A task processing method and device for computing power node

Abstract

The present invention relates to the field of computing power technology, and discloses a task processing method and device for a computing power node, the method comprising: analyzing the expected transmission link of the computing power node according to the acquired computing power resource demand information of the computing power node; determining at least one first target transmission node in the expected transmission link, the first target transmission node including first multi-dimensional attribute information; for each first target transmission node, predicting the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node; analyzing the target transmission link corresponding to the expected transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all transmission efficiency range information and the expected transmission link. It can be seen that the implementation of the present invention improves the flexibility and accuracy of the computing power resource allocation and transmission of the computing power node, so as to improve the task processing efficiency and flexibility of the computing power node.

Description

Technical Field

[0001] The present invention relates to the field of computing power technology, and in particular to a task processing method and device for a computing power node. Background Art

[0002] With the rapid development of information technology, the demand for computing power has exploded, especially in cutting-edge fields such as cloud computing, big data, and artificial intelligence.

[0003] In the current computing power resource allocation system, computing power nodes usually rely on fixed computing power resource pools or server clusters. However, practice has found that this fixed computing power resource allocation method will make the computing power nodes relatively fixed in the actual task processing process, and there is little room for flexible processing of emergencies. Some nodes are even unable to handle emergencies and complete corresponding tasks in a timely manner and according to the predetermined time limit. In the actual application process, it affects the user's task processing efficiency.

[0004] It can be seen that it is particularly important to improve the flexibility and accuracy of computing resource allocation and transmission of computing nodes in order to improve the task processing efficiency and flexibility of computing nodes. Summary of the invention

[0005] The present invention provides a task processing method and device for a computing power node, which can improve the flexibility and accuracy of computing power resource allocation and transmission of the computing power node, so as to improve the task processing efficiency and flexibility of the computing power node.

[0006] In order to solve the above technical problems, the first aspect of the present invention discloses a task processing method for a computing power node, the method comprising:

[0007] Obtain computing resource demand information of computing nodes;

[0008] Analyze the expected transmission link of the computing power node according to the computing power resource demand information, the expected transmission link includes an expected computing power transmission link and an expected task processing transmission link, the expected computing power transmission link includes the computing power node and the expected computing power resource node of the computing power node, and the expected task processing transmission link includes the computing power node and the target task node of the computing power node;

[0009] Determine at least one first target transmission node in the expected transmission link, where the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node;

[0010] For each of the first target transmission nodes, predicting the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node;

[0011] According to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link, the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link are analyzed, the target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node.

[0012] As an optional implementation, in the first aspect of the present invention, before obtaining the computing resource demand information of the computing node, the method further includes:

[0013] Obtain target task information of a computing power node and first status information of the computing power node, wherein the target task information includes task content information and task node information, wherein the task node information is used to indicate the task process node status, and the task node information includes task time node information and task docking object node information;

[0014] Analyze the task preparation information of the computing power node according to the task content information and the first status information, wherein the task preparation information is used to indicate the preparation status of the computing power node for the target task information;

[0015] Predicting preparation timeliness information of the task preparation information, where the preparation timeliness information is used to indicate the time consumption of the computing power node for the preparation of the target task information;

[0016] Predicting the current processing time information of the target task information by the computing resources according to the preparation time information and the task node information;

[0017] Calculating a first target distance value between the current processing time information and the task node information, wherein the first target distance value is used to indicate a mismatch degree between the current processing time information and the task node information;

[0018] The computing resource demand information of the computing node is analyzed according to the first target distance value and the task preparation information.

[0019] As an optional implementation manner, in the first aspect of the present invention, analyzing the expected transmission link of the computing power node according to the computing power resource demand information includes:

[0020] According to the computing power resource demand information, analyzing the first attribute information of the computing power node and the second attribute information of the target task node of the computing power node, the first attribute information includes at least one of current node processing efficiency information, computing power resource application cost information, first location information, to-be-processed data volume information, to-be-processed data type information, to-be-processed data conversion logic information, and first network environment information, and the second attribute information includes at least one of second location information and second network environment information;

[0021] According to the first attribute information, analyzing the third attribute information of the computing power node, the third attribute information includes at least one of the required computing power resource type information, the required computing power resource amount information, the required computing power resource application scenario information, and the computing power demand change trend information, the computing power demand change trend information is used to indicate the change trajectory of the computing power node's demand for computing power resources within a preset second time period;

[0022] According to the third attribute information and the second attribute information, the expected transmission link of the computing power node is analyzed.

