Cloud network data storage method and device based on fog computing, equipment and medium

Abstract

The application provides a cloud network data storage method and device based on fog computing, equipment and medium, and relates to the technical field of cloud servers. The method generates an Internet Protocol address cloud resource pool association table according to a cloud resource pool identifier and a user terminal Internet Protocol address. A plurality of fog computing nodes are established according to the density of the user terminal. In response to a registration request of the user terminal, a resource locator is generated and sent to the user terminal. In response to a file upload request packet sent by the user terminal, a target cloud storage pool is determined for the user terminal according to the Internet Protocol address cloud resource pool association table, and a target cloud storage pool address identifier is sent to the user terminal. In response to an upload data request, a target fog computing node list for uploading data for the user terminal is determined according to a preset fog computing node screening algorithm, and the target fog computing node list is sent to the user terminal.

Description

Technical Field

[0001] This application relates to the field of cloud server technology, and in particular to a cloud network data storage method, apparatus, device and medium based on fog computing. Background Technology

[0002] The cloud-network service architecture is based on two fundamental pillars: first, the operator's existing data centers or service centers, which are transformed into new service and data centers; and second, the already established next-generation network. Both operate on the Internet Protocol (IP) network and are now well integrated, forming a powerful and flexible Unified Service Implementation (USD) system. This provides convenient and fast cloud computing and network services to various customers, collectively referred to as "cloud-network integration" services.

[0003] Current cloud storage methods store data in different resource pools based on different regions. For example, data from region A is stored in the resource pool corresponding to region A, and data from region B is stored in the resource pool corresponding to region B. Users can only use the storage services of the resource pool they have purchased. If a user has purchased services from region A and roams to region B, the user first accesses the Internet from region B, then the Internet connection is routed to region A, and then the Internet connection from region A is routed to the cloud storage resource pool storage service in region A.

[0004] However, existing cloud network data transmission methods have long data transmission latency and poor user experience. Summary of the Invention

[0005] This application provides a cloud network data storage method, apparatus, device, and medium based on fog computing to solve the technical problems of long data transmission latency and poor user experience in existing cloud network data methods.

[0006] Firstly, this application provides a cloud network data storage method based on fog computing, including:

[0007] Based on the cloud resource pool identifier and the user terminal Internet Protocol address, an Internet Protocol address cloud resource pool association table is generated. Any two cloud resource pools are connected through a high-speed link, and the bandwidth of the high-speed link is greater than a preset bandwidth threshold.

[0008] Multiple fog computing nodes are established based on the density of user terminals;

[0009] In response to a registration request from a user terminal, a resource locator is generated and sent to the user terminal.

[0010] In response to a file upload request packet sent by a user terminal, a target cloud storage pool is determined for the user terminal according to the Internet Protocol address cloud resource pool association table, and the target cloud storage pool address identifier is sent to the user terminal so that the user terminal initiates an upload data request after receiving the target cloud storage pool address identifier. The file upload request packet includes the resource locator of the user terminal.

[0011] In response to the data upload request, a target fog computing node list for data upload to the user terminal is determined according to a preset fog computing node filtering algorithm, wherein the target fog computing node list includes at least one target fog computing node;

[0012] The target fog computing node list is sent to the user terminal so that the user terminal can establish a connection with the target fog computing nodes and upload data to the target cloud resource pool through the target fog computing nodes.

[0013] This application establishes a high-speed link between cloud resource pools, characterized by low data transmission latency and high speed. It generates an Internet Protocol address (IPA) cloud resource pool association table for user terminals and cloud resource pools, and establishes multiple fog computing nodes based on the density of user terminals. These fog computing nodes can provide data upload services to users. At the network edge, data can be processed and analyzed closer to the source, quickly uploading the user's data to the nearest cloud resource pool in the IPA cloud resource pool association table. This creates more access points for user terminals, further improving the efficiency of data transmission between users and the cloud. This results in increased business data throughput, reduced transmission latency, reduced jitter, and easier access to the storage system from the nearest endpoint, enhancing user experience and the convenience of cloud storage.

[0014] Optionally, the registration request includes a user identifier; correspondingly, generating a resource locator in response to the user terminal's registration request includes: performing a hash calculation on the user identifier and the registration date in response to the user terminal's registration request to obtain a resource locator.

[0015] In this application, a unique link is generated for each user, and a resource locator is obtained through hash calculation. This prevents man-in-the-middle attacks from obtaining user information and improves the security of user data and cloud network data storage.

[0016] Optionally, the file upload request packet further includes the Internet Protocol address of the user terminal; correspondingly, the step of determining the target cloud storage pool for the user terminal in response to the file upload request packet sent by the user terminal, based on the Internet Protocol address cloud resource pool association table, includes: determining the cloud resource pool closest to the user terminal as the target cloud resource pool based on the Internet Protocol address of the user terminal and the Internet Protocol address cloud resource pool association table.

[0017] In this application, the target cloud resource pool is determined for the user based on the distance between the user terminal and the cloud resource pool, and a high-speed link is established between the cloud resource pools to realize fast data transmission, improve the efficiency of data transmission between the user and the cloud, so as to further improve the business data throughput, reduce transmission latency, reduce jitter, facilitate the user to access the storage system from the nearest end, and improve the user experience.

