Distributed object storage tag retrieval method, system and device

Abstract

The present invention provides a distributed object storage tag retrieval method, system and device, the method comprising: obtaining an object query request, the object query request is used to query an object, each object is provided with multiple classification identifiers, each classification identifier corresponds to a request condition, multiple storage spaces are created according to the classification identifiers, each storage space only stores the request conditions corresponding to the classification identifiers in different objects; extracting the request conditions in the object query request; obtaining the classification identifier corresponding to the request condition based on a dictionary tree; calibrating the corresponding storage space according to the classification identifier, using an ant colony algorithm in the calibrated storage space to process the query request, and obtaining the query result and the optimal retrieval path of the object. The present invention has the following beneficial effects: It solves the technical problems of hash conflicts, limitations in range searches and low efficiency in processing large-scale data in the prior art.

Description

Technical Field

[0001] The present invention belongs to the field of computer technology, and in particular to a distributed object storage tag retrieval method, system and device. Background Art

[0002] With the rapid development of artificial intelligence, machine learning and big data technology, data has experienced an unprecedented explosive growth, giving birth to many new applications that are highly dependent on massive data, greatly enhancing the strategic value of data. As a key technology to support large-scale data storage needs, object storage has become a key challenge in fully exploring and utilizing the value of data by optimizing its retrieval efficiency.

[0003] Distributed object storage and retrieval technologies in the prior art mainly rely on hash search and linear search methods. Hash search uses a hash function to map the search content to a specific storage location to achieve search; linear search starts from the first element and searches and compares in sequence until the result to be searched is found. However, hash search has limitations when processing range searches, and is prone to hash conflicts, affecting search accuracy; linear search methods are less efficient when processing large-scale data, resulting in low overall search performance. Summary of the invention

[0004] In view of this, the present invention aims to propose a distributed object storage tag retrieval method, system and device, in order to solve at least one of the above-mentioned technical problems.

[0005] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0006] A first aspect of the present invention provides a distributed object storage tag retrieval method, the method comprising:

[0007] Obtain an object query request, where the object query request is used to query an object, where multiple classification identifiers are set in each object, each classification identifier corresponds to a request condition, and multiple storage spaces are created according to the classification identifiers, where each storage space only stores request conditions corresponding to the classification identifiers in different objects;

[0008] Extract request conditions in the object query request;

[0009] Obtaining the classification identifier corresponding to the request condition based on the dictionary tree;

[0010] The corresponding storage space is calibrated according to the classification identification, and the query request is processed in the calibrated storage space using the ant colony algorithm to obtain the query result and the optimal retrieval path of the object.

[0011] Furthermore, the dictionary tree is a tree data structure, and its specific structure includes:

[0012] A root node, which serves as a starting point and does not store any characters;

[0013] A tree node, each of which stores a character, sequentially connecting the characters in the path between the root node and the current tree node to obtain a character string corresponding to the current tree node; wherein the characters represented by all child nodes of each node are different;

[0014] The end mark indicates the end of the character string and is used to distinguish the prefix from the complete character string.

[0015] Furthermore, the process of obtaining the classification identifier corresponding to the request condition includes:

[0016] Construct a corresponding dictionary tree for each classification identifier, and the dictionary tree stores all strings related to the corresponding classification identifier;

[0017] Traverse the dictionary tree corresponding to each classification identifier. In each dictionary tree, search for character nodes that match the request conditions from the root node in sequence according to the character order of the request conditions, and return the corresponding information based on the search results.

[0018] Furthermore, the process of returning corresponding information according to the search result includes:

[0019] If the path corresponding to the search result is complete and the last character node is the end mark, the request condition is stored in the dictionary tree of the corresponding category mark, marked as a successful query and the current category mark is returned; otherwise, the dictionary tree of the next category is queried until the query is successful;

[0020] If the query is still unsuccessful after traversing the dictionary trees of all classification identifiers, an error warning is returned to indicate that the request condition is incorrect.