[0023] As an optional implementation manner, in the first aspect of the present invention, the determining at least one first target transmission node in the desired transmission link includes:

[0024] Determine at least one transmission node and a transmission node sequence set in the expected transmission link, where the transmission node sequence set is used to represent data processing ordering of all the transmission nodes in the expected transmission link and data processing logic of the expected transmission link;

[0025] For each of the transmission nodes, determine the first data processing range information of the transmission node according to the transmission node sequence set; obtain the second state information of the transmission node and the application scenario set of the transmission node, wherein the application scenario set includes at least one application scenario of the transmission node; analyze the second data processing range information of the transmission node according to the second state information and the application scenario set; determine whether the second data processing range information matches the first data processing range information, and when it is determined that the second data processing range information matches the first data processing range information, determine the transmission node as the first target transmission node.

[0026] As an optional implementation manner, in the first aspect of the present invention, for each of the first target transmission nodes, predicting the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node includes:

[0027] Analyze the first multi-dimensional attribute information of the first target transmission node according to the second data processing range information of the first target transmission node, where the first multi-dimensional attribute information includes at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information;

[0028] Determine environmental information within a preset range of the first target transmission node within a preset first time period;

[0029] Analyze at least one interference factor of the first target transmission node according to the environmental information, where the interference factor is used to represent the interference factor to the first target transmission node within the preset range in the preset first time period;

[0030] Calculate an interference target value of the first target transmission node according to all the interference factors, where the interference target value is used to indicate the interference degree of all the interference factors within the preset range on the first target transmission node in a preset first time period;

[0031] Calculating, according to the interference target value, second multi-dimensional attribute information of the first target transmission node in the preset first time period, where the second multi-dimensional attribute information corresponds to the first multi-dimensional attribute information;

[0032] The transmission efficiency range information of the first target transmission node within the preset first time period is predicted according to the second multi-dimensional attribute information.

[0033] As an optional implementation manner, in the first aspect of the present invention, analyzing the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link, includes:

[0034] Analyzing the required transmission efficiency range information of the computing power node for the expected transmission link according to the computing power resource requirement information;

[0035] Generating actual transmission efficiency range information of the desired transmission link according to all the transmission efficiency range information;

[0036] Calculating a second target distance value between the actual transmission efficiency range information and the required transmission efficiency range information, wherein the second target distance value is used to indicate a degree of mismatch between the actual transmission efficiency range information and the required transmission efficiency range information;

[0037] Determine whether the second target distance value is greater than or equal to a preset second target distance threshold, and when it is determined that the second target distance value is greater than or equal to the preset second target distance threshold, determine at least one second target transmission node according to the second target distance value; and analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to all the second target transmission nodes and the second target distance value;

[0038] When it is determined that the second target distance value is less than the preset second target distance threshold, the expected transmission link is determined as the target transmission link of the computing power node, and based on all the transmission efficiency range information, the computing power transmission mode information of the target transmission link is analyzed.

[0039] As an optional implementation manner, in the first aspect of the present invention, determining at least one second target transmission node according to the second target distance value includes:

[0040] For each of the transmission efficiency range information, calculating a third target distance value between the transmission efficiency range information and the required transmission efficiency range information, wherein the third target distance value is used to indicate a degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information;

[0041] According to all the third target distance values, determine at least one third target transmission node among all the first target transmission nodes, the third target distance value of the third target transmission node being greater than or equal to a third target distance threshold, and the third target distance threshold being determined according to the second target distance value;

[0042] For each of the third target transmission nodes, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node.

