Artificial intelligence resource scheduling system and method

Abstract

The invention discloses an artificial intelligence resource scheduling system and method, and relates to the technical field of scheduling systems, and the technical scheme is that the artificial intelligence resource scheduling system comprises a resource scheduling platform module, the resource scheduling platform module comprises a basic-level facility module, a resource management module, an intelligent scheduling module, a scheduling monitoring module, a safe scheduling management and control module and a connection module, the resource scheduling platform module is in data connection with the basic-level facility module, the resource management module, the intelligent scheduling module, the scheduling monitoring module, the safety scheduling management and control module and the connection module, and the connection end of the resource management module is provided with the resource library management module. The resource library management module comprises a resource registration module, a resource library construction module, a resource state monitoring module and a resource dynamic adjustment module, and the system has the beneficial effects that the compatibility and flexibility of the system are improved, the operation and maintenance efficiency is improved, the automation degree is high, intelligent decision making, resource allocation optimization and task scheduling are carried out, the operation cost is low, and the operation efficiency is improved. And resource waste is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of scheduling systems, and in particular to an artificial intelligence resource scheduling system and method. Background Art

[0002] With the continuous deepening of Internet applications, the demand for information integration and resource sharing among enterprises is increasing. In terms of technology, there has been a development from static, manual resource sharing to dynamic, network resource sharing. Since the resources involved in the integration are distributed and dynamically changing, how to reasonably allocate and schedule resources is the main issue we need to study.

[0003] The existing dispatching system has few interfaces, low system compatibility and flexibility, manual dispatching intervention, low degree of automation, high operating costs and large investment costs. Summary of the invention

[0004] To this end, the present invention provides an artificial intelligence resource scheduling system and method to solve the problems of few scheduling system interfaces, low system compatibility and flexibility, manual scheduling intervention, low degree of automation, high operating costs, and high investment costs.

[0005] In order to achieve the above-mentioned purpose, the present invention provides the following technical solutions: an artificial intelligence resource scheduling system, including a resource scheduling platform module, the resource scheduling platform module includes a basic facility module, a resource management module, an intelligent scheduling module, a scheduling monitoring module, a safe scheduling control module and a connection module, and the resource scheduling platform module is respectively connected to the basic facility module, the resource management module, the intelligent scheduling module, the scheduling monitoring module, the safe scheduling control module and the connection module.

[0006] Preferably, a resource library management module is provided at the connection end of the resource management module, and the resource library management module includes a resource registration module, a resource library construction module, a resource status monitoring module and a resource dynamic adjustment module, and the resource library management module is respectively data-connected to the resource registration module, the resource library construction module, the resource status monitoring module and the resource dynamic adjustment module.

[0007] Preferably, the intelligent scheduling module includes a scheduling task management module and an efficient scheduling module, and the intelligent scheduling module is respectively connected to the scheduling task management module and the efficient scheduling module in terms of data; the scheduling task management module includes a task receiving module, a task parsing module, a resource evaluation module and a task allocation module, and the scheduling task management module is respectively connected to the task receiving module, the task parsing module, the resource evaluation module and the task allocation module in terms of data; the efficient scheduling module includes a priority scheduling module, a load balancing module, a predictive scheduling module and an adaptive scheduling module, and the efficient scheduling module is respectively connected to the priority scheduling module, the load balancing module, the predictive scheduling module and the adaptive scheduling module in terms of data.

[0008] Preferably, the security scheduling control module includes an identity authentication module, a permission management module, a data encryption module and a security audit module, and the security scheduling control module is data-connected to the identity authentication module, the permission management module, the data encryption module and the security audit module respectively.