[0021] Furthermore, the process of processing the query request using the ant colony algorithm includes:

[0022] The data in the storage space is stored in a grid-like manner, and each point in the grid records a character in the request condition. The first point corresponding to the query condition is taken as the starting position, and the ant walks from the starting position to another point and continues to walk until the ant walks to the end mark, thereby obtaining an ant walking path;

[0023] Increase the pheromone concentration at the point corresponding to the requested condition and decrease the pheromone concentration at the remaining points;

[0024] Ants choose their wandering direction based on the pheromone concentration. If the current wandering path of the ants is shorter than the historical wandering path of the ants when the ants finish wandering, the pheromone concentration of the points in the current wandering path of the ants will increase.

[0025] The ant walking process is iterated until the shortest ant walking path is obtained, which is taken as the most effective query path.

[0026] Furthermore, each ant is equipped with an independent memory for storing search process information and control parameters, including:

[0027] The process information includes a taboo table, an allowed access object table, and a pheromone release matrix; the control parameters include a pheromone importance factor, a heuristic information importance factor, a pheromone volatility factor, and a pheromone intensity constant.

[0028] A second aspect of the present invention provides a distributed object storage tag retrieval system, the system comprising:

[0029] The request receiving module establishes a connection with the application, receives the request conditions in the object query request, passes the request conditions to the request classification module for processing, and returns the content sent by the calculation and retrieval module to the connected application;

[0030] A request classification module receives the request conditions sent by the request receiving module, queries the corresponding classification identifier according to the request conditions, and sends the request conditions and their corresponding classification identifiers to the calculation retrieval module;

[0031] The computational retrieval module receives the information sent by the request classification module, determines the query scope according to the classification identifier, uses the request conditions within the query scope and combines the ant colony algorithm to process the object query request to obtain the query result and the optimal search path, and sends them to the request receiving module.

[0032] The third aspect of the present invention proposes an electronic device, comprising a processor and a memory that is communicatively connected to the processor and is used to store executable instructions for the processor, wherein the processor is used to execute the distributed object storage tag retrieval method described in the first aspect above.

[0033] The fourth aspect of the present invention proposes a server, characterized in that it includes at least one processor and a memory communicatively connected to the processor, the memory storing instructions executable by the at least one processor, and the instructions are executed by the processor so that the at least one processor executes the distributed object storage tag retrieval method as described in the first aspect.

[0034] The fifth aspect of the present invention proposes a computer-readable storage medium storing a computer program, characterized in that: when the computer program is executed by a processor, the distributed object storage tag retrieval method described in the first aspect is implemented.

[0035] Compared with the prior art, the distributed object storage tag retrieval method, system and device of the present invention have the following beneficial effects:

[0036] According to the preset types of to-be-queried fields contained in the query request, the dictionary tree data structure is used to quickly find and determine the classification identifiers to which these to-be-queried fields belong; according to the query request classification identifier, the corresponding record content is found and determined; based on the record content corresponding to the query request classification identifier, the ant colony algorithm is used to search to find and return the query results and the optimal retrieval path that match the query request content of the business side object, which solves the technical problems of hash conflicts, limitations in range searches and low efficiency in processing large-scale data in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0038] Figure 1 This is a schematic diagram of the process of the distributed object storage tag retrieval method according to an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the structure of a distributed object storage tag retrieval system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0041] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0042] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0043] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0044] Embodiment 1

[0045] like Figure 1 As shown, a distributed object storage tag retrieval method, the method comprising:

[0046] Obtain an object query request, where the object query request is used to query an object, where multiple classification identifiers are set in each object, each classification identifier corresponds to a request condition, and multiple storage spaces are created according to the classification identifiers, where each storage space only stores request conditions corresponding to the classification identifiers in different objects;

[0047] S1, extracting request conditions in the object query request;

[0048] S2, obtaining a classification identifier corresponding to the request condition based on the dictionary tree;

[0049] S3. Demarcate the corresponding storage space according to the classification identifier, and use the ant colony algorithm to process the query request in the demarcated storage space to obtain the query result and the optimal retrieval path of the object.

