Computer software and hardware intelligent interaction system and method

Abstract

The invention relates to the technical field of computer intelligent interaction, and provides a computer software and hardware intelligent interaction system and method, an operation priority calculation module is used for obtaining to-be-operated data input into a computer, evaluating a data emergency situation corresponding to the to-be-operated data and setting an operation priority corresponding to the to-be-operated data; the resource screening module is used for screening computing resources of the data to be operated from the software and hardware resources; the data response delay calculation module is used for collecting resource parameters corresponding to the calculation resources and calculating data response delay of the to-be-calculated data in the calculation resources; the collaborative efficiency calculation module is used for analyzing and calculating resource attributes corresponding to the resources, performing resource combination on the interactive resources to obtain combined interactive resources, and calculating resource collaborative efficiency among the combined interactive resources; and the interactive processing module is used for executing interactive calculation processing of the to-be-calculated data by utilizing the combined interactive resources to obtain a processing result. The intelligent interaction efficiency of computer software and hardware is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer intelligent interaction technology, and in particular to a computer software and hardware intelligent interaction system and method. Background Art

[0002] A computer refers to an electronic computer, which is a modern intelligent device that can store, process and output data according to pre-set programs. It consists of two major parts: hardware and software. The hardware includes components such as the central processing unit (CPU), memory, and hard disk, while the software includes operating systems, applications, etc. These hardware and software work together to provide a physical basis for the operation of the computer.

[0003] The existing intelligent interaction of computer software and hardware adopts predefined rules for interaction. The interaction process is as follows: developers or system administrators set a series of detailed rules in advance based on experience, hardware specifications and software requirements. These rules cover various possible situations and conditions, continuously monitor the status of the computer system, match and compare the monitored system status with the predefined rules, and judge whether the current system status meets the conditions set by a certain rule. If the monitored status meets the conditions of a certain rule, the corresponding interaction operation is performed according to the action specified by the rule. However, the predefined rules in this method have limitations and cannot fully explore and utilize the potential performance and resources of computer software and hardware, resulting in resource waste or performance bottlenecks, which in turn leads to low interaction efficiency of computer software and hardware. Summary of the invention

[0004] The present invention provides a computer software and hardware intelligent interaction system and method, the main purpose of which is to improve the intelligent interaction efficiency of computer software and hardware.

[0005] To achieve the above-mentioned purpose, the present invention provides a computer software and hardware intelligent interaction system, comprising: an operation priority calculation module, a resource screening module, a response delay calculation module, a collaborative efficiency calculation module, and an interaction processing module;

[0006] The operation priority calculation module is used to obtain the data to be operated input into the computer, evaluate the data emergency situation corresponding to the data to be operated, and query the operation task corresponding to the data to be operated, and set the operation priority corresponding to the data to be operated in combination with the data emergency situation and the operation task;

[0007] The resource screening module is used to schedule the software and hardware resources in the computer for processing the data to be calculated, and collect resource load data corresponding to the software and hardware resources, calculate the resource computing energy efficiency corresponding to the software and hardware resources according to the resource load data, and screen the computing resources for the data to be calculated from the software and hardware resources according to the resource computing energy efficiency;

[0008] The data response delay calculation module is used to collect resource parameters corresponding to the computing resources, and calculate the data response delay of the data to be calculated in the computing resources according to the resource parameters;

[0009] The collaborative efficiency calculation module is used to analyze the resource attributes corresponding to the computing resources, determine the interactive resources in the computing resources according to the resource attributes, combine the interactive resources in combination with the data response delay to obtain combined interactive resources, and calculate the resource collaborative efficiency between the combined interactive resources in combination with the data response delay;

[0010] The interactive processing module is used to combine the data to be calculated, the calculation priority and the resource coordination efficiency, and use the combined interactive resources to perform interactive calculation processing on the data to be calculated to obtain a processing result.

[0011] Optionally, the evaluating the data emergency situation corresponding to the data to be calculated includes:

[0012] Identify the input timestamp when the data to be calculated is input into the computer, and query the deadline timestamp corresponding to the data to be calculated;

[0013] Calculate the time margin corresponding to the data to be calculated by combining the input timestamp and the deadline timestamp;

[0014] Calculating the data importance corresponding to the data to be calculated;

[0015] The data emergency situation corresponding to the data to be calculated is evaluated in combination with the time margin and the data importance.

[0016] Optionally, the step of setting a computing priority corresponding to the data to be computed in combination with the data emergency situation and the computing task includes:

[0017] Extracting a data identifier corresponding to the data to be calculated, and calculating an identifier weight corresponding to the data identifier;

[0018] extracting a key identifier from the data identifier according to the identifier weight;

[0019] Decomposing the computing task to obtain decomposed tasks, and analyzing the task objectives corresponding to the decomposed tasks;

[0020] Calculating a matching coefficient between the task target and the key identifier;

[0021] The operation priority corresponding to the data to be operated is set according to the matching coefficient and the data emergency situation.

[0022] Optionally, calculating the resource computing energy efficiency corresponding to the software and hardware resources according to the resource load data includes:

[0023] Determining the current computing task of the software and hardware resources according to the resource load data;

[0024] Calculate the resource usage of the software and hardware resources according to the current computing task;

[0025] Calculate the computing power availability corresponding to the software and hardware resources according to the computing power occupied by the resources;

[0026] Collecting resource maintenance data corresponding to the software and hardware resources, and calculating resource reliability corresponding to the software and hardware resources based on the resource maintenance data;

[0027] The resource computing energy efficiency corresponding to the software and hardware resources is calculated according to the resource reliability and the computing power availability.

