Intelligent scheduling and management system for computing resources

Abstract

The present invention discloses an intelligent scheduling and management system for computing power resources, which relates to the field of computers and includes: a monitoring module for collecting computing power resource application information of computer equipment in real time, and monitoring computing power application risks of computer equipment based on the computing power resource application information; a scheduling module for analyzing the activity and importance of running programs on computer equipment, selecting running programs as computing power resource scheduling targets based on the activity and importance of running programs, and executing scheduling operations; the present invention can collect computing power resource application information of computer equipment in real time and monitor risks, and analyze program activity and importance, and reasonably select scheduling targets for scheduling. At the same time, it predicts a computing power shortage index and triggers scheduling operations in a timely manner according to the prediction results. The system can timely adjust the computing power resources occupied by program running to avoid insufficient computing power, thereby ensuring that the system has relatively sufficient computing power resources in real time and improving the operating efficiency of computer equipment.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to an intelligent scheduling and management system for computing resources. Background Art

[0002] Computing resource scheduling is a key operating mechanism in the intelligent era. It flexibly allocates the computing power of various computing devices based on factors such as task requirements and computing node status. It can break down complex computing tasks and accurately match them to the most appropriate server, cluster or cloud computing power, thereby achieving efficient resource utilization, reducing costs, and significantly improving computing efficiency.

[0003] The invention patent application with application number 202411864033.0 discloses an intelligent computing resource scheduling and optimization system, including a monitoring and acquisition module, a scheduling and allocation module, an optimization prediction module and a task management module. The monitoring and acquisition module is used to collect and monitor the operation data of computing resources. The scheduling and allocation module dynamically schedules computing resources based on task requirements. The optimization prediction module predicts resource requirements based on historical data and optimizes resource allocation. The task management module is used to manage user task information. The monitoring and acquisition module includes a hardware monitoring unit, a resource acquisition unit and a transmission control unit. The hardware monitoring unit is used to monitor computing resources. The hardware status information of the node, the resource acquisition unit is used to collect the resource usage of the task, the transmission control unit is used to control the external transmission of the monitoring and acquisition data, the scheduling and allocation module includes a resource allocation unit, a task scheduling unit and a strategy selection unit, the resource allocation unit is used to calculate the amount of resources allocated to each task, the task scheduling unit schedules the task to the corresponding node based on the allocated resource amount, and the strategy selection unit is used to select the scheduling strategy applied by the task scheduling unit. This application aims to solve the problem that "the existing technology cannot predict the changes in the resource requirements of the task, resulting in a lag in the scheduling of resources and the overall operational efficiency of the system needs to be improved."

[0004] However, relying solely on computing power resource prediction is obviously unable to absolutely meet the real-time and irregular computing power resource needs.

[0005] To this end, we propose an intelligent scheduling and management system for computing resources. Summary of the Invention

[0006] In response to the above-mentioned shortcomings of the prior art, the present invention provides an intelligent scheduling and management system for computing resources, which can effectively solve the problems of the prior art.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] The present invention discloses an intelligent scheduling and management system for computing resources, comprising:

[0009] The monitoring module is used to collect computer equipment computing power resource application information in real time and monitor the computing power application risk of computer equipment based on the computing power resource application information; the scheduling module is used to analyze the activity and importance of running programs on computer equipment, select running programs as computing power resource scheduling targets based on the activity and importance of running programs, and perform scheduling operations; the prediction module is used to obtain the computer equipment computing power application risk monitored by the monitoring module in real time, and predict the computer equipment computing power shortage index based on the computer equipment computing power application risk; the trigger module is used to obtain the computer equipment computing power shortage index prediction result in the prediction module, trigger a jump based on the prediction result, and jump to the scheduling module operation stage; the interaction module is used to obtain the trigger module operation trigger result in real time. After the trigger jump, the scheduling module operation stage synchronously issues an interactive pop-up window on the display connected to the computer equipment; the feedback module is used to generate system operation messages and synchronously upload the operation messages to the preset cloud storage space:

[0010] Furthermore, the computing power resource application information collected by the monitoring module is the programs currently running on the computer device and the memory occupied by each running program. The monitoring module is provided with a control unit and a storage unit at the lower level. The control unit is used to sense in real time whether there is a new program actively running or actively ending on the computer device. When the sensing result is yes, the monitoring module is triggered to refresh and run again, and the computer device computing power application risk monitoring operation is performed again. The storage unit is used to receive the computer device computing power resource application information collected by the monitoring module and store the application information.