[0043] A second aspect of the present invention discloses a task processing device for a computing node, the device comprising:

[0044] The acquisition module is used to obtain the computing resource demand information of the computing node;

[0045] An analysis module, configured to analyze the expected transmission link of the computing power node according to the computing power resource demand information, wherein the expected transmission link includes an expected computing power transmission link and an expected task processing transmission link, wherein the expected computing power transmission link includes the computing power node and an expected computing power resource node of the computing power node, and the expected task processing transmission link includes the computing power node and a target task node of the computing power node;

[0046] a determination module, configured to determine at least one first target transmission node in the desired transmission link, wherein the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node;

[0047] A prediction module, configured to predict, for each of the first target transmission nodes, transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node;

[0048] The analysis module is also used to analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link, the target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node.

[0049] As an optional implementation, in the second aspect of the present invention, the acquisition module is also used to obtain target task information of the computing power node and first status information of the computing power node before the acquisition module obtains the computing power resource demand information of the computing power node, the target task information includes task content information and task node information, the task node information is used to indicate the task process node status, and the task node information includes task time node information and task docking object node information;

[0050] The analysis module is further used to analyze the task preparation information of the computing power node according to the task content information and the first status information, wherein the task preparation information is used to indicate the preparation status of the computing power node for the preparatory work of the target task information;

[0051] The prediction module is further used to predict the preparation timeliness information of the task preparation information, and the preparation timeliness information is used to indicate the time consumption of the preparation work of the computing power node for the target task information;

[0052] The prediction module is further used to predict the current processing time information of the computing power resource on the target task information according to the preparation time information and the task node information;

[0053] And, the device further comprises:

[0054] A calculation module, used for calculating a first target distance value between the current processing time information and the task node information, wherein the first target distance value is used for indicating a mismatch degree between the current processing time information and the task node information;

[0055] The analysis module is also used to analyze the computing resource demand information of the computing node based on the first target distance value and the task preparation information.

[0056] As an optional implementation, in the second aspect of the present invention, the specific manner in which the analysis module analyzes the expected transmission link of the computing power node according to the computing power resource demand information includes:

[0057] According to the computing power resource demand information, analyzing the first attribute information of the computing power node and the second attribute information of the target task node of the computing power node, the first attribute information includes at least one of current node processing efficiency information, computing power resource application cost information, first location information, to-be-processed data volume information, to-be-processed data type information, to-be-processed data conversion logic information, and first network environment information, and the second attribute information includes at least one of second location information and second network environment information;

[0058] According to the first attribute information, analyzing the third attribute information of the computing power node, the third attribute information includes at least one of the required computing power resource type information, the required computing power resource amount information, the required computing power resource application scenario information, and the computing power demand change trend information, the computing power demand change trend information is used to indicate the change trajectory of the computing power node's demand for computing power resources within a preset second time period;

[0059] According to the third attribute information and the second attribute information, the expected transmission link of the computing power node is analyzed.

[0060] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the determination module determines at least one first target transmission node in the desired transmission link includes:

[0061] Determine at least one transmission node and a transmission node sequence set in the expected transmission link, where the transmission node sequence set is used to represent data processing ordering of all the transmission nodes in the expected transmission link and data processing logic of the expected transmission link;

[0062] For each of the transmission nodes, determine the first data processing range information of the transmission node according to the transmission node sequence set; obtain the second state information of the transmission node and the application scenario set of the transmission node, wherein the application scenario set includes at least one application scenario of the transmission node; analyze the second data processing range information of the transmission node according to the second state information and the application scenario set; determine whether the second data processing range information matches the first data processing range information, and when it is determined that the second data processing range information matches the first data processing range information, determine the transmission node as the first target transmission node.

[0063] As an optional implementation, in the second aspect of the present invention, for each of the first target transmission nodes, the prediction module predicts the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node. The specific method includes:

[0064] Analyze the first multi-dimensional attribute information of the first target transmission node according to the second data processing range information of the first target transmission node, where the first multi-dimensional attribute information includes at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information;

[0065] Determine environmental information within a preset range of the first target transmission node within a preset first time period;

[0066] Analyze at least one interference factor of the first target transmission node according to the environmental information, where the interference factor is used to represent the interference factor to the first target transmission node within the preset range in the preset first time period;

[0067] Calculate an interference target value of the first target transmission node according to all the interference factors, where the interference target value is used to indicate the interference degree of all the interference factors within the preset range on the first target transmission node in a preset first time period;

[0068] Calculating, according to the interference target value, second multi-dimensional attribute information of the first target transmission node in the preset first time period, where the second multi-dimensional attribute information corresponds to the first multi-dimensional attribute information;

[0069] The transmission efficiency range information of the first target transmission node within the preset first time period is predicted according to the second multi-dimensional attribute information.