[0028] Optionally, calculating the resource reliability corresponding to the software and hardware resources according to the resource failure data includes:

[0029] Extracting fault repair data and fault cycle data from the resource fault data;

[0030] According to the fault repair data, the number of faults corresponding to the software and hardware resources and their corresponding fault repair cycles are counted;

[0031] Determine the resource deactivation period corresponding to the software and hardware resources according to the fault cycle data, and query the operation log of the software and hardware resources;

[0032] Calculating the resource operation cycle of the software and hardware resources according to the operation log;

[0033] In combination with the number of failures, the failure repair cycle, the resource operation cycle and the resource downtime cycle, the resource reliability corresponding to the software and hardware resources is calculated by the following formula:

[0034]

[0035] Among them, A represents the resource reliability corresponding to the software and hardware resources, B failures Indicates the number of failures, T repair Represents the fault repair cycle, T downtime Indicates the resource deactivation period, T total Indicates the resource operation cycle.

[0036] Optionally, calculating the data response delay of the data to be calculated in the computing resource according to the resource parameter includes:

[0037] Calculating the transmission distance between the data to be calculated and each of the computing resources, and determining the resource congestion degree corresponding to the computing resource;

[0038] Measuring a network delay factor corresponding to the computing resource, and calculating a core performance coefficient corresponding to the computing resource according to the resource parameter;

[0039] In combination with the transmission distance, the resource congestion, the network delay factor and the core performance coefficient, the data response delay of the data to be calculated in the computing resource is calculated by the following formula:

[0040]

[0041] Where E represents the data response delay of the data to be calculated in the computing resources, and D a represents the transmission distance corresponding to the ath data in the data to be calculated, γ represents the resource congestion, represents the network delay factor, μ represents the core performance coefficient, and F represents the transmission bandwidth used by the computing resources.

[0042] Optionally, calculating the core performance coefficient corresponding to the computing resource according to the resource parameter includes:

[0043] Identify a resource component corresponding to the computing resource, and determine a component performance value corresponding to the resource component according to the resource parameter;

[0044] Scheduling historical service data corresponding to the resource component, and calculating component contribution corresponding to the resource component according to the historical service data;

[0045] The core efficiency coefficient corresponding to the computing resource is calculated according to the component contribution and the component performance value.

[0046] Optionally, the determining the interactive resources in the computing resources includes:

[0047] Obtain resource computing power attributes corresponding to the computing resources, based on the resource computing power attributes;

[0048] Parsing the resource operation function corresponding to the computing resource, and analyzing the resource input and resource output corresponding to the computing resource according to the resource operation function;

[0049] Analyzing resource dependencies between the computing resources in combination with the resource input and the resource output;

[0050] Calculating the functional correlation between the resource operation functions;

[0051] Determine interactive resources in the computing resources according to the functional association and the resource dependency.

[0052] Optionally, the calculating the resource coordination efficiency between the combined interactive resources in combination with the data response delay includes:

[0053] Calculating the data capacity corresponding to the data to be calculated, and measuring the data compression duration and data decompression duration corresponding to the data to be calculated using a preset measurement software;

[0054] In combination with the data response delay, the data capacity, the data compression duration, and the data decompression duration, the resource coordination efficiency between the combined interactive resources is calculated by the following formula:

[0055]

[0056] Among them, Q represents the resource coordination efficiency between the combined interactive resources, G represents the effective data capacity of the data to be calculated, represents the total processing time, K represents the data response delay, L represents the corresponding data capacity in the data to be calculated, CH represents the data compression time, NH represents the data decompression time, and MH represents the processing time threshold.

[0057] A computer software and hardware intelligent interaction method, characterized in that the method comprises:

[0058] Obtaining data to be calculated input into the computer, evaluating the data emergency situation corresponding to the data to be calculated, querying the calculation task corresponding to the data to be calculated, and setting the calculation priority corresponding to the data to be calculated in combination with the data emergency situation and the calculation task;

[0059] Scheduling the software and hardware resources in the computer for processing the data to be calculated, and collecting resource load data corresponding to the software and hardware resources, calculating the resource computing energy efficiency corresponding to the software and hardware resources according to the resource load data, and selecting the computing resources for the data to be calculated from the software and hardware resources according to the resource computing energy efficiency;

[0060] Collecting resource parameters corresponding to the computing resources, and calculating data response delay of the data to be calculated in the computing resources according to the resource parameters;

[0061] Analyze resource attributes corresponding to the computing resources, determine interactive resources in the computing resources according to the resource attributes, combine the interactive resources in combination with the data response delay to obtain combined interactive resources, and calculate resource coordination efficiency between the combined interactive resources in combination with the data response delay;

[0062] In combination with the data to be calculated, the calculation priority and the resource coordination efficiency, the combined interactive resources are used to perform interactive calculation processing of the data to be calculated to obtain a processing result.