[0011] Among them, the operation of collecting computer equipment computing power resource application information in the monitoring module is executed in real time by the user-defined frequency on the system side, and the frequency is initially set to 1 second / time. When the storage unit stores the computer equipment computing power resource application information, it is stored separately based on the source application of the computing power resource application information, and each computing power resource application information is marked with a collection timestamp, and the computing power resource application information stored in each differentiated storage interval is sorted based on the marked collection timestamp.

[0012] Furthermore, the monitoring module records the computer equipment computing power application risks monitored during historical operations. The monitoring logic of the computer equipment computing power application risks is as follows:

[0013]

[0014] Where: K is the computing power utilization ratio of the computer device; n is the total number of programs currently running on the computer device; Q i The memory occupied by the i-th running program; Q MAX is the maximum available memory of the computer device; σ is the correction;

[0015] in, Q min The memory required for the program that is not currently running and requires the least memory to run among the programs loaded on the computer device is 1. If any one or more of formula (1) and formula (2) are true, it means that there is a risk in the application of the computing power of the computer device. If both formula (1) and formula (2) are false, it means that there is no risk in the application of the computing power of the computer device.

[0016] Furthermore, the value of the modified σ obeys:

[0017] Obtain historical computing power resource application information of computer equipment, obtain current computing power resource application information of computer equipment, apply the programs contained in each historical computing power resource application information and the current computing power resource application information to create several data sets, and the data sets derived from the historical computing power resource application information are recorded as A1, A2, A3, ..., A x ,The dataset derived from the current computing resource application information is denoted as B;

[0018] In A1, A2, A3, ..., A x Get the intersection correspondence program, create a set based on the intersection correspondence program and record it as A'. When the intersection A' is an empty set, select A1, A2, A3, ..., A x Create a set of three or more programs that appear the most times, denoted as A′;

[0019]

[0020] Where: s is the reference value; q(B∩A′) is the total number of programs in the intersection; q(B∪A)′ is the total number of programs in the union;

[0021] The correction σ is in the range of 0 to 1, and the reference value s is inversely proportional to the correction σ.

[0022] Furthermore, the activity and importance analysis logic of the programs running on the computer device in the scheduling module is expressed as follows:

[0023]

[0024] Where: F(α1) is the recommendation index when running program α1 is selected as the computing resource scheduling target; pα1 is the number of times running program α1 is run in the historical computing resource application information; p all The number of historical computing resource application information; t j t is the running time of program α1 when it runs for the jth time; max , t min is the longest and shortest continuous running time of program α1 in the historical computing resource application information; QMAX ′、Q MIN ′ is the maximum and minimum running memory occupied by running program α1 in the historical computing resource application information; Q j is the average memory usage of program α1 during its j-th run, measured in seconds; γ is the normalization factor;

[0025] in, Express The averaging operation, Express The average operation is based on the above calculation formula. Each running program is sorted in descending order based on the recommendation index, and the last running program in the descending order is selected as the computing resource scheduling target. They are used to indicate the activity and importance of running programs respectively.

[0026] Furthermore, the prediction logic of the computer computing power shortage index in the prediction module is:

[0027]

[0028] Where: EL is the computer computing power shortage index; u is the historical utilization ratio of computer equipment computing power; K v+1 , K v is the ratio of computing power utilization of computer equipment obtained at the v+1th and vth times; n is the total number of programs currently running on the computer; f(P i,ass ) is the decision function; P i,ass is the result of determining whether the highest correlation program of the i-th program is in n;

[0029] Among them, f(P i,ass ) takes the value of 0 or 1, and the highest correlation program of the i-th program is in n, then f(P i,ass )=0, otherwise f(P i,ass )=1, the larger the EL is, the more scarce the computer computing power is.

[0030] Furthermore, during the operation phase of the trigger module, the latest two prediction results of the computing power shortage index of the prediction module are accumulated and recorded as EL based on the acquisition order. before EL now , EL now >EL before , then the jump is triggered, otherwise, the jump is not triggered;

[0031] Among them, after each operation of the trigger module is completed, it is recorded as EL before The deletion of now reserve.

[0032] Furthermore, the interactive pop-up window content issued by the interactive module is customized by the system end user, and is used to prompt the computer device user that the computer device is about to perform a computing resource scheduling operation based on the scheduling module;

[0033] Among them, the interactive pop-up window issued on the display connected to the computer device is manually canceled by the user. After the interactive pop-up window is canceled, the running program clicked by the user for the first time on the computer device is excluded from the selection targets of the computing power resource scheduling target in the selection stage.