[0018] Optionally, the data upload request includes the number of data chunks and the chunk size; correspondingly, determining the target fog computing node list for the user terminal to upload data according to the preset fog computing node filtering algorithm includes: determining fog computing nodes whose distance from the user terminal is less than a preset distance threshold according to the Internet Protocol address of the user terminal; and determining the target fog computing node list for the user terminal to upload data according to the preset fog computing node filtering algorithm, combined with the chunk size and the matching status of the fog computing nodes whose distance from the user terminal is less than the preset distance threshold.

[0019] This application locates fog computing nodes around the user based on the address of the user terminal, and filters out a list of fog computing nodes that meet the requirements based on the block size and the load status of the fog computing nodes. This allows the identification of target fog computing nodes with the lowest transmission latency and the highest transmission speed, further improving the efficiency of cloud network data storage and enhancing the user experience.

[0020] Optionally, after sending the target fog computing node list to the user terminal, the method further includes: after the user terminal establishes a connection with the target fog computing node, receiving block data uploaded by the user terminal through the target fog computing node; and uploading the block data to the target cloud resource pool through the target fog computing node.

[0021] In this application, user terminal data is uploaded to the cloud resource pool through fog computing nodes. By processing data closer to the network edge, fog computing can significantly reduce data transmission latency, thereby shortening response time. Fog computing can improve security by processing and analyzing data closer to the source, reducing the risk of sensitive data being transmitted to remote data centers or the cloud over the network, further improving the security and transmission efficiency of cloud network data storage, and enhancing user experience.

[0022] Optionally, after receiving the block data uploaded by the user terminal through the target fog computing node, the method further includes: performing a digest calculation based on the digest data and block sequence number of the block data; if the digest calculation is incorrect, sending an error message to the user terminal.

[0023] This application can promptly detect data transmission errors and notify the user terminal in a timely manner, reminding the user terminal to retransmit the data, thereby improving the accuracy and reliability of cloud network data storage and further enhancing the user experience.

[0024] Optionally, after uploading the block data to the target cloud resource pool through the target fog computing node, the method further includes: updating the storage record according to a preset format.

[0025] Here, this application updates the storage record promptly after the user data is successfully uploaded, making it easier for users to understand the storage status and download the stored data based on the storage record, thus further improving the user experience.

[0026] Optionally, after updating the stored record according to the preset format, the method further includes:

[0027] In response to a user terminal's data download request, the storage location of the data to be downloaded by the user terminal is determined through the Internet Protocol address cloud resource pool association table.

[0028] This application not only provides a method for reducing data upload latency, but also allows users to quickly download data stored on cloud servers, improving data processing efficiency and further enhancing the user experience.

[0029] Secondly, this application provides a cloud network data storage device, comprising:

[0030] The association table generation module is used to generate an Internet Protocol address cloud resource pool association table based on the cloud resource pool identifier and the user terminal Internet Protocol address. Any two cloud resource pools are connected through a high-speed link, and the bandwidth of the high-speed link is greater than a preset bandwidth threshold.

[0031] The fog computing node establishment module is used to establish multiple fog computing nodes based on the density of user terminals.

[0032] The resource locator generation module is used to generate a resource locator in response to a registration request from a user terminal and send the resource locator to the user terminal.

[0033] The cloud resource pool determination module is used to respond to the file upload request packet sent by the user terminal, determine the target cloud storage pool for the user terminal according to the Internet Protocol address cloud resource pool association table, and send the target cloud storage pool address identifier to the user terminal, so that the user terminal initiates an upload data request after receiving the target cloud storage pool address identifier. The file upload request packet includes the resource locator of the user terminal.

[0034] A fog computing node determination module is used to respond to the data upload request and determine a list of target fog computing nodes for the data uploaded by the user terminal according to a preset fog computing node filtering algorithm, wherein the list of target fog computing nodes includes at least one target fog computing node.

[0035] The sending module is used to send the target fog computing node list to the user terminal, so that the user terminal can establish a connection with the target fog computing nodes and upload data to the target cloud resource pool through the target fog computing nodes.

[0036] Optionally, the registration request includes a user identifier;

[0037] Accordingly, the resource locator generation module is specifically used for:

[0038] In response to a user terminal's registration request, a hash calculation is performed on the user identifier and registration date to obtain a resource locator.

[0039] Optionally, the file upload request packet may also include the Internet Protocol address of the user terminal;

[0040] Accordingly, the cloud resource pool determination module is specifically used for:

[0041] Based on the Internet Protocol address of the user terminal and the Internet Protocol address cloud resource pool association table, the cloud resource pool closest to the user terminal is determined as the target cloud resource pool.

[0042] Optionally, the data upload request includes the number of data chunks and the chunk size;

[0043] Accordingly, the fog computing node determination module is specifically used for:

[0044] Based on the Internet Protocol address of the user terminal, determine the fog computing nodes that are less than a preset distance threshold from the user terminal;

[0045] Based on a preset fog computing node filtering algorithm, and combined with the block size and the matching status of fog computing nodes whose distance from the user terminal is less than a preset distance threshold, a list of target fog computing nodes for data upload by the user terminal is determined.

[0046] Optionally, after the sending module sends the target fog computing node list to the user terminal, the above device further includes an uploading module, used for:

[0047] After the user terminal establishes a connection with the target fog computing node, the target fog computing node receives the block data uploaded by the user terminal.

[0048] The block data is uploaded to the target cloud resource pool via the target fog computing node.

[0049] Optionally, after the upload module receives the block data uploaded by the user terminal through the target fog computing node, the above apparatus further includes:

[0050] Based on the summary data and block number of the block data, a summary calculation is performed;

[0051] If the summary calculation is incorrect, an error message is sent to the user terminal.