[0063] The present invention can understand the urgency of the need to calculate the data to be calculated by evaluating the data emergency situation corresponding to the data to be calculated, thereby facilitating the subsequent setting of the calculation priority. The present invention calculates the resource calculation energy efficiency corresponding to the software and hardware resources according to the resource load data, and can understand the degree to which the software and hardware resources are effectively utilized through the resource calculation energy efficiency, thereby facilitating the subsequent screening of computing resources. The present invention calculates the data response delay of the data to be calculated in the computing resources according to the resource parameters, and can obtain the transmission time of the data to be calculated in the computing resources, which is convenient for the subsequent planning and processing of the computing resources. The present invention determines the interactive resources in the computing resources, which is convenient for the subsequent more reasonable allocation of computing resources and improves the system performance of the computer. The present invention combines the data to be calculated, the calculation priority and the resource coordination efficiency, and uses the combined interactive resources to perform the interactive calculation processing of the data to be calculated, which can improve the interactive efficiency of the computer. Therefore, a computer hardware and software intelligent interaction system and method provided by an embodiment of the present invention can improve the intelligent interaction efficiency of computer hardware and software. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A functional module diagram of a computer software and hardware intelligent interaction system provided by an embodiment of the present invention;

[0065] Figure 2 A flowchart of a computer software and hardware intelligent interaction method provided by one embodiment of the present invention.

[0066] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. 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.

[0068] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0069] In fact, the server-side device deployed by the computer software and hardware intelligent interaction system may be composed of one or more devices. The above-mentioned computer software and hardware intelligent interaction system can be implemented as: business instance, virtual machine, hardware device. For example, the computer software and hardware intelligent interaction system can be implemented as a business instance deployed on one or more devices in the cloud node. In simple terms, the live broadcast service system can be understood as a software deployed on the cloud node, which is used to provide computer software and hardware intelligent interaction services to each user terminal. Alternatively, the computer software and hardware intelligent interaction system can also be implemented as a virtual machine deployed on one or more devices in the cloud node. The virtual machine is installed with application software for managing each user terminal. Alternatively, the computer software and hardware intelligent interaction system can also be implemented as a server consisting of many hardware devices of the same or different types, and one or more hardware devices are set to provide computer software and hardware intelligent interaction services to each user terminal.

[0070] In terms of implementation, the computer software and hardware intelligent interaction system and the user end are adapted to each other. That is, the computer software and hardware intelligent interaction system is an application installed on the cloud service platform, and the user end is a client that establishes a communication connection with the application; or the computer software and hardware intelligent interaction system is implemented as a website, and the user end is implemented as a web page; or the computer software and hardware intelligent interaction system is implemented as a cloud service platform, and the user end is implemented as a small program in an instant messaging application.

[0071] Reference Figure 1 , which is a functional module diagram of a computer software and hardware intelligent interaction system provided by an embodiment of the present invention.

[0072] The computer software and hardware intelligent interaction system 100 of the present invention can be set in a cloud server. In terms of implementation, it can be used as one or more service devices, or as an application installed on the cloud (such as a server or server cluster of a live service operator), or it can be developed as a website. According to the functions implemented, the computer software and hardware intelligent interaction system 100 includes an operation priority calculation module 101, a resource screening module 102, a response delay calculation module 103, a collaborative efficiency calculation module 104, and an interaction processing module 105.

[0073] In the embodiment of the present invention, in the tracking based on the intelligent interaction of computer software and hardware, each of the above modules can be implemented independently and called with other modules. The call here can be understood as a module that can connect multiple modules of another type and provide corresponding services to the multiple modules connected to it. In the computer software and hardware intelligent interaction system provided by the embodiment of the present invention, the scope of application of the computer software and hardware intelligent interaction architecture can be adjusted by adding modules and directly calling them without modifying the program code, so as to achieve cluster-based horizontal expansion, so as to achieve the purpose of quickly and flexibly expanding the computer software and hardware intelligent interaction system. In actual applications, the above modules can be set in the same device or different devices, or they can be set in virtual devices, such as service instances in cloud servers.

[0074] In the following, in conjunction with specific embodiments, each component of the computer software and hardware intelligent interaction system and the specific workflow are described respectively.

[0075] The operation priority calculation module 101 is used to obtain the data to be calculated input into the computer, evaluate the data emergency situation corresponding to the data to be calculated, and query the operation task corresponding to the data to be calculated, and set the operation priority corresponding to the data to be calculated in combination with the data emergency situation and the operation task.

[0076] By evaluating the data emergency situation corresponding to the data to be calculated, the present invention can understand the urgency of the need to calculate the data to be calculated, thereby facilitating the setting and processing of subsequent calculation priorities, wherein the data to be calculated is relevant data that the computer needs to process, and the data emergency situation indicates the urgency of the need to calculate the data to be calculated.

[0077] As an embodiment of the present invention, the evaluation of the data emergency situation corresponding to the data to be calculated includes: identifying the input timestamp when the data to be calculated is input into the computer, and querying the deadline timestamp corresponding to the data to be calculated, combining the input timestamp and the deadline timestamp, calculating the time margin corresponding to the data to be calculated, calculating the data importance corresponding to the data to be calculated, and combining the time margin and the data importance to evaluate the data emergency situation corresponding to the data to be calculated.