[0034] Furthermore, the system operation message content includes: computer equipment computing power application risk monitoring results, computer equipment computing power shortage index prediction results, trigger module trigger jump times, and the cumulative number of programs selected as computing power resource scheduling targets by the scheduling module;

[0035] Among them, the system end user or computer device user downloads and reads the system operation message in the cloud storage space.

[0036] Furthermore, the monitoring module is interactively connected to a control unit and a storage unit at the lower level through a wireless network, the monitoring module is interactively connected to a prediction module and a scheduling module through a wireless network, the prediction module is interactively connected to a trigger module and an interaction module through a wireless network, the scheduling module is interactively connected to a feedback module through a wireless network, and the trigger module is interactively connected to the scheduling module through a wireless network.

[0037] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0038] The system in the present invention can collect computer equipment computing power resource application information in real time and monitor risks, analyze program activity and importance, and reasonably select scheduling targets for scheduling. At the same time, it predicts the computing power shortage index and triggers scheduling operations in time according to the prediction results. It will also prompt the user through a pop-up window. The system will run synchronously to generate messages to record relevant key information for user convenience. Through these functions, the system can adjust the computing power resources occupied by program operation in time to avoid insufficient computing power, thereby ensuring that the system has relatively sufficient computing power resources in real time and improving the operating efficiency of computer equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0040] Figure 1 This is a structural diagram of the intelligent scheduling and management system for computing resources. DETAILED DESCRIPTION

[0041] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 making creative efforts are within the scope of protection of the present invention.

[0042] The present invention will be further described below with reference to the embodiments.

[0043] Example:

[0044] The computing power resource intelligent scheduling and management system of this embodiment is as follows: Figure 1 Shown, including:

[0045] A monitoring module is used to collect computing power resource application information of computer equipment in real time and monitor computing power application risks of computer equipment based on the computing power resource application information;

[0046] The computing power resource application information collected by the monitoring module is the programs currently running on the computer device and the memory occupied by each running program. The monitoring module is provided with a control unit and a storage unit at the lower level. The control unit is used to sense in real time whether there is a new program actively running or actively ending on the computer device. When the perception result is yes, it triggers the monitoring module to refresh and run again, and execute the computer device computing power application risk monitoring operation again. The storage unit is used to receive the computer device computing power resource application information collected by the monitoring module and store the application information;

[0047] The operation of collecting computer equipment computing power resource application information in the monitoring module is executed in real time at a user-defined frequency on the system side. The frequency is initially set to 1 second / time. When the storage unit stores the computer equipment computing power resource application information, it is stored separately based on the source application of the computing power resource application information. Each computing power resource application information is marked with a collection timestamp, and the computing power resource application information stored in each differentiated storage interval is sorted based on the marked collection timestamp.

[0048] The monitoring module records the computing power application risks of computer equipment detected during historical operation. The monitoring logic for computing power application risks of computer equipment is as follows:

[0049]

[0050] Where: K is the computing power utilization ratio of the computer device; n is the total number of programs currently running on the computer device; Qi The memory occupied by the i-th running program; Q MAX is the maximum available memory of the computer device; σ is the correction;

[0051] in, Q min is the memory required for the program that is not currently running and requires the least memory to run among the programs loaded on the computer device. If any one or more of formula (1) and formula (2) are true, it means that there is a risk in the application of the computing power of the computer device. If both formula (1) and formula (2) are false, it means that there is no risk in the application of the computing power of the computer device.

[0052] The above logical formula is used to calculate the proportion of computing power application of computer equipment, thereby providing support for whether there are risks in the computing power application of computer equipment.

[0053] The modified σ value obeys:

[0054] Obtain historical computing power resource application information of computer equipment, obtain current computing power resource application information of computer equipment, apply the programs contained in each historical computing power resource application information and the current computing power resource application information to create several data sets, and the data sets derived from the historical computing power resource application information are recorded as A1, A2, A3, ..., A x ,The dataset derived from the current computing resource application information is denoted as B;

[0055] In A1, A2, A3, ..., A x Get the intersection correspondence program, create a set based on the intersection correspondence program and record it as A'. When the intersection A' is an empty set, select A1, A2, A3, ..., A x Create a set of three or more programs that appear the most times, denoted as A′;

[0056]

[0057] Where: s is the reference value; q(B∩A′) is the total number of programs in the intersection; q(B∪A)′ is the total number of programs in the union;

[0058] Among them, the correction σ value is in the range of 0 to 1, and the reference value s is inversely proportional to the correction σ;

[0059] Through the above logic, the value of the correction σ is constrained.