[0009] Preferably, the basic facility module includes a scheduling server body, a plurality of support columns are fixedly provided at the bottom of the scheduling server body, a through slot is provided on one side of the support column, a card plate is provided inside the through slot, two springs are connected between the card plate and the inner wall of the through slot, one side of the card plate extends out of the support column, an inner cavity is provided inside the scheduling server body, a support plate is fixedly provided at the bottom of the scheduling server body, a threaded rod is connected to the top of the support plate through a bearing, the threaded rod extends into the inner cavity and is connected to the inner wall of the inner cavity through a bearing, a limit rod is fixedly provided between the support plate and the scheduling server body, a connecting plate is provided on the outside of the threaded rod through a threaded sleeve, the limit rod penetrates the connecting plate and is slidably connected to the connecting plate, a plurality of push blocks are fixedly provided on the outside of the connecting plate, the push blocks slide in the through slot, a first bevel gear is fixedly provided on the outside of the threaded rod, a second bevel gear is provided on one side of the first bevel gear, the first bevel gear is meshed with the second bevel gear, a rotating rod is fixedly provided on one side of the second bevel gear, one end of the rotating rod is fixedly connected to a knob, two fixed plates are fixedly provided inside the inner cavity, the rotating rod penetrates the fixed plate and is connected to the fixed plate through a bearing.

[0010] Preferably, a mounting base plate is provided at the bottom of the scheduling server body, a plurality of supporting sleeves are fixedly provided on the top of the mounting base plate, the supporting column extends into the interior of the supporting sleeve, a card slot is provided on the inner wall of the supporting sleeve, and the card plate is engaged with the card slot.

[0011] Preferably, an anti-theft cover is provided on one side of the dispatch server body, and a lock is provided on one side of the anti-theft cover.

[0012] Preferably, a box door is provided on one side of the dispatching server body, and a ventilation plate is provided on one side of the dispatching server body.

[0013] An artificial intelligence resource scheduling method, the specific steps are as follows:

[0014] S1, automatically register physical machines, virtual machines, containers and other resources, build a logical resource library based on resource type, performance and other attributes, monitor key indicators such as resource utilization and health status in real time, and automatically adjust resource allocation based on resource usage;

[0015] S2, receiving task submissions through the user interface, parsing task requirements, evaluating the current resource library status, determining available resources, and assigning tasks to the most appropriate resources based on resource evaluation results and task requirements;

[0016] S3. Sort tasks according to their priority, give priority to high-priority tasks, ensure load balancing of each node, avoid resource bottlenecks, plan resource allocation in advance based on historical data and prediction models, and dynamically adjust scheduling strategies according to the real-time status of the system.

[0017] The embodiments of the present invention have the following advantages:

[0018] 1. The scheduling system provides a rich set of API interfaces, supports the access of third-party tools and services, improves the compatibility and flexibility of the system, and automates deployment, monitoring, and fault recovery, reduces manual intervention, improves operation and maintenance efficiency, has a high degree of automation, makes intelligent decisions, optimizes resource allocation and task scheduling, has low operating costs, low investment costs, and reduces resource waste;

[0019] 2. The push block is driven downward by the connecting plate, and the push block moves downward and pushes the card plate to move. The spring on one side of the card plate is compressed and the card plate moves into the card slot at the same time, so that the card plate and the card slot are buckled. The support column is fixed inside the support sleeve, which is convenient for the installation and disassembly of the dispatching server body. The anti-theft cover is locked and fixed by the lock. It cannot be opened without a key, which prevents the dispatching server body from being disassembled and stolen. The ventilation plate has a ventilation function and is highly practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0021] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.

[0022] Figure 1 A system structure diagram of a resource scheduling platform module provided by the present invention;

[0023] Figure 2 A system structure diagram of the resource management module provided by the present invention;

[0024] Figure 3 A diagram showing the structure of the intelligent scheduling module system provided by the present invention;

[0025] Figure 4 A system structure diagram of the safety dispatching and control module provided by the present invention;

[0026] Figure 5 A stereoscopic diagram of the dispatch server provided by the present invention;

[0027] Figure 6 The scheduling server body provided by the present invention is cut away Figure 1 ;

[0028] Figure 7 The scheduling server body provided by the present invention is cut away Figure 2 ;

[0029] Figure 8 The present invention provides Figure 7 Enlarged view of the structure of part A in the middle.