[0078] Among them, the input timestamp is the time point corresponding to when the data to be calculated is input into the computer, the deadline timestamp is the deadline processing time point corresponding to the data to be calculated, the time margin indicates the time slackness of the data to be calculated, and the data importance indicates the importance corresponding to the data to be calculated. Further, the identification of the input timestamp when the data to be calculated is input into the computer can be realized by the time function; the deadline timestamp corresponding to the data to be calculated can be obtained by querying in the data warehouse; the time difference between the input timestamp and the deadline timestamp is calculated to obtain the time margin corresponding to the data to be calculated; the data entropy corresponding to the data to be calculated can be calculated, and the data importance of the data to be calculated can be obtained according to the data entropy; the time margin and the data importance are normalized, and the normalized values ​​are added to obtain the comprehensive score corresponding to the data to be calculated. According to the comprehensive score, the data emergency situation corresponding to the data to be calculated is evaluated, for example: scores 1-2 are "low emergency", scores 2-3 are "medium-low emergency", scores 3-4 are "medium emergency", and scores 4-5 are "high emergency".

[0079] The present invention sets the operation priority corresponding to the data to be calculated by combining the data emergency situation and the operation task, so as to facilitate the subsequent calculation of the data that needs to be urgently processed in the data to be calculated, wherein the operation priority represents the priority processing degree corresponding to the data to be calculated.

[0080] As an embodiment of the present invention, the combination of the data emergency situation and the computing task to set the computing priority corresponding to the data to be calculated includes: extracting the data identifier corresponding to the data to be calculated, calculating the identifier weight corresponding to the data identifier, extracting the key identifier in the data identifier according to the identifier weight, performing task decomposition on the computing task to obtain decomposed tasks, analyzing the task objectives corresponding to the decomposed tasks, calculating the matching coefficient between the task objectives and the key identifier, and setting the computing priority corresponding to the data to be calculated according to the matching coefficient and the data emergency situation.

[0081] Among them, the data identifier is the label corresponding to the data to be calculated, the identifier weight represents the importance corresponding to the data identifier, the key identifier is a representative identifier among the data identifiers, the decomposed task is a subtask in the calculation task, the task goal is the task achievement purpose corresponding to the decomposed task, and the matching coefficient represents the degree of matching between the task goal and the key identifier.

[0082] Further, the extraction of the data identifier corresponding to the data to be operated can be achieved by an identifier extraction tool, which is compiled by a scripting language, such as JS scripting language; the calculation of the identifier weight corresponding to the data identifier can be achieved by a weight calculator, which is compiled by Python language; the identifier weight is compared with a preset weight, and when the identifier weight is greater than the preset weight, the corresponding data identifier is extracted as a key identifier, and the preset weight can be set to 0.8, or can be set according to the actual application scenario; the task decomposition of the operation task can be achieved by a process analysis method, and the operation task is decomposed according to the task process of the operation task; the corresponding task target can be analyzed by the task name corresponding to the decomposed task; the calculation of the matching coefficient between the task target and the key identifier can be achieved by a cosine similarity algorithm; by constructing a priority judgment matrix of the matching coefficient and the data emergency situation, analyzing the summation result in the matrix, and setting the operation priority corresponding to the data to be operated according to the summation result, for example, if the data emergency situation is low urgency, the matching coefficient is 0.6, then the corresponding matching degree is low matching degree, and the priority judgment matrix result corresponding to the data to be operated is low priority, then the operation priority is low.

[0083] The resource screening module 102 is used to schedule the software and hardware resources in the computer for processing the data to be calculated, and collect resource load data corresponding to the software and hardware resources, calculate the resource computing energy efficiency corresponding to the software and hardware resources based on the resource load data, and screen out the computing resources for the data to be calculated from the software and hardware resources based on the resource computing energy efficiency.

[0084] The present invention calculates the resource computing energy efficiency corresponding to the software and hardware resources based on the resource load data, and the degree to which the software and hardware resources are effectively utilized can be understood through the resource computing energy efficiency, thereby facilitating the subsequent screening and processing of computing resources, wherein the software and hardware resources are resources used in the computer to process the data to be calculated, and the resource load data are data recorded during the operation process corresponding to the software and hardware resources, and the resource computing energy efficiency indicates the degree to which the software and hardware resources are effectively utilized. Furthermore, the scheduling of the software and hardware resources for processing the data to be calculated in the computer can be achieved through a computer controller, such as a program counter, an instruction register, and an operation controller; the collection of resource load data corresponding to the software and hardware resources can be achieved through a task manager.

[0085] As an embodiment of the present invention, calculating the resource computing energy efficiency corresponding to the software and hardware resources based on the resource load data includes: determining the current computing task of the software and hardware resources based on the resource load data, calculating the resource occupation computing power of the software and hardware resources based on the current computing task, calculating the computing power availability corresponding to the software and hardware resources based on the resource occupation computing power, collecting resource maintenance data corresponding to the software and hardware resources, calculating the resource reliability corresponding to the software and hardware resources based on the resource maintenance data, and calculating the resource computing energy efficiency corresponding to the software and hardware resources based on the resource reliability and the computing power availability.

[0086] Among them, the current computing task is the task that the software and hardware resources currently need to calculate and process, the resource occupied computing power is the quantitative value of the used resources of the software and hardware resources, the computing power availability rate represents the percentage of available computing power corresponding to the software and hardware, the resource maintenance data is the data of the maintenance record of the software and hardware resources, and the resource reliability represents the resource reliability degree corresponding to the software and hardware resources.