[0060] The scheduling module is used to analyze the activity and importance of running programs on the computer device, select running programs as computing resource scheduling targets based on the activity and importance of the running programs, and perform scheduling operations;

[0061] The activity and importance analysis logic of the programs running on the computer devices in the scheduling module is expressed as follows:

[0062]

[0063] Where: F(α1) is the recommendation index when running program α1 is selected as the computing resource scheduling target; pα1 is the number of times running program α1 is run in the historical computing resource application information; p all The number of historical computing resource application information; t j t is the running time of program α1 when it runs for the jth time; max , t min is the longest and shortest continuous running time of program α1 in the historical computing resource application information; Q MAX ′、Q MIN ′ is the maximum and minimum running memory occupied by running program α1 in the historical computing resource application information; Q j is the average memory usage of program α1 during its j-th run, measured in seconds; γ is the normalization factor;

[0064] in, Express The averaging operation, Express The average operation is based on the above calculation formula. Each running program is sorted in descending order based on the recommendation index, and the last running program in the descending order is selected as the computing resource scheduling target. They are used to indicate the activity and importance of running programs respectively;

[0065] The above logical formula provides a basis for selecting running programs as computing resource scheduling targets, thereby accurately realizing the selection of running programs as computing resource scheduling targets.

[0066] A prediction module is used to obtain in real time the computing power application risk of the computer equipment monitored by the monitoring module, and predict the computing power shortage index of the computer equipment based on the computing power application risk of the computer equipment;

[0067] The prediction logic of the computer computing power shortage index in the prediction module is:

[0068]

[0069] Where: EL is the computer computing power shortage index; u is the historical utilization ratio of computer equipment computing power; K v+1 , K v is the ratio of computing power utilization of computer equipment obtained at the v+1th and vth times; n is the total number of programs currently running on the computer; f(P i,ass) is the decision function; P i,ass is the result of determining whether the highest correlation program of the i-th program is in n;

[0070] Among them, f(P i,ass ) takes the value of 0 or 1, and the highest correlation program of the i-th program is in n, then f(P i,ass )=0, otherwise f(P i,ass )=1, the larger the EL, the more scarce the computer computing power;

[0071] The calculation by the above logic formula provides further operation support for the trigger module operation of the system in this embodiment.

[0072] The trigger module is used to obtain the prediction results of the computing power shortage index of computer equipment in the prediction module, trigger a jump based on the prediction results, and jump to the operation phase of the scheduling module;

[0073] During the trigger module operation phase, the latest two prediction results of the computer equipment computing power shortage index of the prediction module are accumulated and recorded as EL based on the acquisition order. before EL now , EL now >EL before , then the jump is triggered, otherwise, the jump is not triggered;

[0074] Among them, after each operation of the trigger module is completed, it is recorded as EL before The deletion of now reserve;

[0075] The interactive module is used to obtain the triggering results of the triggering module in real time. After the trigger jump, the scheduling module will send an interactive pop-up window on the display connected to the computer device during the operation phase;

[0076] The interactive pop-up window issued by the interactive module is customized by the system user and is used to remind the computer device user that the computer device is about to perform computing resource scheduling operations based on the scheduling module.

[0077] The interactive pop-up window displayed on the display connected to the computer device is manually canceled by the user. After the interactive pop-up window is canceled, the running program that the user clicks on the computer device for the first time is excluded from the selection targets in the computing power resource scheduling target selection phase;

[0078] Feedback module, used to generate system operation messages and simultaneously upload the operation messages to the preset cloud storage space;

[0079] The system operation message content includes: computer equipment computing power application risk monitoring results, computer equipment computing power shortage index prediction results, trigger module trigger jump times, and the cumulative number of programs selected as computing power resource scheduling targets by the scheduling module;

[0080] Among them, the system end user or computer device user downloads and reads the system operation message in the cloud storage space;

[0081] The monitoring module is interactively connected to the control unit and the storage unit at the lower level through a wireless network, the monitoring module is interactively connected to the prediction module and the scheduling module through a wireless network, the prediction module is interactively connected to the trigger module and the interaction module through a wireless network, the scheduling module is interactively connected to the feedback module through a wireless network, and the trigger module is interactively connected to the scheduling module through a wireless network.