[0050] The dictionary tree is a tree data structure, and its specific structure includes:

[0051] A root node, which serves as a starting point and does not store any characters;

[0052] A tree node, each of which stores a character, sequentially connecting the characters in the path between the root node and the current tree node to obtain a character string corresponding to the current tree node; wherein the characters represented by all child nodes of each node are different;

[0053] The end mark indicates the end of the character string and is used to distinguish the prefix from the complete character string.

[0054] In some embodiments, the relationship between the object, the classification identifier (Key), and the request condition (Value) is as follows:

[0055] Distributed object storage tags are used to describe the category of objects. Objects are marked with a set of key-value pairs. Tags can be added when uploading objects, or for existing objects. The Key of the key-value pair is used to record the classification identifier of the object, and the Value is used to record the description information of the category.

[0056] A single object can be set with up to 20 tags. Keys and Values ​​cannot be repeated. The length of each Key cannot exceed 128 characters, and the length of each Value cannot exceed 256 characters. Keys and Values ​​are case sensitive. Key and Value names cannot contain '-', which is the end mark.

[0057] For example, there is the following tag information: Name: zs; Age: 35; Position: pm; Address: bj.

[0058] In the object storage process, data is stored by category, and independent storage space is created based on the classification identification KEY of the tag. The data records are regarded as points in the grid, and each point represents an object.

[0059] For example, there is the following storage information: Under the Name category, the storage space stores 9 objects, and the description information is zs, ls, lw, ls, zs, zta, zs, wh, ls;

[0060] Under the Address category, the storage space stores 9 objects, and their description information is tj.hrb, bj, ti, nmg, sh, bj, tj, tj.

[0061] The process of obtaining the classification identifier corresponding to the request condition includes:

[0062] Construct a corresponding dictionary tree for each classification identifier, and the dictionary tree stores all strings related to the corresponding classification identifier;

[0063] Traverse the dictionary tree corresponding to each classification identifier. In each dictionary tree, search for character nodes that match the request conditions from the root node in sequence according to the character order of the request conditions, and return the corresponding information based on the search results.

[0064] The process of returning corresponding information according to the search result includes:

[0065] If the path corresponding to the search result is complete and the last character node is the end mark, the request condition is stored in the dictionary tree of the corresponding category mark, marked as a successful query and the current category mark is returned; otherwise, the dictionary tree of the next category is queried until the query is successful;

[0066] If the query is still unsuccessful after traversing the dictionary trees of all classification identifiers, an error warning is returned to indicate that the request condition is incorrect.

[0067] The process of processing the query request using the ant colony algorithm includes:

[0068] The data in the storage space is stored in a grid-like manner, and each point in the grid records a character in the request condition. The first point corresponding to the query condition is taken as the starting position, and the ant walks from the starting position to another point and continues to walk until the ant walks to the end mark, thereby obtaining an ant walking path;

[0069] Increase the pheromone concentration at the point corresponding to the requested condition and decrease the pheromone concentration at the remaining points;

[0070] Ants choose their wandering direction based on the pheromone concentration. If the current wandering path of the ants is shorter than the historical wandering path of the ants when the ants finish wandering, the pheromone concentration of the points in the current wandering path of the ants will increase.

[0071] The ant walking process is iterated until the shortest ant walking path is obtained, which is taken as the most effective query path.

[0072] Each ant is equipped with independent memory to store search process information and control parameters, including:

[0073] The process information includes a taboo table, an allowed access object table, and a pheromone release matrix; the control parameters include a pheromone importance factor, a heuristic information importance factor, a pheromone volatility factor, and a pheromone intensity constant.