[0087] Furthermore, log record data in the resource load data can be extracted, and the current computing task of the software and hardware resources can be determined based on the log record data; the computing power capacity corresponding to the current computing task is calculated, and the computing power capacity is summed to obtain the resource occupation computing power of the software and hardware resources; based on the resource occupation computing power, the total resource computing power corresponding to the software and hardware resources is queried, and the computing power availability is obtained through 1-resource occupation computing power / total resource computing power; the resource maintenance data corresponding to the software and hardware resources can be collected through a maintenance work order system; the resource computing energy efficiency corresponding to the software and hardware resources is obtained by calculating the product of the resource reliability and the computing power availability and the correction coefficient. The correction coefficient is a numerical value for adjusting and optimizing the calculation result, which can be obtained through analysis and statistics of a large amount of actual data, or determined based on experience and specific business needs.

[0088] Optionally, as an optional embodiment of the present invention, the resource reliability corresponding to the software and hardware resources is calculated according to the resource fault data, including: extracting fault repair data and fault cycle data from the resource fault data, counting the number of faults corresponding to the software and hardware resources and their corresponding fault repair cycles according to the fault repair data, determining the resource downtime cycle corresponding to the software and hardware resources according to the fault cycle data, querying the operation log of the software and hardware resources, calculating the resource operation cycle of the software and hardware resources according to the operation log, and combining the number of faults, the fault repair cycle, the resource operation cycle and the resource downtime cycle to calculate the resource reliability corresponding to the software and hardware resources by the following formula:

[0089]

[0090] Among them, A represents the resource reliability corresponding to the software and hardware resources, B failures Indicates the number of failures, T repair Represents the fault repair cycle, T downtime Indicates the resource deactivation period, T total Indicates the resource operation cycle.

[0091] Among them, the fault repair data and the fault cycle data are the maintenance record data about the software and hardware resources in the resource fault data and the recorded time when the resources cannot be used due to the fault. The resource outage cycle indicates the duration of the software and hardware resources being unavailable due to the fault. The operation log is the operational behavior record of starting, shutting down and executing tasks of the software and hardware resources. The resource operation cycle indicates the operation duration of the software and hardware resources. Furthermore, the extraction of the fault repair data and fault cycle data in the resource fault data can be implemented by an extraction function, which is compiled by a programming language; each fault outage time in the fault cycle data is added to obtain the resource outage cycle corresponding to the software and hardware resources; the startup time and shutdown time of the software and hardware resources are determined from the operation log, and the difference between the shutdown time and the startup time is calculated to obtain the resource operation cycle of the software and hardware resources.

[0092] The present invention selects computing resources for the data to be calculated from the software and hardware resources based on the resource computing energy efficiency, thereby avoiding the subsequent allocation of computing tasks to resources with low energy efficiency, resulting in unnecessary energy consumption and cost increase, wherein the computing resources are resources that can process the data to be calculated, and further, the values ​​of the resource computing energy efficiency corresponding to each resource in the software and hardware resources are compared, and the resource with the highest resource computing energy efficiency is selected from the resources of the same type as the computing resource for the data to be calculated.

[0093] The data response delay calculation module 103 is used to collect resource parameters corresponding to the computing resources, and calculate the data response delay of the data to be calculated in the computing resources according to the resource parameters.

[0094] The present invention calculates the data response delay of the data to be calculated in the computing resource based on the resource parameters, and can obtain the transmission time of the data to be calculated in the computing resource, which is convenient for subsequent planning and processing of the computing resources, wherein the resource parameters are quantitative descriptions of the capabilities of the computing resources, and the data response delay represents the transmission time of the data to be calculated in the computing resources. Furthermore, the collection of resource parameters corresponding to the computing resources can be achieved through hardware detection software, such as a performance monitor.

[0095] As an embodiment of the present invention, the data response delay of the data to be calculated in the computing resource according to the resource parameters includes: calculating the transmission distance between the data to be calculated and each resource in the computing resources, determining the resource congestion corresponding to the computing resource, measuring the network delay factor corresponding to the computing resource, calculating the core performance coefficient corresponding to the computing resource according to the resource parameters, combining the transmission distance, the resource congestion, the network delay factor and the core performance coefficient, and calculating the data response delay of the data to be calculated in the computing resource by the following formula:

[0096]

[0097] Where E represents the data response delay of the data to be calculated in the computing resources, and D a represents the transmission distance corresponding to the ath data in the data to be calculated, γ represents the resource congestion, represents the network delay factor, μ represents the core performance coefficient, and F represents the transmission bandwidth used by the computing resources.

[0098] Among them, the transmission distance represents the distance in which the data to be calculated is transmitted to the computing resource, the resource congestion degree represents the congestion degree corresponding to the computing resource, the network delay factor represents the delay degree corresponding to the computing resource, the core efficiency coefficient represents the core performance quantification value corresponding to the computing resource, and the transmission bandwidth represents the amount of data transmitted by the computing resource per unit time.

[0099] Optionally, the transmission distance can be obtained by calculating the distance between the data to be calculated and each resource in the computing resources; the resource congestion degree can be obtained by calculating the rate of change of the throughput corresponding to the computing resources; the measurement of the network delay factor corresponding to the computing resources can be achieved through network performance testing software, such as iPerf software.

[0100] Optionally, as an optional embodiment of the present invention, calculating the core performance coefficient corresponding to the computing resource based on the resource parameters includes: identifying the resource component corresponding to the computing resource, determining the component performance value corresponding to the resource component based on the resource parameters, scheduling historical service data corresponding to the resource component, calculating the component contribution corresponding to the resource component based on the historical service data, and calculating the core performance coefficient corresponding to the computing resource based on the component contribution and the component performance value.