[0030] In the figure: 1. Resource scheduling platform module; 2. Basic facilities module; 3. Resource management module; 4. Intelligent scheduling module; 5. Scheduling monitoring module; 6. Security scheduling control module; 7. Connection module; 8. Resource library management module; 9. Resource registration module; 10. Resource library construction module; 11. Resource status monitoring module; 12. Resource dynamic adjustment module; 13. Scheduling task management module; 14. Efficient scheduling module; 15. Task receiving module; 16. Task parsing module; 17. Resource evaluation module; 18. Task allocation module; 19. Priority scheduling module; 20. Load balancing module; 21. Prediction scheduling module ; 22. Adaptive scheduling module; 23. Identity authentication module; 24. Authority management module; 25. Data encryption module; 26. Security audit module; 27. Scheduling server body; 28. Support column; 29. ​​Support sleeve; 30. Mounting base plate; 31. Anti-theft cover; 32. Box door; 33. Lock; 34. Support plate; 35. Ventilation plate; 36. Threaded rod; 37. Connecting plate; 38. Through groove; 39. Inner cavity; 40. First bevel gear; 41. Second bevel gear; 42. Rotating rod; 43. Fixed plate; 44. Knob; 45. Limit rod; 46. Push block; 47. Card plate; 48. Spring; 49. Card slot. DETAILED DESCRIPTION

[0031] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] See attached Figure 1 -Attached Figure 8 , an artificial intelligence resource scheduling system provided by the present invention comprises a resource scheduling platform module 1, the resource scheduling platform module 1 comprises a basic facility module 2, a resource management module 3, an intelligent scheduling module 4, a scheduling monitoring module 5, a safe scheduling control module 6 and a connection module 7, the resource scheduling platform module 1 is respectively connected with the basic facility module 2, the resource management module 3, the intelligent scheduling module 4, the scheduling monitoring module 5, the safe scheduling control module 6 and the connection module 7;

[0033] In this implementation scheme, the basic infrastructure module 2 includes physical servers, virtualization technology, network equipment, etc., which provide stable computing, storage and network resources for the upper layer. The resource management module 3 is responsible for the abstraction, encapsulation and management of resources. The intelligent scheduling module 4 includes core functions such as task parsing and allocation, scheduling algorithm implementation, etc., and performs intelligent scheduling according to resource status and task requirements. The scheduling monitoring module 5 monitors the system operation status, collects and analyzes log data, and provides a basis for performance optimization and troubleshooting. The secure scheduling control module 6 is responsible for the security and authority control of the system, ensuring data security and compliance. The connection module 7 provides a user interface UI and API interface to facilitate user operation and system integration;

[0034] Among them, in order to achieve the purpose of resource management, the present device is implemented by the following technical solutions: the connection end of the resource management module 3 is provided with a resource library management module 8, the resource library management module 8 includes a resource registration module 9, a resource library construction module 10, a resource status monitoring module 11 and a resource dynamic adjustment module 12, the resource library management module 8 is respectively connected with the resource registration module 9, the resource library construction module 10, the resource status monitoring module 11 and the resource dynamic adjustment module 12 data, the resource library management module 8 is responsible for dynamically monitoring, managing and optimizing computing resources, automatically discovering and registering physical machines, virtual machines, containers and other resources through the resource registration module 9, constructing a logical resource library according to resource type, performance and other attributes through the resource library construction module 10, supporting flexible configuration, real-time monitoring of key indicators such as resource utilization and health status through the resource status monitoring module 11, and automatically adjusting resource allocation according to resource utilization through the resource dynamic adjustment module 12 to improve resource utilization;