[0074] Embodiment 2

[0075] A distributed object storage label retrieval system, characterized in that the system comprises:

[0076] The request receiving module establishes a connection with the application, receives the request conditions in the object query request, passes the request conditions to the request classification module for processing, and returns the content sent by the calculation and retrieval module to the connected application;

[0077] A request classification module receives the request conditions sent by the request receiving module, queries the corresponding classification identifier according to the request conditions, and sends the request conditions and their corresponding classification identifiers to the calculation retrieval module;

[0078] The computational retrieval module receives the information sent by the request classification module, determines the query scope according to the classification identifier, uses the request conditions within the query scope and combines the ant colony algorithm to process the object query request to obtain the query result and the optimal search path, and sends them to the request receiving module.

[0079] like Figure 2 As shown, in some embodiments, the structure and functions of the distributed object storage tag retrieval system are as follows:

[0080] The system is divided into request receiving module, request classification module, and calculation retrieval module;

[0081] A) Request receiving module: It is responsible for establishing a connection with the application. Its main function is to receive the request conditions (i.e., the Value of the tag) in the object query request, and then pass these request conditions to the request classification module for processing; in addition, this module also supports returning the query result information to the corresponding application.

[0082] B) Request classification module: It is divided into receiving unit, query unit and sending unit;

[0083] Receiving unit: used to receive the tag Value passed from the request receiving module.

[0084] Query unit: Confirm the category key corresponding to the valve based on the dictionary tree query.

[0085] The dictionary tree is an efficient tree data structure, which is particularly suitable for handling the storage and search problems of string sets. It reduces storage space and query time by using the common prefix of the string. The root node does not contain any characters, and each node except the root node contains only one character; from the root node to a certain node, the characters passed on the path are connected to form the string corresponding to the node; all child nodes of each node contain different characters; the character ends, and the child node contains '-', which is the end mark;

[0086] During the label construction process, a dedicated dictionary tree is constructed for each category Key.

[0087] When determining the category key corresponding to the valve, the system will traverse the dictionary trees corresponding to each category key in turn. The search process imitates the way of looking up a dictionary, accessing the tree nodes according to the established order and rules. Once the valve is found in the dictionary tree of a category key, the system confirms and returns the category key. If the valve is not in the current dictionary tree, the system will continue to check the dictionary tree of the next category key until a matching value is found. If a matching value is not found after traversing all dictionary trees, the query condition Value input error is returned.

[0088] For example, there are two categories of labels, Address and Name. There are tj and hrb in the Address category, and there are zs, ls, and lw in the Name category. The specific process of determining the category to which ls belongs is as follows:

[0089] First, search for 'ls' in the dictionary tree of Address, and search the child nodes of the root node from the root node to find 'l'; there is no 'l' character, and the dictionary tree search of Address ends; then search for 'ls' in the dictionary tree of Name, and search the child nodes of the root node from the root node to find 'l'; search for 's' from the child nodes of 'l'; confirm that the child nodes of 'ls' contain '-', which is the end mark; the characters match successfully, and return the classification mark "Name" of the queried Value.

[0090] Sending unit: Sends the query condition Valve value and the category Key value corresponding to the query condition Valve value to the calculation and retrieval module.

[0091] C) Computation and retrieval module: It is divided into receiving unit, computing unit and sending unit;

[0092] Receiving unit: used to receive the query condition Valve value transmitted from the request classification module and the category Key value corresponding to the query condition Valve value.

[0093] Computing unit: Determine the query scope, i.e., query space, based on the category key value. In this space, the query condition Valve value is used in combination with the ant colony algorithm to process the object query request on the business side and finally output the query result.

[0094] The ant colony algorithm is a swarm intelligence optimization algorithm that simulates the foraging behavior of ants. It was originally used to solve the traveling salesman problem. Later, due to its strong adaptability and optimization solving capabilities, it was widely used in various optimization scenarios, including path planning of mobile robots, workshop operation scheduling, and trajectory planning. The ant colony algorithm is applied to the field of distributed object label retrieval.

[0095] Specifically, this embodiment determines an independent storage space through a label-based classification identifier KEY, and within the space, according to the query condition Valve value, uses the ant colony algorithm to plan an optimal path covering all target Valve values, and finally returns the nodes on the path and the optimal path to complete the retrieval task.