[0101] Among them, the resource component is the component corresponding to the computing resource, such as memory or hard disk, the component performance value is the specific value of the resource parameter describing the performance of the resource component, such as the memory capacity is 16g, and the historical service data is the recorded data of the past service process corresponding to the resource component, such as the changes in CPU usage in each time period, the fluctuations in memory occupancy, etc. The component contribution degree indicates the extent of the role played by the resource component in processing data.

[0102] Furthermore, the component contribution of the resource component can be determined according to the component utilization rate corresponding to the resource component recorded in the historical service data; the component contribution and the component performance value are multiplied and summed to obtain the core efficiency coefficient corresponding to the computing resource.

[0103] The collaborative efficiency calculation module 104 is used to analyze the resource attributes corresponding to the computing resources, determine the interactive resources in the computing resources based on the resource attributes, combine the interactive resources in combination with the data response delay to obtain combined interactive resources, and calculate the resource collaborative efficiency between the combined interactive resources in combination with the data response delay.

[0104] The present invention facilitates subsequent more reasonable allocation of computing resources and improves the system performance of the computer by determining interactive resources in the computing resources, wherein the interactive resources are resources in the computing resources that can exchange information, share data and operate collaboratively.

[0105] As an embodiment of the present invention, determining the interactive resources in the computing resources includes: obtaining the resource computing power attributes corresponding to the computing resources, parsing the resource operation functions corresponding to the computing resources according to the resource computing power attributes, analyzing the resource input and resource output corresponding to the computing resources according to the resource operation functions, analyzing the resource dependency between the computing resources in combination with the resource input and the resource output, calculating the functional correlation between the resource operation functions, and determining the interactive resources in the computing resources according to the functional correlation and the resource dependency.

[0106] Among them, the resource computing power attribute is the characteristic of the computing resource in terms of computing power, the resource operation function is the specific ability corresponding to the computing resource, the resource input and the resource output are respectively the variables that need to be processed by the computing resource and the variables output after the processing is completed, the resource dependency relationship represents the description of the constraint state between the computing resources, and the functional association degree represents the association relationship between the resource operation functions.

[0107] Furthermore, the resource computing power attributes corresponding to the computing resources can be obtained through system monitoring tools; the analysis of the resource operation functions corresponding to the computing resources can be achieved through principal component analysis; the resource input and resource output corresponding to the computing resources can be obtained by analyzing the algorithms and logic inside the computing resources; the resource input and the resource output can be analyzed by using a causal analysis method to obtain the resource dependency relationship between the computing resources; the calculation of the functional correlation between the resource operation functions can be achieved through a Pearson correlation coefficient algorithm; based on the functional correlation and the resource dependency relationship, the interactive resources in the computing resources are determined, for example, the function of resource 1 is highly correlated with the function of resource 2, and the operation of resource 2 is heavily dependent on the data provided by resource 1, then resource 1 and resource 2 are interactive resources.

[0108] The present invention calculates the resource coordination efficiency between the combined interactive resources in combination with the data response delay, thereby understanding the collaborative effect between the combined interactive resources, and further facilitating the subsequent interactive calculation processing of the data to be calculated, wherein the combined interactive resources are resources obtained by combining the interactive resources according to the numerical value of the data response delay, and the resource coordination efficiency represents the effect of the collaborative cooperation between the combined interactive resources.

[0109] As an embodiment of the present invention, the combining of the data response delay and calculating the resource coordination efficiency between the combined interactive resources includes: calculating the data capacity corresponding to the data to be calculated, measuring the data compression duration and the data decompression duration corresponding to the data to be calculated using preset measurement software, and combining the data response delay, the data capacity, the data compression duration and the data decompression duration to calculate the resource coordination efficiency between the combined interactive resources by the following formula:

[0110]

[0111] Among them, Q represents the resource coordination efficiency between the combined interactive resources, G represents the effective data capacity of the data to be calculated, represents the total processing time, K represents the data response delay, L represents the corresponding data capacity in the data to be calculated, CH represents the data compression time, NH represents the data decompression time, and MH represents the processing time threshold.

[0112] Among them, the effective data capacity represents the amount of data that actually participates in the interaction and generates value, which is obtained by screening and filtering the data to be calculated and then counting the final data amount. The data capacity represents the data size corresponding to the data to be calculated, and the data capacity corresponding to the data to be calculated can be calculated by a byte counting algorithm. The measurement software is software for measuring the data compression time and data decompression time corresponding to the data to be calculated, and the measurement software can be compiled by JAVA language. The processing time threshold represents the maximum acceptable processing time corresponding to the data to be calculated, which can be determined by considering the nature and purpose of the data. If the data is highly time-sensitive, such as financial transaction data or real-time monitoring data, then the processing time threshold will be set very short, because even a small delay may lead to significant economic losses or security risks, and the corresponding threshold is set in combination with relevant expert experience.

[0113] The interactive processing module 105 is used to combine the data to be calculated, the calculation priority and the resource coordination efficiency, and use the combined interactive resources to perform interactive calculation processing on the data to be calculated to obtain a processing result.

[0114] The present invention combines the data to be calculated, the calculation priority and the resource coordination efficiency, and utilizes the combined interactive resources to perform interactive calculation processing of the data to be calculated, thereby improving the interactive efficiency of the computer. Furthermore, the resource coordination efficiency can be used to screen out target interactive resources from the combined interactive resources, analyze the data architecture corresponding to the data to be calculated, match the data to be calculated with the target interactive resources according to the data architecture, and utilize the target interactive resources to perform interactive calculation processing on the data to be calculated according to the calculation priority to obtain a processing result.