[0035] Among them, in order to achieve the purpose of intelligent scheduling, the present device is implemented by the following technical solutions: the intelligent scheduling module 4 includes a scheduling task management module 13 and an efficient scheduling module 14, and the intelligent scheduling module 4 is respectively connected to the scheduling task management module 13 and the efficient scheduling module 14 by data, and the scheduling task management module 13 includes a task receiving module 15, a task parsing module 16, a resource evaluation module 17 and a task allocation module 18, and the scheduling task management module 13 is respectively connected to the task receiving module 15, the task parsing module 16, the resource evaluation module 17 and the task allocation module 18 by data, and the efficient scheduling module 14 includes a priority scheduling module 19, a load balancing module 20, a predictive scheduling module 21 and an adaptive scheduling module 22, and the efficient scheduling module 14 is respectively connected to the priority scheduling module 19, the load balancing module 20, the predictive scheduling module 21 and the adaptive scheduling module 22 by data, through The scheduling task management module 13 receives externally submitted tasks, performs task analysis, and allocates tasks according to task requirements and resource status. The efficient scheduling module 14 adopts a combination of multiple strategies to achieve efficient scheduling. The task receiving module 15 receives task submissions through the user interface. The task analysis module 16 analyzes task requirements, including computing power, memory requirements, GPU requirements, etc. The resource evaluation module 17 evaluates the current resource library status and determines the available resources. The task allocation module 18 allocates tasks to the most suitable resources based on the resource evaluation results and task requirements. The priority scheduling module 19 sorts tasks according to their priorities and gives priority to high-priority tasks. The load balancing module 20 ensures that the load of each node is balanced to avoid resource bottlenecks. The predictive scheduling module 21 plans resource allocation in advance based on historical data and prediction models. The adaptive scheduling module 22 dynamically adjusts the scheduling strategy according to the real-time status of the system.

[0036] Among them, in order to achieve the purpose of safe scheduling, the present device is implemented by the following technical solutions: the safe scheduling control module 6 includes an identity authentication module 23, a permission management module 24, a data encryption module 25 and a security audit module 26, and the safe scheduling control module 6 is respectively connected with the identity authentication module 23, the permission management module 24, the data encryption module 25 and the security audit module 26. The identity authentication module 23 supports multiple identity authentication methods to ensure the authenticity of the user's identity. The permission management module 24 controls the permissions based on roles to limit the user's access to and operation of system resources. The data encryption module 25 encrypts the storage and transmission of sensitive data to prevent data leakage. The security audit module 26 records the user operation log to support security audit and traceability.

[0037] Among them, in order to achieve the purpose of convenient installation and disassembly, the present device is implemented by the following technical solutions: the grassroots facility module 2 includes a dispatching server body 27, a plurality of support columns 28 are fixedly arranged at the bottom of the dispatching server body 27, a through groove 38 is opened on one side of the support column 28, a card plate 47 is arranged inside the through groove 38, two springs 48 are connected between the card plate 47 and the inner wall of the through groove 38, one side of the card plate 47 extends out of the support column 28, an inner cavity 39 is opened inside the dispatching server body 27, a support plate 34 is fixedly arranged at the bottom of the dispatching server body 27, and the top of the support plate 34 is connected to the through groove 38 by a bearing There is a threaded rod 36, which extends into the inner cavity 39 and is connected to the inner wall of the inner cavity 39 through a bearing. A limiting rod 45 is fixedly provided between the support plate 34 and the dispatch server body 27. A connecting plate 37 is provided on the outside of the threaded rod 36 through a threaded sleeve. The limiting rod 45 penetrates the connecting plate 37 and is slidably connected to the connecting plate 37. A plurality of push blocks 46 are fixedly provided on the outside of the connecting plate 37. The push blocks 46 slide in the through groove 38. A first bevel gear 40 is fixedly provided on the outside of the threaded rod 36. A second bevel gear 41 is provided on one side of the first bevel gear 40. The first bevel gear 40 is meshed with the second bevel gear 41. A rotating rod 42 is fixedly provided on one side of the second bevel gear 41, and a knob 44 is fixedly connected to one end of the rotating rod 42. Two fixing plates 43 are fixedly provided inside the inner cavity 39. The rotating rod 42 penetrates the fixing plate 43 and is connected to the fixing plate 43 through a bearing. A mounting base plate 30 is provided at the bottom of the dispatch server body 27, and a plurality of supporting sleeves 29 are fixedly provided on the top of the mounting base plate 30. The supporting column 28 extends into the inside of the supporting sleeve 29, and a card slot 49 is provided on the inner wall of the supporting sleeve 29. The card plate 47 is buckled with the card slot 49. The mounting base plate 30 is installed on the ground, and the support at the bottom of the dispatch server body 27 is fixedly provided. The support column 28 is inserted into the support sleeve 29, and then the knob 44 is turned, the knob 44 drives the rotating rod 42 to rotate, the rotating rod 42 drives the second bevel gear 41 to rotate, the second bevel gear 41 drives the first bevel gear 40 to rotate, the first bevel gear 40 drives the threaded rod 36 to rotate, the threaded rod 36 drives the connecting plate 37 to move downward, the connecting plate 37 drives the push block 46 to move downward, the push block 46 moves downward and pushes the card plate 47 to move, the spring 48 on one side of the card plate 47 is compressed and the card plate 47 moves into the card slot 49, so that the card plate 47 is engaged with the card slot 49, and the support column 28 is fixed inside the support sleeve 29, which is convenient for the installation and disassembly of the scheduling server body 27;