[0052] Optionally, after the upload module uploads the block data to the target cloud resource pool via the target fog computing node, the above apparatus further includes an update module for:

[0053] Update the stored records according to the preset format.

[0054] Optionally, after the update module updates the stored record according to a preset format, the above device further includes a download module for:

[0055] In response to a user terminal's data download request, the storage location of the data to be downloaded by the user terminal is determined through the Internet Protocol address cloud resource pool association table.

[0056] Thirdly, this application provides a cloud network data storage device based on fog computing, comprising: at least one processor and a memory;

[0057] The memory stores computer-executed instructions;

[0058] The at least one processor executes the computer execution instructions stored in the memory, causing the at least one processor to perform the cloud network data storage method based on fog computing as described in the first aspect and various possible designs of the first aspect.

[0059] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the cloud network data storage method based on fog computing as described in the first aspect and various possible designs of the first aspect.

[0060] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the cloud network data storage method based on fog computing as described in the first aspect and various possible designs of the first aspect.

[0061] This application provides a cloud network data storage method, apparatus, device, and medium based on fog computing. The method establishes high-speed links between cloud resource pools, resulting in low data transmission latency and high speed. It generates an Internet Protocol address (IPA) cloud resource pool association table for user terminals and cloud resource pools. Multiple fog computing nodes are established based on the density of user terminals. These fog computing nodes can provide data upload services to users. At the network edge, data can be processed and analyzed closer to the source, quickly uploading the user's data to the nearest cloud resource pool in the IPA cloud resource pool association table. This establishes more access points for user terminals, thereby improving the efficiency of data transmission between users and the cloud, significantly increasing business data throughput, reducing transmission latency, minimizing jitter, facilitating user access to the storage system from the nearest endpoint, reducing data transmission latency, improving user experience, and enhancing the convenience of cloud storage. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1 A schematic diagram of a cloud network data storage system architecture based on fog computing is provided for an embodiment of this application;

[0064] Figure 2 A flowchart illustrating a cloud network data storage method based on fog computing, provided for an embodiment of this application;

[0065] Figure 3 A schematic diagram of the structure of a cloud network data storage device based on fog computing provided in an embodiment of this application;

[0066] Figure 4 This is a schematic diagram of the structure of a cloud network data storage device based on fog computing, provided as an embodiment of this application.

[0067] The accompanying drawings have illustrated specific embodiments of this disclosure, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this disclosure to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0068] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0069] The terms “first,” “second,” “third,” and “fourth,” etc. (if present), in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0070] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0071] Although cloud service providers have been operating for several years, they still build separate resource pools for cloud storage, and each resource pool provides services independently. This means that once a user purchases storage services from a particular resource pool, they can only use that pool's storage. This is very inconvenient for users with frequent mobility needs. For example, if a user has purchased services in location A and roams to location B, they first need to access the internet in location B, then the internet connection is routed back to location A, and finally the internet connection in location A is routed back to the cloud storage resource pool in location A. This involves a long data transmission process from location B to location A, resulting in latency, packet loss, and jitter, leading to a poor user experience. Existing cloud network data transmission methods have long data transmission latency, resulting in a poor user experience.

[0072] To address the aforementioned technical issues, this application provides a cloud network data storage method, apparatus, device, and medium based on fog computing. This method schedules file blocks to the cloud resource pool closest to the user through high-speed inter-cloud network storage scheduling. When a user uploads data, it is also uploaded to the nearest cloud resource pool, thereby reducing latency, jitter, and packet loss probability when the user uses storage. Furthermore, by introducing fog computing nodes, the number of connection points for user terminals is increased, establishing more access points for user terminals, thereby improving transmission efficiency, reducing transmission latency, and increasing business data throughput.

[0073] Optionally, Figure 1 This is a schematic diagram of a cloud network data storage system architecture based on fog computing, provided as an embodiment of this application. Figure 1 As shown, the above architecture includes: a storage management system 101, a user terminal 102, a first fog computing node 103, a second fog computing node 104, a third fog computing node 105, a first cloud resource pool 106, a second cloud resource pool 107, and a third cloud resource pool 108.

[0074] The storage management system 101 includes a cloud operator storage management system 1011 and a cloud resource pool storage management system 1012.

[0075] User terminal 102 is connected to storage management system 101.

[0076] The cloud resource pool storage management system 1012 is connected to the first cloud resource pool 106, the second cloud resource pool 107 and the third cloud resource pool 108 respectively. It can communicate with the first cloud resource pool 106, the second cloud resource pool 107 and the third cloud resource pool 108 and manage the first cloud resource pool 106, the second cloud resource pool 107 and the third cloud resource pool 108.

[0077] In this system, user terminal 102 is connected to first fog computing node 103, second fog computing node 104 and third fog computing node 105 respectively, and storage management system 101 is connected to first fog computing node 103, second fog computing node 104 and third fog computing node 105 respectively. Both user terminal 102 and storage management system 101 can communicate with any fog computing node.

[0078] In this system, any two cloud resource pools can communicate via a high-speed link.

[0079] Optionally, the cloud operator storage management system 1011 and the cloud resource pool storage management system 1012 can be cloud servers.