[0115] The present invention can understand the urgency of the need to calculate the data to be calculated by evaluating the data emergency situation corresponding to the data to be calculated, thereby facilitating the subsequent setting of the calculation priority. The present invention calculates the resource calculation energy efficiency corresponding to the software and hardware resources according to the resource load data, and can understand the degree to which the software and hardware resources are effectively utilized through the resource calculation energy efficiency, thereby facilitating the subsequent screening of computing resources. The present invention calculates the data response delay of the data to be calculated in the computing resources according to the resource parameters, and can obtain the transmission time of the data to be calculated in the computing resources, which is convenient for the subsequent planning and processing of the computing resources. The present invention determines the interactive resources in the computing resources, which is convenient for the subsequent more reasonable allocation of computing resources and improves the system performance of the computer. The present invention combines the data to be calculated, the calculation priority and the resource coordination efficiency, and uses the combined interactive resources to perform the interactive calculation processing of the data to be calculated, which can improve the interactive efficiency of the computer. Therefore, a computer hardware and software intelligent interaction system and method provided by an embodiment of the present invention can improve the intelligent interaction efficiency of computer hardware and software.

[0116] Reference Figure 2 FIG. 1 is a flow chart of a method for intelligent interaction of computer software and hardware provided by an embodiment of the present invention. In this embodiment, the method for intelligent interaction of computer software and hardware includes:

[0117] Obtaining data to be calculated input into the computer, evaluating the data emergency situation corresponding to the data to be calculated, querying the calculation task corresponding to the data to be calculated, and setting the calculation priority corresponding to the data to be calculated in combination with the data emergency situation and the calculation task;

[0118] Scheduling the software and hardware resources in the computer for processing the data to be calculated, and collecting resource load data corresponding to the software and hardware resources, calculating the resource computing energy efficiency corresponding to the software and hardware resources according to the resource load data, and selecting the computing resources for the data to be calculated from the software and hardware resources according to the resource computing energy efficiency;

[0119] Collecting resource parameters corresponding to the computing resources, and calculating data response delay of the data to be calculated in the computing resources according to the resource parameters;

[0120] Analyze resource attributes corresponding to the computing resources, determine interactive resources in the computing resources according to the resource attributes, combine the interactive resources in combination with the data response delay to obtain combined interactive resources, and calculate resource coordination efficiency between the combined interactive resources in combination with the data response delay;

[0121] In combination with the data to be calculated, the calculation priority and the resource coordination efficiency, the combined interactive resources are used to perform interactive calculation processing of the data to be calculated to obtain a processing result.

[0122] In the several embodiments provided by the present invention, it should be understood that the provided system and method can be implemented in other ways. For example, the system embodiment described above is only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0123] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A computer software and hardware intelligent interaction system, characterized in that: The intelligent interaction system includes: an operation priority calculation module, a resource screening module, a response delay calculation module, a collaborative efficiency calculation module, and an interaction processing module; The operation priority calculation module is used to obtain the data to be operated input into the computer, evaluate the data emergency situation corresponding to the data to be operated, and query the operation task corresponding to the data to be operated, and set the operation priority corresponding to the data to be operated in combination with the data emergency situation and the operation task; The resource screening module is used to schedule the software and hardware resources in the computer for processing the data to be calculated, and collect resource load data corresponding to the software and hardware resources, calculate the resource computing energy efficiency corresponding to the software and hardware resources according to the resource load data, and screen the computing resources for the data to be calculated from the software and hardware resources according to the resource computing energy efficiency; The data response delay calculation module is used to collect resource parameters corresponding to the computing resources, and calculate the data response delay of the data to be calculated in the computing resources according to the resource parameters; The collaborative efficiency calculation module is used to analyze the resource attributes corresponding to the computing resources, determine the interactive resources in the computing resources according to the resource attributes, combine the interactive resources in combination with the data response delay to obtain combined interactive resources, and calculate the resource collaborative efficiency between the combined interactive resources in combination with the data response delay; The interactive processing module is used to combine the data to be calculated, the calculation priority and the resource coordination efficiency, and use the combined interactive resources to perform interactive calculation processing on the data to be calculated to obtain a processing result.

2. A computer software and hardware intelligent interaction system as claimed in claim 1, characterized in that: The evaluating the data emergency situation corresponding to the data to be calculated includes: Identify the input timestamp when the data to be calculated is input into the computer, and query the deadline timestamp corresponding to the data to be calculated; Calculate the time margin corresponding to the data to be calculated by combining the input timestamp and the deadline timestamp; Calculating the data importance corresponding to the data to be calculated; The data emergency situation corresponding to the data to be calculated is evaluated in combination with the time margin and the data importance.

3. A computer software and hardware intelligent interaction system as claimed in claim 1, characterized in that: The step of setting the operation priority corresponding to the data to be operated in combination with the data emergency situation and the operation task includes: Extracting a data identifier corresponding to the data to be calculated, and calculating an identifier weight corresponding to the data identifier; extracting a key identifier from the data identifier according to the identifier weight; Decomposing the computing task to obtain decomposed tasks, and analyzing the task objectives corresponding to the decomposed tasks; Calculating a matching coefficient between the task target and the key identifier; The operation priority corresponding to the data to be operated is set according to the matching coefficient and the data emergency situation.