[0070] As an optional implementation, in the second aspect of the present invention, the specific manner in which the analysis module analyzes the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link includes:

[0071] Analyzing the required transmission efficiency range information of the computing power node for the expected transmission link according to the computing power resource requirement information;

[0072] Generating actual transmission efficiency range information of the desired transmission link according to all the transmission efficiency range information;

[0073] Calculating a second target distance value between the actual transmission efficiency range information and the required transmission efficiency range information, wherein the second target distance value is used to indicate a degree of mismatch between the actual transmission efficiency range information and the required transmission efficiency range information;

[0074] Determine whether the second target distance value is greater than or equal to a preset second target distance threshold, and when it is determined that the second target distance value is greater than or equal to the preset second target distance threshold, determine at least one second target transmission node according to the second target distance value; and analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to all the second target transmission nodes and the second target distance value;

[0075] When it is determined that the second target distance value is less than the preset second target distance threshold, the expected transmission link is determined as the target transmission link of the computing power node, and based on all the transmission efficiency range information, the computing power transmission mode information of the target transmission link is analyzed.

[0076] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the analysis module determines at least one second target transmission node according to the second target distance value includes:

[0077] For each of the transmission efficiency range information, calculating a third target distance value between the transmission efficiency range information and the required transmission efficiency range information, wherein the third target distance value is used to indicate a degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information;

[0078] According to all the third target distance values, determine at least one third target transmission node among all the first target transmission nodes, the third target distance value of the third target transmission node being greater than or equal to a third target distance threshold, and the third target distance threshold being determined according to the second target distance value;

[0079] For each of the third target transmission nodes, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node.

[0080] A third aspect of the present invention discloses another task processing device for a computing power node, the device comprising:

[0081] A memory storing executable program code;

[0082] a processor coupled to the memory;

[0083] The processor calls the executable program code stored in the memory to execute the task processing method of the computing power node disclosed in the first aspect of the present invention.

[0084] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the task processing method of the computing power node disclosed in the first aspect of the present invention.

[0085] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0086] In an embodiment of the present invention, computing power resource demand information of a computing power node is obtained; based on the computing power resource demand information, an expected transmission link of the computing power node is analyzed, the expected transmission link includes an expected computing power transmission link and an expected task processing transmission link, the expected computing power transmission link includes a computing power node and an expected computing power resource node of the computing power node, and the expected task processing transmission link includes a computing power node and a target task node of the computing power node; at least one first target transmission node in the expected transmission link is determined, the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to a set of application scenarios of the first target transmission node; for each first target transmission node, based on the first multi-dimensional attribute information of the first target transmission node, the transmission efficiency range information of the first target transmission node within a preset first time period is predicted; based on the computing power resource demand information, all transmission efficiency range information and the expected transmission link, the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link are analyzed, the target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node. It can be seen that the implementation of the present invention can analyze the expected transmission links of the computing power nodes including the expected computing power transmission links and the expected task processing transmission links according to the acquired computing power resource demand information, thereby determining the computing power nodes and the target task nodes, as well as the computing power nodes and the expected computing power resource nodes, by determining at least one first target transmission node in the above-mentioned expected transmission links, and based on the first multi-dimensional attribute information of each first target transmission node, predicting the transmission efficiency range information of each first target transmission node within a preset first time period, thereby improving the comprehensiveness and accuracy of the understanding and analysis of the expected transmission links of the computing power nodes, and facilitating further understanding of the transmission capacity and potential bottlenecks of the transmission nodes of the expected transmission links, according to the computing power resource demand information , all transmission efficiency range information and expected transmission links, analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link used to indicate the dynamic transmission mode of the computing power resources of the computing power node, so as to dynamically adjust the task processing full link of the computing power node including the computing power resource transmission link and the task processing transmission link in combination with the computing power resource demand information, improve the analysis and generation accuracy of the target transmission link, improve the allocation flexibility and accuracy of computing power resources and the utilization efficiency of computing power resources, and further improve the task processing efficiency, accuracy and stability of computing power resources, so that the computing power node can adapt to more dimensional application scenarios and task requirements, and improve the task processing response efficiency and robustness of the computing power node. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0088] Figure 1 It is a flowchart of a task processing method of a computing power node disclosed in an embodiment of the present invention;