[0080] It is understandable that the number and specific structure of the aforementioned storage management system 101, user terminal 102, first fog computing node 103, second fog computing node 104, third fog computing node 105, first cloud resource pool 106, second cloud resource pool 107, and third cloud resource pool 108 can be determined according to actual circumstances. Figure 1 This is merely illustrative; the embodiments in this application do not impose a specific limitation on the number of nodes mentioned above.

[0081] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the architecture of a cloud network data storage system based on fog computing. In other feasible embodiments of this application, the above architecture may include more or fewer components than illustrated, or combine some components, or split some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0082] Furthermore, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0083] The technical solutions of this application are described below using several embodiments as examples. The same or similar concepts or processes may not be repeated in some embodiments.

[0084] Figure 2 This application provides a flowchart illustrating a cloud network data storage method based on fog computing, which can be applied to... Figure 1 The storage management system 101 in the document can be implemented by a specific entity that can be determined based on the actual application scenario. For example... Figure 2 As shown, the method includes the following steps:

[0085] S201: Generate an Internet Protocol address cloud resource pool association table based on the cloud resource pool identifier and the user terminal Internet Protocol address.

[0086] Any two cloud resource pools are connected via a high-speed link, and the bandwidth of the high-speed link is greater than a preset bandwidth threshold.

[0087] It is understood that the preset bandwidth threshold can be determined according to the actual situation, and the embodiments of this application do not impose specific restrictions on it.

[0088] In one possible implementation, after cloud computing establishes cloud resource pools in various locations, high-speed inter-cloud links (high-speed links) are built between each cloud resource pool via dedicated lines. These dedicated lines can achieve bandwidths of 100G or more than 1000G. For each resource pool of the cloud operator, a mesh-like connection is desired, meaning there is a direct high-speed link between every two cloud resource pools, or at most one hop between them. Storage scheduling between cloud pools is accomplished through these links. For each cloud resource pool's storage resource pool, a cloud resource pool identifier is determined, such as a unique identification document (ID). Simultaneously, all user terminal Internet Protocol (IP) addresses, or IP address pools—that is, all possible user IP addresses—are assigned to designated cloud resource pools, forming an IP address-cloud resource pool association table. This IP address assignment relationship will be continuously refined and updated as the number of cloud resource pools increases.

[0089] S202: Establish multiple fog computing nodes based on the density of user terminals.

[0090] Optionally, multiple regions can be divided according to the preset region size. If the number of user terminals in a certain region is greater than the preset number threshold, a fog computing node is established at that user terminal, and a different number of fog computing nodes are established according to the number of user terminals in different regions.

[0091] Optionally, multiple regions can be divided according to a preset area size, and the regions can be sorted from largest to smallest according to the number of user terminals in each region. The number of fog computing nodes in different regions can then be determined according to the order.

[0092] Optionally, a large number of fog computing nodes can be deployed in areas with a high density of user terminals, such as public offices, where more than 30 fog computing nodes can be deployed in a 100-square-meter space.

[0093] S203: In response to the user terminal's registration request, generate a resource locator and send the resource locator to the user terminal.

[0094] Optionally, in this embodiment of the application, the communication with the user terminal can be through an application on the user terminal or through a portal system, website, etc.

[0095] Optionally, the registration request can be a login request or a purchase request from the user's terminal.

[0096] Optionally, users can purchase cloud storage services after logging into the cloud operator's portal.

[0097] Optionally, the registration request includes a user identifier; accordingly, in response to the user terminal's registration request, a resource locator is generated, including: in response to the user terminal's registration request, performing a hash calculation on the user identifier and the registration date to obtain the resource locator.

[0098] In this embodiment, a unique link is generated for each user, and a resource locator is obtained through hash calculation to prevent man-in-the-middle attacks from obtaining user information, thereby improving the security of user data and cloud network data storage.

[0099] In one possible implementation, the cloud operator provides a Uniform Resource Locator (URL) to users through a portal, allowing users to upload data to cloud storage. This URL is a unique link generated by the cloud operator for each user, obtained by performing a SHA256 hash of the user's ID and registration date. For example, if a user's ID, registration time, and phone number are: zhang***&2022***&185****1234, the hashed URL would be MD5(zhang***&2022***&185****1234) or other hash algorithms such as SHA256 or SM3. The purpose of this algorithm is solely to prevent man-in-the-middle attacks from extracting user information from the link. This link information is stored in the cloud operator's storage management system.

[0100] Optionally, after a user completes user ID verification through the cloud operator's portal or an application provided by the cloud operator, the cloud operator's storage management system returns a URL and a file block size requirement (blocksize) to the user application or portal system. The user application records the URL for use in subsequent processes.

[0101] S204: In response to the file upload request packet sent by the user terminal, determine the target cloud storage pool for the user terminal according to the Internet Protocol address cloud resource pool association table, and send the target cloud storage pool address identifier to the user terminal so that the user terminal can initiate an upload data request after receiving the target cloud storage pool address identifier.

[0102] The file upload request packet includes the resource locator of the user terminal.

[0103] Optionally, the file upload request packet also includes the Internet Protocol address of the user terminal; accordingly, in response to the file upload request packet sent by the user terminal, the target cloud storage pool is determined for the user terminal according to the Internet Protocol address cloud resource pool association table, including: determining the cloud resource pool closest to the user terminal as the target cloud resource pool according to the Internet Protocol address of the user terminal and the Internet Protocol address cloud resource pool association table.