4. A computer software and hardware intelligent interaction system as claimed in claim 1, characterized in that: The calculating, according to the resource load data, the resource computing energy efficiency corresponding to the software and hardware resources comprises: Determining the current computing task of the software and hardware resources according to the resource load data; Calculate the resource usage of the software and hardware resources according to the current computing task; Calculate the computing power availability corresponding to the software and hardware resources according to the computing power occupied by the resources; Collecting resource maintenance data corresponding to the software and hardware resources, and calculating resource reliability corresponding to the software and hardware resources based on the resource maintenance data; The resource computing energy efficiency corresponding to the software and hardware resources is calculated according to the resource reliability and the computing power availability.

5. A computer software and hardware intelligent interaction system as claimed in claim 4, characterized in that: The calculating, according to the resource failure data, the resource reliability corresponding to the software and hardware resources comprises: Extracting fault repair data and fault cycle data from the resource fault data; According to the fault repair data, the number of faults corresponding to the software and hardware resources and their corresponding fault repair cycles are counted; Determine the resource deactivation period corresponding to the software and hardware resources according to the fault cycle data, and query the operation log of the software and hardware resources; Calculating the resource operation cycle of the software and hardware resources according to the operation log; In combination with the number of failures, the failure repair cycle, the resource operation cycle and the resource downtime cycle, the resource reliability corresponding to the software and hardware resources is calculated by the following formula: Among them, A represents the resource reliability corresponding to the software and hardware resources, B failures Indicates the number of failures, T repair Represents the fault repair cycle, T downtime Indicates the resource deactivation period, T total Indicates the resource operation cycle.

6. A computer software and hardware intelligent interaction system as claimed in claim 1, characterized in that: The calculating, according to the resource parameter, a data response delay of the data to be operated in the computing resource comprises: Calculating the transmission distance between the data to be calculated and each of the computing resources, and determining the resource congestion degree corresponding to the computing resource; Measuring a network delay factor corresponding to the computing resource, and calculating a core performance coefficient corresponding to the computing resource according to the resource parameter; In combination with the transmission distance, the resource congestion, the network delay factor and the core performance coefficient, the data response delay of the data to be calculated in the computing resource is calculated by the following formula: Where E represents the data response delay of the data to be calculated in the computing resources, and D a represents the transmission distance corresponding to the ath data in the data to be calculated, γ represents the resource congestion, represents the network delay factor, μ represents the core performance coefficient, and F represents the transmission bandwidth used by the computing resources.

7. A computer software and hardware intelligent interaction system as claimed in claim 6, characterized in that: Calculating the core performance coefficient corresponding to the computing resource according to the resource parameter includes: Identify a resource component corresponding to the computing resource, and determine a component performance value corresponding to the resource component according to the resource parameter; Scheduling historical service data corresponding to the resource component, and calculating component contribution corresponding to the resource component according to the historical service data; The core efficiency coefficient corresponding to the computing resource is calculated according to the component contribution and the component performance value.

8. A computer software and hardware intelligent interaction system as claimed in claim 1, characterized in that: The determining of the interactive resources in the computing resources includes: Obtain resource computing power attributes corresponding to the computing resources, based on the resource computing power attributes; Parsing the resource operation function corresponding to the computing resource, and analyzing the resource input and resource output corresponding to the computing resource according to the resource operation function; Analyzing resource dependencies between the computing resources in combination with the resource input and the resource output; Calculating the functional correlation between the resource operation functions; Determine interactive resources in the computing resources according to the functional association and the resource dependency.

9. A computer software and hardware intelligent interaction system as claimed in claim 1, characterized in that: The calculating the resource coordination efficiency between the combined interactive resources in combination with the data response delay includes: Calculating the data capacity corresponding to the data to be calculated, and measuring the data compression duration and data decompression duration corresponding to the data to be calculated using a preset measurement software; In combination with the data response delay, the data capacity, the data compression duration, and the data decompression duration, the resource coordination efficiency between the combined interactive resources is calculated by the following formula: Among them, Q represents the resource coordination efficiency between the combined interactive resources, G represents the effective data capacity of the data to be calculated, represents the total processing time, K represents the data response delay, L represents the corresponding data capacity in the data to be calculated, CH represents the data compression time, NH represents the data decompression time, and MH represents the processing time threshold.

10. A computer software and hardware intelligent interaction method, characterized in that: The method comprises: Obtaining data to be calculated input into the computer, evaluating the data emergency situation corresponding to the data to be calculated, querying the calculation task corresponding to the data to be calculated, and setting the calculation priority corresponding to the data to be calculated in combination with the data emergency situation and the calculation task; Scheduling the software and hardware resources in the computer for processing the data to be calculated, and collecting resource load data corresponding to the software and hardware resources, calculating the resource computing energy efficiency corresponding to the software and hardware resources according to the resource load data, and selecting the computing resources for the data to be calculated from the software and hardware resources according to the resource computing energy efficiency; Collecting resource parameters corresponding to the computing resources, and calculating data response delay of the data to be calculated in the computing resources according to the resource parameters; Analyze resource attributes corresponding to the computing resources, determine interactive resources in the computing resources according to the resource attributes, combine the interactive resources in combination with the data response delay to obtain combined interactive resources, and calculate resource coordination efficiency between the combined interactive resources in combination with the data response delay; In combination with the data to be calculated, the calculation priority and the resource coordination efficiency, the combined interactive resources are used to perform interactive calculation processing of the data to be calculated to obtain a processing result.

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