[0038] Among them, in order to achieve the purpose of anti-theft, the present device adopts the following technical solutions: an anti-theft cover 31 is provided on one side of the dispatch server body 27, and a lock 33 is provided on one side of the anti-theft cover 31. The anti-theft cover 31 is locked and fixed by the lock 33, and cannot be opened without a key, thereby preventing the dispatch server body 27 from being disassembled and stolen;

[0039] Among them, in order to achieve the purpose of ventilation, the present device is implemented by adopting the following technical solutions: a box door 32 is provided on one side of the dispatch server body 27, and a ventilation plate 35 is provided on one side of the dispatch server body 27, and the ventilation plate 35 has the function of ventilation and heat dissipation;

[0040] An artificial intelligence resource scheduling method, the specific steps are as follows:

[0041] S1, automatically register physical machines, virtual machines, containers and other resources, build a logical resource library based on resource type, performance and other attributes, monitor key indicators such as resource utilization and health status in real time, and automatically adjust resource allocation based on resource usage;

[0042] S2, receiving task submissions through the user interface, parsing task requirements, evaluating the current resource library status, determining available resources, and assigning tasks to the most appropriate resources based on resource evaluation results and task requirements;

[0043] S3. Sort tasks according to their priority, give priority to high-priority tasks, ensure load balancing of each node, avoid resource bottlenecks, plan resource allocation in advance based on historical data and prediction models, and dynamically adjust scheduling strategies according to the real-time status of the system.

[0044] The use process of the present invention is as follows: When using the present invention,

[0045] The basic infrastructure module 2 includes physical servers, virtualization technology, network equipment, etc., providing stable computing, storage and network resources for the upper layer. The resource management module 3 is responsible for the abstraction, encapsulation and management of resources. The intelligent scheduling module 4 includes core functions such as task parsing and allocation, scheduling algorithm implementation, etc., and performs intelligent scheduling according to resource status and task requirements. The scheduling monitoring module 5 monitors the system operation status, collects and analyzes log data, and provides a basis for performance optimization and troubleshooting. The secure scheduling control module 6 is responsible for the security and authority control of the system to ensure data security and compliance. The connection module 7 provides a user interface UI and API interface to facilitate user operation and system integration. The resource library management module 8 is responsible for dynamically monitoring, managing and optimizing computing resources. It automatically discovers and registers physical machines, virtual machines, containers and other resources through the resource registration module 9. The resource library construction module 10 builds a logical resource library according to resource type, performance and other attributes to support flexible configuration. The resource status monitoring module 11 monitors key indicators such as resource utilization and health status in real time. The resource dynamic adjustment module 12 automatically adjusts resource allocation according to resource usage to improve resource utilization. The scheduling task management module 13 receives externally submitted tasks and performs task parsing. The efficient scheduling module 14 adopts a combination of multiple strategies to achieve efficient scheduling. The task receiving module 15 receives task submissions through the user interface. The task parsing module 16 parses task requirements, including computing capacity, memory requirements, GPU requirements, etc. The resource evaluation module 17 evaluates the current resource library status and determines the available resources. The task allocation module 18 allocates tasks to the most suitable resources according to the resource evaluation results and task requirements. The priority scheduling module 19 sorts tasks according to their priorities and gives priority to high-priority tasks. The load balancing module 20 ensures that the load of each node is balanced to avoid resource bottlenecks. The predictive scheduling module 21 plans resource allocation in advance based on historical data and predictive models. The adaptive scheduling module 22 dynamically adjusts the scheduling strategy according to the real-time status of the system. The identity authentication module 23 supports multiple identity authentication methods to ensure the authenticity of the user identity. The authority management module 24 controls the authority based on roles to limit the user's access and operation to system resources. The data encryption module 25 encrypts the storage and transmission of sensitive data to prevent data leakage. The security audit module 26 records user operation logs to support security auditing and tracing.