[0104] In this embodiment, the target cloud resource pool is determined for the user based on the distance between the user terminal and the cloud resource pool, and a high-speed link is established between the cloud resource pools to achieve fast data transmission, improve the efficiency of data transmission between the user and the cloud, thereby increasing the business data throughput, reducing transmission latency, reducing jitter, facilitating users to access the storage system from the nearest end, and improving the user experience.

[0105] In one possible implementation, the user terminal sends a file upload request packet to the cloud operator's storage management system. This request packet includes: a URL, file size (calculated by the application or portal system), filename, and the user terminal's IP address. Upon receiving the user request, the cloud operator's storage management system returns upload progress information to the user and, based on the user terminal's IP address, selects the cloud resource pool closest to that IP address to allocate storage space to the user. It then returns the target cloud storage pool ID to the cloud operator's storage management system, which in turn returns the target cloud storage pool ID and the address of the target cloud resource pool's storage management system to the user terminal.

[0106] S205: In response to the data upload request, determine the list of target fog computing nodes for the user terminal to upload data based on the preset fog computing node filtering algorithm.

[0107] The target fog computing node list includes at least one target fog computing node.

[0108] Optionally, the data upload request includes the number of data chunks and the chunk size; correspondingly, according to a preset fog computing node filtering algorithm, a list of target fog computing nodes for uploading data to the user terminal is determined, including: determining fog computing nodes whose distance from the user terminal is less than a preset distance threshold based on the user terminal's Internet Protocol address; and determining the list of target fog computing nodes for uploading data to the user terminal based on the preset fog computing node filtering algorithm, combined with the chunk size and the matching status of fog computing nodes whose distance from the user terminal is less than the preset distance threshold.

[0109] In this embodiment, the fog computing nodes around the user are located based on the address of the user terminal. Based on the block size and the load status of the fog computing nodes, a list of fog computing nodes that meet the requirements is selected. This can identify the target fog computing node with the lowest transmission latency and the highest transmission speed, further improving the efficiency of cloud network data storage and enhancing the user experience.

[0110] Optionally, after receiving the address of the cloud resource pool storage management system, the user terminal divides the file into blocks according to the system-required block size and sends an upload data request to the cloud resource pool storage management system interface. This request includes the number of file system blocks and the block size.

[0111] Upon receiving the request, the cloud resource pool storage management system determines the user's location based on the source IP address carried in the information sent by the user terminal. Then, in the fog computing operator system, it locates fog computing nodes near the user based on their location. Based on the block size and the load status of the fog computing nodes, it selects a list of suitable fog computing nodes and sends it to the user terminal.

[0112] Alternatively, the selection algorithm for fog computing nodes can choose from the following methods:

[0113] Let the total load of the fog computing node be:

[0114]

[0115]

[0116] in For the overall load of the fog computing node, c i For CPU utilization, m i For memory utilization, b i This represents the bandwidth utilization of this fog node. i This refers to the weighting coefficient for each indicator. This indicator is determined based on the CPU, memory, and bandwidth allocation of the fog computing operator, depending on the specific circumstances; the embodiments in this application do not impose specific limitations. Furthermore, q1 + q2 + q3 = 1, and n is any positive integer.

[0117]

[0118] in This represents the idle load and available resource ratio of fog computing nodes.

[0119] Fog computing nodes s i The weight is

[0120]

[0121] The initial weight of each fog computing node is 10. The overall load of each fog computing node changes dynamically with the requests from end users, and the weight is dynamically adjusted according to the load of the fog computing node.

[0122] Total load F of each fog computing node (sum) Defined as:

[0123]

[0124] Weights H of each fog calculation node (sum) Defined as:

[0125]

[0126] The sum of the number of connections of each fog computing node B (sum) Defined as:

[0127]

[0128] Next, we will calculate the ratio of load to weight and the ratio of connection number to weight to find the usable fog computing node sequence and send it to the user terminal.

[0129] The filtering algorithm is as follows:

[0130] For each fog computing node, two values ​​P1 and P2 are calculated, forming a vector P. si (P1, P2).

[0131]

[0132]

[0133] For each fog computation node, calculate vector P. si Then filter out P based on the results. si Fog nodes whose vectors are all less than 1 are listed as a list array(P). i ...P m ...P r ).

[0134] Based on the block size and number of blocks sent by the user terminal, a suitable array of fog computing nodes is selected and sent to the user terminal. Nodes with memory space larger than the block size need to be selected. The specific number of nodes in this array depends on the fog computing node operator's operational strategy. For example, more fog computing nodes may be sent to high-priority users, and fewer to low-priority users.

[0135] S206: Send the target fog computing node list to the user terminal so that the user terminal can establish a connection with the target fog computing nodes and upload data to the target cloud resource pool through the target fog computing nodes.

[0136] In one possible implementation, after receiving information from the target fog computing node, the user terminal establishes a connection with each fog computing node and sends each file block to the fog computing node through these connections. Simultaneously, when sending block data, it sends the data block digest data and block sequence number. The digest data can use algorithms such as SHA256, MD5, or SM3. Upon receiving the data, the fog computing node first performs a digest calculation. If the digest calculation is incorrect, it replies to the user terminal, and the user terminal resends the data block. If the digest calculation is correct, the fog computing node sends the data block to the cloud resource pool storage management system. Upon receiving the data block, the cloud resource pool storage management system sorts the data blocks and checks for any missing data. If any is missing, it sends the missing block sequence number to the user terminal, and the user terminal continues to select a fog computing node that has already received a reply to resend the missing block. If the cloud resource pool storage management system checks for any issues, it proceeds to the next step. After completing the upload of a file block, the cloud resource pool storage management system updates the record for that file block in its own system. When the cloud resource pool storage management system receives a record, it sends file block storage information to the cloud operator's storage management system. Upon receiving this information, the cloud operator's storage management system updates its data. This data can be displayed in tabular form. Table 1's header may include `filename` and `datablock`. `filename` is the file name, and `datablock` is the file's data block digest name, calculated using a digest algorithm (such as MD5, SHA256, or SM3). Table 2's header may include `block` and `Avaliblezone`. `block` is the data block digest data, and `Avaliblezone` is the target cloud resource pool ID for this data block.