[0089] Figure 2 It is a flowchart of another task processing method of a computing power node disclosed in an embodiment of the present invention;

[0090] Figure 3 It is a structural schematic diagram of a task processing device of a computing power node disclosed in an embodiment of the present invention;

[0091] Figure 4 It is a structural schematic diagram of another task processing device of a computing power node disclosed in an embodiment of the present invention;

[0092] Figure 5 It is a structural diagram of a task processing device of another computing power node disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0093] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 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 creative work are within the scope of protection of the present invention.

[0094] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0095] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0096] The present invention discloses a task processing method and device for a computing power node, which can analyze the expected transmission links of the computing power node including the expected computing power transmission link and the expected task processing transmission link according to the acquired computing power resource demand information, so as to determine the computing power node and the target task node, as well as the computing power node and the expected computing power resource node, by determining at least one first target transmission node in the above-mentioned expected transmission link, and based on the first multi-dimensional attribute information of each first target transmission node, predicting the transmission efficiency range information of each first target transmission node in a preset first time period, thereby improving the comprehensiveness and accuracy of the understanding and analysis of the expected transmission link of the computing power node, facilitating further understanding of the transmission capacity and potential bottlenecks of the transmission node of the expected transmission link, and according to the computing power resource demand information, predicting the transmission efficiency range information of each first target transmission node in a preset first time period, and predicting the transmission efficiency range information of each first target transmission node in a preset first time period, thereby improving the comprehensiveness and accuracy of the understanding and analysis of the expected transmission link of the computing power node, and facilitating further understanding of the transmission capacity and potential bottlenecks of the transmission node of the expected transmission link, and predicting the transmission efficiency range information of each first target transmission node in a preset first time period ... The computing resource demand information, all transmission efficiency range information and expected transmission links are analyzed, and the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link used to indicate the dynamic transmission mode of the computing power resources of the computing power node are analyzed, so that the computing power resource demand information can be combined to dynamically adjust the task processing full link of the computing power node including the computing power resource transmission link and the task processing transmission link, improve the analysis and generation accuracy of the target transmission link, improve the allocation flexibility and accuracy of computing power resources and the utilization efficiency of computing power resources, and further improve the task processing efficiency, accuracy and stability of computing power resources, so that the computing power node can adapt to more dimensional application scenarios and task requirements, and improve the task processing response efficiency and robustness of the computing power node. The following are detailed explanations.

[0097] Embodiment 1

[0098] See also Figure 1 , Figure 1 1 is a flow chart of a task processing method of a computing node disclosed in an embodiment of the present invention. Figure 1 The task processing method of the computing power node described can be applied to computing power node devices. The computing power node devices are different from computing power resource devices. They can have basic data processing capabilities. They can also be applied to intelligent devices related to computing power node devices, including but not limited to cloud devices, edge computing devices, relay devices, base station devices, city management devices, intelligent network devices, and smart home devices. One or more of these are not limited in the embodiments of the present invention. Figure 1 As shown, the task processing method of the computing power node may include the following operations:

[0099] 101. Obtain computing resource demand information of computing nodes;

[0100] In the embodiment of the present invention, optionally, the computing resource demand information may be obtained by sensing the computing nodes, specifically, by detecting the real-time data of the computing nodes, or by actively uploading the objects corresponding to the computing nodes, wherein the objects may include but are not limited to one or more of a person, a unit, a terminal device, etc.;

[0101] In an embodiment of the present invention, as an optional implementation manner, before obtaining the computing resource demand information of the computing node, the method further includes:

[0102] Obtain target task information of the computing power node and first status information of the computing power node, the target task information includes task content information and task node information, the task node information is used to indicate the task process node status, and the task node information includes task time node information and task docking object node information;

