retrieve the target data after successful verification and send it back to the terminal; at the same time, it regularly performs integrity checks, defragmentation and redundant backup updates on the data in the cloud storage nodes to achieve automatic recovery after data corruption. The control module is electrically connected to the data preprocessing module, data encryption module, node allocation module, data upload and backup module, and access and maintenance module, respectively, and is used to control the coordinated work of each module to ensure the orderly progress of data storage.
7. A data storage system based on cloud storage according to claim 6, characterized in that: The data preprocessing module includes a format verification unit for verifying the format of the raw data, a redundancy removal unit for removing redundant data from the raw data, and an adaptive compression unit for compressing the raw data.
8. A data storage system based on cloud storage according to claim 6, characterized in that: The data encryption module includes a symmetric encryption unit, an asymmetric encryption unit, and a key management unit to encrypt standardized data.
9. A data storage system based on cloud storage according to claim 6, characterized in that: The node allocation module includes a cluster construction unit, a load monitoring unit, and a node allocation unit to build a multi-cloud storage node cluster, calculate the load weight of each node, and allocate corresponding primary storage nodes and backup storage nodes to the data based on the load weight.
10. A data storage system based on cloud storage according to claim 6, characterized in that: The access maintenance module includes an identity verification unit, a permission verification unit, a data retrieval unit, and a data maintenance unit to perform identity verification and permission verification. After successful verification, the target data is retrieved and fed back to the terminal. The module also performs integrity checks, defragmentation, and redundant backup updates on the data in the cloud storage nodes on a regular basis.