[0137] Here, this embodiment establishes a high-speed link between cloud resource pools, resulting in low data transmission latency and high speed. For user terminals and cloud resource pools, an Internet Protocol address (IPA) cloud resource pool association table is generated. Multiple fog computing nodes are established based on the density of user terminals. These fog computing nodes can provide data upload services to users. At the network edge, data can be processed and analyzed closer to the source, quickly uploading the data to be stored by the user to the nearest cloud resource pool in the IPA cloud resource pool association table. This establishes more access points for user terminals, thereby improving the efficiency of data transmission between users and the cloud, significantly increasing business data throughput, reducing transmission latency, minimizing jitter, facilitating user access to the storage system from the nearest endpoint, reducing data transmission latency, improving user experience, and enhancing the convenience of cloud storage use.

[0138] Optionally, after sending the target fog computing node list to the user terminal, the method further includes: after the user terminal establishes a connection with the target fog computing node, receiving the block data uploaded by the user terminal through the target fog computing node; and uploading the block data to the target cloud resource pool through the target fog computing node.

[0139] In this embodiment, user terminal data is uploaded to the cloud resource pool via fog computing nodes. By processing data closer to the network edge, fog computing can significantly reduce data transmission latency, thereby shortening response time. Fog computing can improve security by processing and analyzing data closer to the source, reducing the risk of sensitive data being transmitted to remote data centers or the cloud via the network, further improving the security and transmission efficiency of cloud network data storage, and enhancing user experience.

[0140] Optionally, after receiving the block data uploaded by the user terminal through the target fog computing node, the method further includes: performing digest calculation based on the digest data and block sequence number of the block data; if the digest calculation is incorrect, sending an error message to the user terminal.

[0141] In this application, the embodiments can promptly detect data transmission errors and notify the user terminal in a timely manner, reminding the user terminal to retransmit the data, thereby improving the accuracy and reliability of cloud network data storage and further enhancing the user experience.

[0142] Optionally, after uploading the block data to the target cloud resource pool via the target fog computing node, the method further includes: updating the storage record according to a preset format.

[0143] Here, in this embodiment of the application, after the user data is successfully uploaded, the storage record is updated in a timely manner, so that the user can understand the storage status and download the stored data according to the storage record, which further improves the user experience.

[0144] Optionally, after updating the stored record according to a preset format, the method further includes:

[0145] In response to a user terminal's data download request, the storage location of the data to be downloaded by the user terminal is determined through the Internet Protocol address cloud resource pool association table.

[0146] In addition to providing a data upload method that reduces latency, this application also allows users to quickly download data stored on cloud servers, improving data processing efficiency and further enhancing the user experience.

[0147] Optionally, this application embodiment also provides a data download method, the specific steps of which are as follows:

[0148] Download Process 1.1: The user logs into the cloud operator's storage management system through the cloud operator's portal or an application provided by the cloud operator. The user sends a request to browse the file list, which includes the resource locator (url1) sent by the cloud operator's storage management system during user terminal registration and the user's available memory space information. The cloud operator's storage management system returns a list of the user's files. The number of entries depends on the user's available memory space; for example, 2GB of memory might return 400 entries, and 8GB of memory might return 2000 entries.

[0149] Download Process 1.2: The user browses the entry records, selects a file name, and initiates a file download request to the cloud operator's storage management system. This request includes the user's source IP address and the requested file name, such as "My Movies." The cloud operator's storage management system responds with a message indicating that the download link is being generated on the user's terminal.

[0150] Download process 1.3: The cloud operator's storage management system searches for the cloud resource pool to which this IP address is assigned in the IP address cloud resource pool association table based on the source IP address in the request. The target cloud resource pool ID is then found.

[0151] Download Process 1.4: The cloud operator's storage management system determines that the file is not in the target cloud resource pool by checking Tables 1 and 2. The cloud operator's storage management system initiates a storage scheduling process, transferring the first file block from the cloud resource pool's storage management system first, followed by the second block, and then transferring it to the target cloud resource pool through high-speed, high-priority inter-cloud transmission scheduling, while updating Table 2.

[0152] Download process 1.5: The cloud operator's storage management system generates a download link URL3 pointing to the target cloud resource pool and returns it to the user terminal.

[0153] Download Process 1.6: The user terminal downloads file blocks via URL3. The cloud operator's storage management system schedules the third file block to the target cloud resource pool. Simultaneously, the cloud operator's storage management system generates a download link for block 2 in the target cloud resource pool. The user continues downloading, and so on, until all data blocks are downloaded. At the same time, the cloud operator's storage management system updates Table 2, adding the target cloud resource pool to the available zones of the third and fourth blocks, and generating download links. Multi-threaded downloads can also be supported here. The user sets a thread limit in the application. The user-set limit cannot exceed the limit set in the cloud operator's storage management system to prevent the system from being overwhelmed by the user's system. Within the limit, when the user terminal receives a link, it initiates a download request, thus achieving multi-threading. Each time the target cloud resource pool completes the download of a file block, it updates the last access time of each block in Table 3 located in the target cloud resource pool.