[0096] In the object retrieval process, the first matching point with the same Valve value as the query condition is set as the starting position of the ant's walk. Then, the ant walks freely in the fully connected table. The walking trajectory of each ant represents a retrieval attempt starting from the starting point. If the walking path of an ant is shorter, that is, its retrieval result is more accurate, then the path will be given more pheromones.

[0097] As the ants continue to wander, more pheromones will accumulate between objects with the same target Value, while the pheromones between objects with different target Values ​​will gradually decrease due to volatilization. This process is continuously iterated to optimize the retrieval object nodes and their connection paths, ensuring that the target object and its optimal retrieval path can be located more accurately.

[0098] In an ant colony optimization algorithm applied to the above embodiment, it is assumed that the ant colony contains m ants. These ants rely on a pheromone matrix to guide path selection during the search process. The matrix records the pheromone concentrations between all objects. The goal of the algorithm is to find the shortest path and its corresponding optimal path.

[0099] Each ant is equipped with independent memory to store key information during its search, including:

[0100] Taboo table: records the objects that the ant has visited to ensure that these objects are not visited repeatedly in subsequent searches.

[0101] The table of objects that can be accessed: stores the unvisited objects that the current ant can still access, as a reference for its future search direction.

[0102] Pheromone release matrix: used to record the amount of pheromone released by the ant on the path it passes through in an iteration cycle.

[0103] In addition, each ant also carries some control parameters, including:

[0104] α: Pheromone importance factor, which controls the weight of pheromone in path selection.

[0105] β: Heuristic information importance factor, which controls the weight of heuristic information (such as path length) in path selection.

[0106] ρ: Pheromone volatilization factor, which determines the reduction ratio of pheromone after each iteration.

[0107] Q: Pheromone intensity constant, which determines the total amount of pheromone released onto the path after the ant completes one iteration.

[0108] During the operation of the algorithm, each ant will calculate the total cost or distance of its entire walk as the basis for evaluating the quality of the path. When the algorithm runs for the maximum number of iterations, it will stop walking and return the target object and its optimal retrieval path.

[0109] According to the scheme described in the above embodiment, a specific ant colony algorithm process is given as follows:

[0110] 1. Initialization;

[0111] 2. Query the matching node and set the first matching point found as the starting position of the ant's walk;

[0112] 3. Select the next route location based on the taboo list, the table of objects allowed to be accessed, the pheromone release matrix, and the control parameters;

[0113] 4. Determine whether there are new passing locations. If yes, return to the previous step and select the next passing location. After all locations are found, proceed to the next step.

[0114] 5. Update the pheromone matrix;

[0115] 6. Determine whether the maximum number of iterations has been reached. If not, return to the second step and start again from the starting point. If it has been reached, proceed to the next step.

[0116] 7. Return the target object and its optimal search path;

[0117] 8. End.

[0118] For example, retrieve the object whose label is ls in the distributed object storage.

[0119] By requesting the classification module, we obtain the category Name to which the label ls belongs, and execute the ant colony algorithm in the Name space to confirm the location of the object containing the label ls and its optimal search path.

[0120] Sending unit: transmits the result of the object query request to the request receiving module, including the specific location of the object and the optimized best retrieval path.

[0121] Embodiment 3

[0122] An electronic device comprises a processor and a memory which is in communication with the processor and is used to store instructions executable by the processor, wherein the processor is used to execute the distributed object storage tag retrieval method described in the first embodiment above.

[0123] Embodiment 4

[0124] A server, characterized in that it includes at least one processor and a memory communicatively connected to the processor, the memory storing instructions executable by the at least one processor, the instructions being executed by the processor so that the at least one processor executes the distributed object storage tag retrieval method as described in Example 1.