[0082] In this embodiment, the monitoring module collects computer equipment computing power resource application information in real time, monitors the computer equipment computing power application risk based on the computing power resource application information, and the control unit senses in real time whether there is a new program actively running or actively ending on the computer equipment. When the perception result is yes, the monitoring module is triggered to refresh and run, and the computer equipment computing power application risk monitoring operation is executed again. The storage unit synchronously receives the computer equipment computing power resource application information collected by the monitoring module and stores the application information. The scheduling module is post-operated to analyze the activity and importance of the running program on the computer equipment, and selects the running program based on the activity and importance of the running program. In order to achieve the computing power resource scheduling goal, the scheduling operation is executed. The prediction module obtains the computing power application risk of the computer equipment monitored by the monitoring module in real time, and predicts the computing power shortage index of the computer equipment based on the computing power application risk of the computer equipment. The trigger module further obtains the prediction result of the computer equipment computing power shortage index in the prediction module, triggers the jump based on the prediction result, and jumps to the scheduling module operation stage. The interaction module obtains the trigger result of the trigger module operation in real time. After the trigger jump, the scheduling module operation stage synchronously issues an interactive pop-up window on the display connected to the computer equipment. Finally, the system operation message is generated through the feedback module, and the operation message is synchronously uploaded to the preset cloud storage space.

[0083] By running the system in the above embodiment, the computer device can be ensured to have as much computing power resources as possible available in real time to ensure stable operation of the computer device, making the computer device run more stably and providing a better user experience.

[0084] In summary, in the above embodiment, the system can collect computer equipment computing power resource application information in real time and monitor risks, analyze program activity and importance, and reasonably select scheduling targets for scheduling. At the same time, it predicts the computing power shortage index, triggers scheduling operations in a timely manner according to the prediction results, and prompts the user through a pop-up window. The system synchronously runs and generates messages to record relevant key information for user convenience. Through these functions, the system can adjust the computing power resources occupied by program operation in a timely manner to avoid insufficient computing power, thereby ensuring that the system has relatively sufficient computing power resources in real time and improving the operating efficiency of computer equipment.

[0085] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. 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 make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. Intelligent scheduling and management system for computing resources, characterized by: include: A monitoring module is used to collect computing power resource application information of computer equipment in real time and monitor computing power application risks of computer equipment based on the computing power resource application information; The scheduling module is used to analyze the activity and importance of running programs on the computer device, select running programs as computing resource scheduling targets based on the activity and importance of the running programs, and perform scheduling operations; A prediction module is used to obtain in real time the computing power application risk of the computer equipment monitored by the monitoring module, and predict the computing power shortage index of the computer equipment based on the computing power application risk of the computer equipment; The trigger module is used to obtain the prediction results of the computing power shortage index of computer equipment in the prediction module, trigger a jump based on the prediction results, and jump to the operation phase of the scheduling module; The interactive module is used to obtain the triggering results of the triggering module in real time. After the trigger jump, the scheduling module will send an interactive pop-up window on the display connected to the computer device during the operation phase; The feedback module is used to generate system operation messages and simultaneously upload the operation messages to the preset cloud storage space.

2. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: The computing power resource application information collected by the monitoring module is the programs currently running on the computer device and the memory occupied by each running program. The monitoring module is provided with a control unit and a storage unit at the lower level. The control unit is used to sense in real time whether there is a new program actively running or actively ending on the computer device. When the perception result is yes, the monitoring module is triggered to refresh and run again, and the computer device computing power application risk monitoring operation is performed again. The storage unit is used to receive the computer device computing power resource application information collected by the monitoring module and store the application information; Among them, the operation of collecting computer equipment computing power resource application information in the monitoring module is executed in real time by the user-defined frequency on the system side, and the frequency is initially set to 1 second / time. When the storage unit stores the computer equipment computing power resource application information, it is stored separately based on the source application of the computing power resource application information, and each computing power resource application information is marked with a collection timestamp, and the computing power resource application information stored in each differentiated storage interval is sorted based on the marked collection timestamp.