[0154] Alternatively, this application embodiment also provides another data download method, the specific steps of which are as follows:

[0155] Download Process 2.1: The user logs into the cloud operator's storage management system through the cloud operator's portal or an application provided by the cloud operator. The user sends a request to browse the file list, which includes URL1 and the user's terminal's available memory space information. The cloud operator's storage management system returns a list of the user's files. The number of entries depends on the user's terminal's available memory space; for example, 2GB of memory will return 400 entries, and 8GB of memory will return 2000 entries.

[0156] Download Process 2.2: The user browses the entry records, selects a file name, and initiates a file download request to the cloud operator's storage management system. This request includes the user's source IP address and the requested file name - "My Movies". The cloud operator's storage management system responds with information indicating that the download link is being generated on the user's terminal.

[0157] Download process 2.3: The cloud operator's storage management system searches for the target cloud resource pool assigned to this IP address in the IP address cloud resource pool association table based on the source IP address in the request. The target cloud resource pool ID is then found.

[0158] Download process 2.4: The cloud operator's storage management system determines whether the file exists in the target cloud resource pool by looking up Table 1 and Table 2.

[0159] Download process 2.5: The cloud operator's storage management system generates a download link (url3) pointing to the target cloud resource pool and returns it to the user terminal. It continuously generates download links for the user terminal until all blocks are downloaded. The fog computing node method used during the upload process can also be used here to improve download efficiency.

[0160] Download process 2.6: After each file block is downloaded from the target cloud resource pool, the last access time of each block in Table 3 of the target cloud resource pool is updated.

[0161] Optionally, embodiments of this application can also implement data adjustment and optimization of the storage system:

[0162] After a period of operation, there may be too much duplicate data across various cloud pools, requiring deletion to increase storage space and facilitate subsequent scheduling. The cloud operator's storage management system optimizes data deletion based on the operator's parameter configuration. For example, if the operator is configured to delete a maximum of 10 data entries, then the system iterates through the data stored in Table 2. If Table 2 contains 5 data entries, it's determined that no data needs to be deleted. If the operator is configured to delete a maximum of 3 data entries, and Table 2 contains 5, then data deletion is necessary. After retrieving more than 3 data blocks, the system then searches Table 3 in the relevant cloud storage pools. Based on the updates to Table 2, the data in Table 3 is updated, and the relevant data block information in Table 3 is deleted. For example, the data block corresponding to the resource pool with the longest access time is deleted.

[0163] Figure 3 A schematic diagram of a cloud network data storage device based on fog computing, provided in an embodiment of this application, is shown below. Figure 3 As shown, the apparatus in this embodiment includes: an association table generation module 301, a fog computing node establishment module 302, a resource locator generation module 303, a cloud resource pool determination module 304, a fog computing node determination module 305, and a sending module 306. The fog computing-based cloud network data storage device can be a server or a terminal device, or a chip or integrated circuit that implements the functions of a server or terminal device. It should be noted that the division of the association table generation module 301, fog computing node establishment module 302, resource locator generation module 303, cloud resource pool determination module 304, fog computing node determination module 305, and sending module 306 is only a logical functional division; physically, they can be integrated or independent.

[0164] The association table generation module is used to generate an association table of cloud resource pools based on the cloud resource pool identifier and the Internet Protocol address of the user terminal. Any two cloud resource pools are connected through a high-speed link, and the bandwidth of the high-speed link is greater than a preset bandwidth threshold.

[0165] The fog computing node establishment module is used to establish multiple fog computing nodes based on the density of user terminals.

[0166] The resource locator generation module is used to generate resource locators in response to the registration request from the user terminal and send the resource locators to the user terminal.

[0167] The cloud resource pool determination module is used to respond to the file upload request packet sent by the user terminal, determine the target cloud storage pool for the user terminal according to the Internet Protocol address cloud resource pool association table, and send the target cloud storage pool address identifier to the user terminal so that the user terminal can initiate an upload data request after receiving the target cloud storage pool address identifier. The file upload request packet includes the resource locator of the user terminal.

[0168] The fog computing node determination module is used to respond to the data upload request and determine the target fog computing node list for the user terminal to upload data according to the preset fog computing node filtering algorithm. The target fog computing node list includes at least one target fog computing node.

[0169] The sending module is used to send the target fog computing node list to the user terminal so that the user terminal can establish a connection with the target fog computing nodes and upload data to the target cloud resource pool through the target fog computing nodes.

[0170] Optionally, the registration request may include a user identifier;

[0171] Accordingly, the resource locator generation module is specifically used for:

[0172] In response to a user terminal's registration request, a hash calculation is performed on the user identifier and registration date to obtain a resource locator.

[0173] Optionally, the file upload request packet may also include the Internet Protocol address of the user terminal;

[0174] Accordingly, the cloud resource pool determination module is specifically used for:

[0175] Based on the Internet Protocol address of the user terminal and the Internet Protocol address cloud resource pool association table, the cloud resource pool closest to the user terminal is determined as the target cloud resource pool.