[0125] Embodiment 5

[0126] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the distributed object storage tag retrieval method described in Example 1.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

[0128] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed object storage tag retrieval method, characterized in that: The method comprises: Obtain an object query request, where the object query request is used to query an object, where multiple classification identifiers are set in each object, each classification identifier corresponds to a request condition, and multiple storage spaces are created according to the classification identifiers, where each storage space only stores request conditions corresponding to the classification identifiers in different objects; Extract request conditions in the object query request; Obtaining the classification identifier corresponding to the request condition based on the dictionary tree; The corresponding storage space is calibrated according to the classification mark, and the query request is processed in the calibrated storage space using the ant colony algorithm to obtain the query result and the optimal search path of the object; The process of processing the query request using the ant colony algorithm includes: The data in the storage space is stored in a grid-like manner, each point in the grid records a character in the request condition, and the first point of the grid corresponding to the query condition is used as the starting position. The ant walks from the starting position to another point and continues to walk until the ant walks to the end mark, thereby obtaining an ant walking path; Increase the pheromone concentration at the point corresponding to the requested condition and decrease the pheromone concentration at the remaining points; Ants choose their wandering direction based on the pheromone concentration. If the current wandering path of the ants is shorter than the historical wandering path of the ants when the ants finish wandering, the pheromone concentration of the points in the current wandering path of the ants will increase. Iterate the ant walking process until the shortest ant walking path is obtained, and take it as the most effective query path; Each ant is equipped with independent memory to store search process information and control parameters, including: The process information includes a taboo table, an allowed access object table, and a pheromone release matrix; the control parameters include a pheromone importance factor, a heuristic information importance factor, a pheromone volatility factor, and a pheromone intensity constant.

2. The distributed object storage tag retrieval method according to claim 1, characterized in that: The dictionary tree is a tree data structure, and its specific structure includes: A root node, which serves as a starting point and does not store any characters; A tree node, each of which stores a character, sequentially connecting the characters in the path between the root node and the current tree node to obtain a character string corresponding to the current tree node; wherein the characters represented by all child nodes of each node are different; The end mark indicates the end of the character string and is used to distinguish the prefix from the complete character string.

3. The distributed object storage tag retrieval method according to claim 2, characterized in that: The process of obtaining the classification identification corresponding to the request condition based on the dictionary tree includes: Construct a corresponding dictionary tree for each classification identifier, and the dictionary tree stores all strings related to the corresponding classification identifier; Traverse the dictionary tree corresponding to each classification identifier. In each dictionary tree, search for character nodes that match the request conditions from the root node in sequence according to the character order of the request conditions, and return the corresponding information based on the search results.

4. The distributed object storage tag retrieval method according to claim 3, characterized in that: The process of returning corresponding information according to the search result includes: If the path corresponding to the search result is complete and the last character node is the end mark, the request condition is stored in the dictionary tree of the corresponding category mark, marked as a successful query and the current category mark is returned; otherwise, the dictionary tree of the next category is queried until the query is successful; If the query is still unsuccessful after traversing the dictionary trees of all classification identifiers, an error warning is returned to indicate that the request condition is incorrect.

5. A distributed object storage tag retrieval system, applying the distributed object storage tag retrieval method according to any one of claims 1 to 4, characterized in that: The system comprises: The request receiving module establishes a connection with the application, receives the request conditions in the object query request, passes the request conditions to the request classification module for processing, and returns the content sent by the calculation and retrieval module to the connected application; A request classification module receives the request conditions sent by the request receiving module, queries the corresponding classification identifier according to the request conditions, and sends the request conditions and their corresponding classification identifiers to the calculation retrieval module; The computational retrieval module receives the information sent by the request classification module, determines the query scope according to the classification identifier, uses the request conditions within the query scope and combines the ant colony algorithm to process the object query request to obtain the query result and the optimal search path, and sends them to the request receiving module.

6. An electronic device, comprising a processor and a memory connected to the processor for storing instructions executable by the processor, characterized in that: The processor is used to execute the distributed object storage tag retrieval method described in any one of claims 1-4 above.

7. A server, characterized in that: It includes at least one processor and a memory communicatively connected to the processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor so that the at least one processor executes the distributed object storage tag retrieval method as described in any one of claims 1-4.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the distributed object storage tag retrieval method described in any one of claims 1 to 4 is implemented.

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