[0103] Analyze task preparation information of the computing power node according to the task content information and the first status information, where the task preparation information is used to indicate the preparation status of the computing power node for the target task information;

[0104] Prediction task preparation information preparation time information, preparation time information is used to indicate the time consumption of the computing power node for the preparation of the target task information;

[0105] According to the preparation time information and task node information, predict the current processing time information of the computing power resources for the target task information;

[0106] Calculating a first target distance value between the current processing time information and the task node information, the first target distance value is used to indicate the degree of mismatch between the current processing time information and the task node information;

[0107] According to the first target distance value and task preparation information, the computing resource demand information of the computing power node is analyzed.

[0108] In the embodiment of the present invention, optionally, the computing power node itself also needs to have a certain data processing capability, so the above-mentioned first status information includes but is not limited to computing resource status information (such as: CPU usage rate, main frequency, idle rate, etc., information reflecting the computing capability of the node; remaining capacity, usage rate, read and write speed, etc. of the memory, information affecting the data processing capability of the node; capacity, remaining space, read and write speed, etc. of the disk, information determining the data storage capability of the node), bandwidth status information, network delay information, connection status information, task queue information, task load information, energy consumption information, physical environment information, security protection information, intrusion detection information, operating system information, software configuration information, health status information, at least one of fault information;

[0109] Further optionally, the task preparation information may specifically include storage space information, running memory information, configuration information, etc. required to complete the target task corresponding to the target task information.

[0110] It can be seen that the implementation of this optional embodiment can further analyze the task preparation information of the computing power node used to represent the preparation status of the computing power node for the target task information based on the acquired target task information of the computing power node and the above-mentioned multi-dimensional optional first status information of the computing power node, and then predict the preparation timeliness information of the above-mentioned task preparation information, and predict the current processing time information of the computing power resources for the target task information based on the preparation timeliness information and the task node information; calculate the first target distance value used to represent the degree of mismatch between the current processing time information and the task node information, and analyze the computing power resource demand information of the computing power node based on the first target distance value and the task preparation information, which can further improve the degree of automation, scientificity and comprehensiveness of the analysis of the computing power resource demand information, and is conducive to further improving the task processing accuracy and efficiency of the computing power nodes.

[0111] 102. Analyze the expected transmission link of the computing power node according to the computing power resource demand information. The expected transmission link includes the expected computing power transmission link and the expected task processing transmission link. The expected computing power transmission link includes the computing power node and the expected computing power resource node of the computing power node. The expected task processing transmission link includes the computing power node and the target task node of the computing power node.

[0112] In an embodiment of the present invention, as an optional implementation mode, the above-mentioned analyzing the expected transmission link of the computing power node according to the computing power resource demand information includes:

[0113] According to the computing power resource demand information, first attribute information of the computing power node and second attribute information of the target task node of the computing power node are analyzed, where the first attribute information includes at least one of current node processing efficiency information, computing power resource application cost information, first location information, to-be-processed data volume information, to-be-processed data type information, to-be-processed data conversion logic information, and first network environment information, and the second attribute information includes at least one of second location information and second network environment information;

[0114] Analyze the third attribute information of the computing power node according to the first attribute information, where the third attribute information includes at least one of the required computing power resource type information, required computing power resource amount information, required computing power resource application scenario information, and computing power demand change trend information, where the computing power demand change trend information is used to indicate the change trajectory of the computing power node's demand for computing power resources within a preset second time period;

[0115] According to the third attribute information and the second attribute information, the expected transmission link of the computing power node is analyzed.