[0176] Optionally, the data upload request includes the number of data chunks and the chunk size;

[0177] Accordingly, the fog computing node determination module is specifically used for:

[0178] Based on the Internet Protocol address of the user terminal, determine the fog computing nodes that are less than a preset distance threshold from the user terminal;

[0179] Based on the preset fog computing node filtering algorithm, and combined with the block size and the matching status of fog computing nodes whose distance from the user terminal is less than a preset distance threshold, a list of target fog computing nodes for data upload by the user terminal is determined.

[0180] Optionally, after the sending module sends the target fog computing node list to the user terminal, the above device further includes an uploading module for:

[0181] After the user terminal establishes a connection with the target fog computing node, it receives the block data uploaded by the user terminal through the target fog computing node;

[0182] Block data is uploaded to the target cloud resource pool via the target fog computing node.

[0183] Optionally, after the upload module receives the block data uploaded by the user terminal through the target fog computing node, the above apparatus further includes:

[0184] Digest calculation is performed based on the digest data and block number of the block data;

[0185] If the summary calculation is incorrect, an error message will be sent to the user terminal.

[0186] Optionally, after the upload module uploads block data to the target cloud resource pool via the target fog computing node, the above apparatus further includes an update module for:

[0187] Update the stored records according to the preset format.

[0188] Optionally, after the update module updates the stored record according to a preset format, the above device further includes a download module for:

[0189] In response to a user terminal's data download request, the storage location of the data to be downloaded by the user terminal is determined through the Internet Protocol address cloud resource pool association table.

[0190] refer to Figure 4 The diagram illustrates a structural schematic of a fog computing-based cloud network data storage device 400 suitable for implementing embodiments of the present disclosure. This fog computing-based cloud network data storage device 400 can be a terminal device or a server. The terminal device can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, personal digital assistants (PDAs), portable Android devices (PADs), portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 4 The cloud network data storage device based on fog computing shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments disclosed herein.

[0191] like Figure 4As shown, the fog computing-based cloud network data storage device 400 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to programs stored in read-only memory (ROM) 402 or programs loaded from storage device 408 into random access memory (RAM) 403. The RAM 403 also stores various programs and data required for the operation of the fog computing-based cloud network data storage device 400. The processing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0192] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows the fog computing-based cloud data storage device 400 to communicate wirelessly or wiredly with other devices to exchange data. Although... Figure 4 A cloud network data storage device 400 based on fog computing is shown, but it should be understood that implementation or possession of all the shown devices is not required. More or fewer devices may be implemented alternatively.

[0193] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 409, or installed from a storage device 408, or installed from a ROM 402. When the computer program is executed by the processing device 401, it performs the functions defined in the methods of embodiments of this disclosure.

[0194] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0195] The aforementioned computer-readable medium may be included in the aforementioned fog computing-based cloud network data storage device; or it may exist independently and not assembled into the fog computing-based cloud network data storage device.

[0196] The aforementioned computer-readable medium carries one or more programs, which, when executed by the fog computing-based cloud network data storage device, cause the fog computing-based cloud network data storage device to perform the method shown in the above embodiments.

[0197] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0198] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0199] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0200] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0201] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A cloud network data storage method based on fog computing, characterized in that, include: Based on the cloud resource pool identifier and the user terminal Internet Protocol address, an Internet Protocol address cloud resource pool association table is generated. Any two cloud resource pools are connected through a high-speed link, and the bandwidth of the high-speed link is greater than a preset bandwidth threshold. Multiple fog computing nodes are established based on the density of user terminals; In response to a registration request from a user terminal, a hash calculation is performed on the user identifier and registration date to obtain a resource locator; the registration request includes the user identifier; Based on the user terminal's Internet Protocol (IP) address and the IP address cloud resource pool association table, the cloud resource pool closest to the user terminal is determined as the target cloud resource pool. The target cloud resource pool address identifier is sent to the user terminal, so that upon receiving the target cloud resource pool address identifier, the user terminal initiates an upload data request. The upload data request includes the user terminal's resource locator and IP address; the upload data request includes the number of data chunks and the chunk size. In response to the upload data request, based on the user terminal's IP address, fog computing nodes located less than a preset distance threshold are determined. Based on a preset fog computing node filtering algorithm, combined with the chunk size and the load status of the fog computing nodes located less than the preset distance threshold, a target fog computing node list is determined for the user terminal to upload data. The target fog computing node list includes at least one target fog computing node. The target fog computing node list is sent to the user terminal so that the user terminal can establish a connection with the target fog computing nodes and upload data to the target cloud resource pool through the target fog computing nodes; After the user terminal establishes a connection with the target fog computing node, the target fog computing node receives the block data uploaded by the user terminal. The block data is uploaded to the target cloud resource pool via the target fog computing node.

2. The method according to claim 1, characterized in that, After receiving the block data uploaded by the user terminal through the target fog computing node, the method further includes: Based on the summary data and block number of the block data, a summary calculation is performed; If the summary calculation is incorrect, an error message is sent to the user terminal.

3. The method according to claim 2, characterized in that, After the block data is uploaded to the target cloud resource pool via the target fog computing node, the method further includes: Update the stored records according to the preset format.

4. The method according to claim 3, characterized in that, After updating the stored records according to the preset format, the process further includes: In response to a user terminal's data download request, the storage location of the data to be downloaded by the user terminal is determined through the Internet Protocol address cloud resource pool association table.

5. A cloud network data storage device based on fog computing, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the cloud network data storage method based on fog computing as described in any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the cloud network data storage method based on fog computing as described in any one of claims 1 to 4.

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