[0046] The mounting base plate 30 is mounted on the ground, the support column 28 at the bottom of the scheduling server body 27 is inserted into the support sleeve 29, and then the knob 44 is turned, the knob 44 drives the rotating rod 42 to rotate, the rotating rod 42 drives the second bevel gear 41 to rotate, the second bevel gear 41 drives the first bevel gear 40 to rotate, the first bevel gear 40 drives the threaded rod 36 to rotate, the threaded rod 36 drives the connecting plate 37 to move downward, the connecting plate 37 drives the push block 46 to move downward, the push block 46 moves downward and pushes the card plate 47 to move, the spring 48 on one side of the card plate 47 is compressed and the card plate 47 moves into the card slot 49, so that the card plate 47 is engaged with the card slot 49, the support column 28 is fixed inside the support sleeve 29, which is convenient for the installation and disassembly of the scheduling server body 27, the anti-theft cover 31 is locked and fixed by the lock 33, and it cannot be opened without a key, so as to prevent the scheduling server body 27 from being disassembled and stolen, and the ventilation plate 35 has a ventilation function.

[0047] The above is only a preferred embodiment of the present invention. Any person skilled in the art may modify the present invention by using the above technical solution or modify it into an equivalent technical solution. Therefore, any simple modification or equivalent replacement made according to the technical solution of the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. An artificial intelligence resource scheduling system, comprising a resource scheduling platform module (1), characterized in that: The resource scheduling platform module (1) comprises a basic facility module (2), a resource management module (3), an intelligent scheduling module (4), a scheduling monitoring module (5), a safe scheduling control module (6) and a connection module (7). The resource scheduling platform module (1) is respectively connected to the basic facility module (2), the resource management module (3), the intelligent scheduling module (4), the scheduling monitoring module (5), the safe scheduling control module (6) and the connection module (7) in data connection.

2. An artificial intelligence resource scheduling system according to claim 1, characterized in that: The resource management module (3) is provided with a resource library management module (8) at a connection end. The resource library management module (8) comprises a resource registration module (9), a resource library construction module (10), a resource status monitoring module (11) and a resource dynamic adjustment module (12). The resource library management module (8) is respectively data-connected to the resource registration module (9), the resource library construction module (10), the resource status monitoring module (11) and the resource dynamic adjustment module (12).

3. The artificial intelligence resource scheduling system according to claim 1, characterized in that: The intelligent scheduling module (4) comprises a scheduling task management module (13) and an efficient scheduling module (14), and the intelligent scheduling module (4) is respectively connected to the scheduling task management module (13) and the efficient scheduling module (14) in data connection, the scheduling task management module (13) comprises a task receiving module (15), a task parsing module (16), a resource evaluation module (17) and a task allocation module (18), and the scheduling task management module (13) is respectively connected to the task receiving module (15), the task parsing module (16), the resource evaluation module (17) and the task allocation module (18), and the efficient scheduling module (14) comprises a priority scheduling module (19), a load balancing module (20), a prediction scheduling module (21) and an adaptive scheduling module (22), and the efficient scheduling module (14) is respectively connected to the priority scheduling module (19), the load balancing module (20), the prediction scheduling module (21) and the adaptive scheduling module (22).