3. The intelligent scheduling and management system for computing resources according to claim 2, characterized in that: The monitoring module records the computer equipment computing power application risks monitored in historical operations. The monitoring logic of the computer equipment computing power application risks is as follows: Where: K is the computing power utilization ratio of the computer device; n is the total number of programs currently running on the computer device; Q i The memory occupied by the i-th running program; Q MAX is the maximum available memory of the computer device; σ is the correction; in, Q min The memory required for the program that is not currently running and requires the least memory to run among the programs loaded on the computer device is 1. If any one or more of formula (1) and formula (2) are true, it means that there is a risk in the application of the computing power of the computer device. If both formula (1) and formula (2) are false, it means that there is no risk in the application of the computing power of the computer device.

4. The intelligent scheduling and management system for computing resources according to claim 3 is characterized in that: The modified σ value is subject to: Obtain historical computing power resource application information of computer equipment, obtain current computing power resource application information of computer equipment, apply the programs contained in each historical computing power resource application information and the current computing power resource application information to create several data sets, and the data sets derived from the historical computing power resource application information are recorded as A1, A2, A3, ..., A x ,The dataset derived from the current computing resource application information is denoted as B; In A1, A2, A3, ..., A x Get the intersection correspondence program, create a set based on the intersection correspondence program and record it as A'. When the intersection A' is an empty set, select A1, A2, A3, ..., A x Create a set of three or more programs that appear the most times, denoted as A′; Where: s is the reference value; q(B∩A′) is the total number of programs in the intersection; q(B∪A)′ is the total number of programs in the union; The correction σ is in the range of 0 to 1, and the reference value s is inversely proportional to the correction σ.

5. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: The activity and importance analysis logic of the programs running on the computer device in the scheduling module is expressed as follows: Where: F(α1) is the recommendation index when running program α1 is selected as the computing resource scheduling target; is the number of times the program α1 is run in the historical computing resource application information; p all The number of historical computing resource application information; t j The duration of running program α1 when it runs for the jth time; t max , t min is the longest and shortest continuous running time of program α1 in the historical computing resource application information; Q MAX ′、Q MIN ′ is the maximum and minimum running memory occupied by running program α1 in the historical computing resource application information; Q j is the average memory usage of program α1 during its j-th run, measured in seconds; γ is the normalization factor; in, Express The averaging operation, Express The average operation is based on the above calculation formula. Each running program is sorted in descending order based on the recommendation index, and the last running program in the descending order is selected as the computing resource scheduling target. They are used to indicate the activity and importance of running programs respectively.

6. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: The prediction logic of the computer computing power shortage index in the prediction module is: Where: EL is the computer computing power shortage index; u is the historical utilization ratio of computer equipment computing power; K v+1 , K v is the ratio of computing power utilization of computer equipment obtained at the v+1th and vth times; n is the total number of programs currently running on the computer; f(P i,ass ) is the decision function; P i,ass is the result of determining whether the highest correlation program of the i-th program is in n; Among them, f(P i,ass ) takes the value of 0 or 1, and the highest correlation program of the i-th program is in n, then f(P i,ass )=0, otherwise f(P i,ass )=1, the larger the EL is, the more scarce the computer computing power is.

7. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: During the trigger module operation phase, the latest two prediction results of the computer equipment computing power shortage index of the prediction module are accumulated and recorded as EL based on the acquisition order. before EL now , EL now >EL before , then the jump is triggered, otherwise, the jump is not triggered; Among them, after each operation of the trigger module is completed, it is recorded as EL before The deletion of now reserve.

8. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: The interactive pop-up window issued by the interactive module is customized by the system user and is used to remind the computer device user that the computer device is about to perform a computing resource scheduling operation based on the scheduling module; Among them, the interactive pop-up window issued on the display connected to the computer device is manually canceled by the user. After the interactive pop-up window is canceled, the running program clicked by the user for the first time on the computer device is excluded from the selection targets of the computing power resource scheduling target in the selection stage.

9. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: The system operation message content includes: computer equipment computing power application risk monitoring results, computer equipment computing power shortage index prediction results, trigger module trigger jump times, and the cumulative number of programs selected as computing power resource scheduling targets by the scheduling module; Among them, the system end user or computer device user downloads and reads the system operation message in the cloud storage space.

10. The intelligent scheduling and management system for computing resources according to claim 1, characterized in that: The monitoring module is interactively connected to a control unit and a storage unit at the lower level through a wireless network, the monitoring module is interactively connected to a prediction module and a scheduling module through a wireless network, the prediction module is interactively connected to a trigger module and an interaction module through a wireless network, the scheduling module is interactively connected to a feedback module through a wireless network, and the trigger module is interactively connected to the scheduling module through a wireless network.

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