4. The artificial intelligence resource scheduling system according to claim 1, characterized in that: The security scheduling control module (6) comprises an identity authentication module (23), a rights management module (24), a data encryption module (25) and a security audit module (26), and the security scheduling control module (6) is respectively connected to the identity authentication module (23), the rights management module (24), the data encryption module (25) and the security audit module (26).

5. The artificial intelligence resource scheduling system according to claim 1, characterized in that: The basic facility module (2) comprises a dispatching server body (27), a plurality of support columns (28) are fixedly provided at the bottom of the dispatching server body (27), a through slot (38) is provided on one side of the support column (28), a card plate (47) is provided inside the through slot (38), two springs (48) are connected between the card plate (47) and the inner wall of the through slot (38), one side of the card plate (47) extends out of the support column (28), an inner cavity (39) is provided inside the dispatching server body (27), a support plate (34) is fixedly provided at the bottom of the dispatching server body (27), a threaded rod (36) is connected to the top of the support plate (34) through a bearing, the threaded rod (36) extends into the inner cavity (39) and is connected to the inner wall of the inner cavity (39) through a bearing, a limiting spring (36) is fixedly provided between the support plate (34) and the dispatching server body (27). A positioning rod (45) is provided on the outside of the threaded rod (36) through a threaded sleeve, a connecting plate (37) is provided on the outside of the threaded rod (36), the limiting rod (45) penetrates the connecting plate (37) and is slidably connected to the connecting plate (37), a plurality of push blocks (46) are fixedly provided on the outside of the connecting plate (37), and the push blocks (46) slide inside the through groove (38), a first bevel gear (40) is fixedly sleeved on the outside of the threaded rod (36), a second bevel gear (41) is provided on one side of the first bevel gear (40), the first bevel gear (40) is meshed with the second bevel gear (41), a rotating rod (42) is fixedly provided on one side of the second bevel gear (41), one end of the rotating rod (42) is fixedly connected to a knob (44), two fixed plates (43) are fixedly provided inside the inner cavity (39), the rotating rod (42) penetrates the fixed plate (43) and is connected to the fixed plate (43) through a bearing.

6. An artificial intelligence resource scheduling system according to claim 5, characterized in that: The dispatch server body (27) has a mounting base plate (30) at the bottom, a plurality of support sleeves (29) are fixedly provided on the top of the mounting base plate (30), the support column (28) extends into the interior of the support sleeve (29), a card slot (49) is provided on the inner wall of the support sleeve (29), and the card plate (47) is engaged with the card slot (49).

7. The artificial intelligence resource scheduling system according to claim 5, characterized in that: A theft-proof cover (31) is provided on one side of the dispatch server body (27), and a lock (33) is provided on one side of the theft-proof cover (31).

8. The artificial intelligence resource scheduling system according to claim 5, characterized in that: A box door (32) is provided on one side of the dispatch server body (27), and a ventilation plate (35) is provided on one side of the dispatch server body (27).

9. An artificial intelligence resource scheduling method, characterized in that: The specific steps are as follows: S1, automatically register physical machines, virtual machines, containers and other resources, build a logical resource library based on resource type, performance and other attributes, monitor key indicators such as resource utilization and health status in real time, and automatically adjust resource allocation based on resource usage; S2, receiving task submissions through the user interface, parsing task requirements, evaluating the current resource library status, determining available resources, and assigning tasks to the most appropriate resources based on resource evaluation results and task requirements; S3. Sort tasks according to their priority, give priority to high-priority tasks, ensure load balancing of each node, avoid resource bottlenecks, plan resource allocation in advance based on historical data and prediction models, and dynamically adjust scheduling strategies according to the real-time status of the system.

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