[0116] In the embodiment of the present invention, optionally, the current node processing efficiency information is used to indicate the task processing efficiency of the computing node in the current process, and the computing resource application cost information is used to indicate the computing resource application budget cost of the computing node;

[0117] It can be seen that the implementation of this optional embodiment can analyze the computing power node's multi-dimensional optional first attribute information including at least one of the current node processing efficiency information, computing power resource application cost information, first position information, data volume information to be processed, data type information to be processed, data conversion logic information to be processed, and first network environment information according to the analyzed computing power resource demand information, and the target task node's multi-dimensional optional second attribute information including at least one of the second position information and second network environment information, thereby improving the accuracy and comprehensiveness of the understanding and analysis of the computing power nodes and the target task nodes. According to the above-mentioned first attribute information, the computing power node's multi-dimensional optional third attribute information including at least one of the required computing power resource type information, required computing power resource volume information, required computing power resource application scenario information, and computing power demand change trend information is analyzed. By further combining the second attribute information, the expected transmission link of the computing power node is analyzed to improve the analysis accuracy and automation of the expected transmission link of the computing power node.

[0118] 103. Determine at least one first target transmission node in the expected transmission link, where the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node;

[0119] In the embodiment of the present invention, optionally, the first target transmission node mentioned above may specifically be a relay or transmission node capable of ensuring stable and secure data transmission.

[0120] In the embodiment of the present invention, as another optional implementation manner, the above-mentioned determining at least one first target transmission node in the expected transmission link includes:

[0121] Determine at least one transmission node and a transmission node sequence set in the expected transmission link, where the transmission node sequence set is used to represent the data processing order of all transmission nodes in the expected transmission link and the data processing logic of the expected transmission link;

[0122] For each transmission node, the first data processing range information of the transmission node is determined according to the transmission node sequence set; the second state information of the transmission node and the application scenario set of the transmission node are obtained, and the application scenario set includes at least one application scenario of the transmission node; the second data processing range information of the transmission node is analyzed according to the second state information and the application scenario set; it is determined whether the second data processing range information matches the first data processing range information, and when it is determined that the second data processing range information matches the first data processing range information, the transmission node is determined as the first target transmission node.

[0123] In the embodiment of the present invention, it should be noted that the above-mentioned first data processing range information is determined based on a transmission node sequence set for each transmission node in the determined expected transmission link, which is used to represent the data processing sorting situation of all transmission nodes in the expected transmission link and the data processing logic situation of the expected transmission link, that is, it can be understood that the first data processing range information is used to represent the data processing range situation that the transmission node should theoretically reach in the expected transmission link. Similarly, the second data processing range information is obtained based on obtaining the second state information of the transmission node for representing its state and different from the first state information and the application scenario set of the transmission node including at least one application scenario of the transmission node. That is, it can be understood that the second data processing range information is used to represent the actual data processing range situation of the transmission node;

[0124] In the embodiment of the present invention, the above-mentioned application scenarios include but are not limited to application scenarios such as education, medical treatment, industry, and transportation. Specifically, they may include but are not limited to application scenarios such as big data analysis and real-time communication.

[0125] It can be seen that the implementation of this optional embodiment can determine whether the transmission node is the first target transmission node by judging whether the data processing range that the transmission node should theoretically achieve in the expected transmission link matches the actual data processing range of the transmission node, that is, whether the transmission node has the above-mentioned optional characteristics of ensuring stable and secure data transmission, which can improve the analysis efficiency of further understanding the transmission capacity and potential bottlenecks of the transmission node of the expected transmission link, which is conducive to improving the analysis and generation efficiency of the target transmission link, and also improves the allocation and utilization efficiency of computing resources.

[0126] 104. For each first target transmission node, predict the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node;

[0127] In this optional embodiment, as an optional implementation manner, the above-mentioned predicting, for each first target transmission node, the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node includes:

[0128] Analyze first multi-dimensional attribute information of the first target transmission node according to the second data processing range information of the first target transmission node, where the first multi-dimensional attribute information includes at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information;

[0129] Determine environmental information within a preset range of the first target transmission node within a preset first time period;

[0130] Analyze at least one interference factor of the first target transmission node according to the environmental information, where the interference factor is used to represent the interference factor to the first target transmission node within a preset range and in a preset first time period;

[0131] Calculate the interference target value of the first target transmission node according to all interference factors, where the interference target value is used to indicate the interference degree of all interference factors within a preset range on the first target transmission node in a preset first time period;

[0132] Calculate, according to the interference target value, second multi-dimensional attribute information of the first target transmission node in a preset first time period, where the second multi-dimensional attribute information corresponds to the first multi-dimensional attribute information;

[0133] According to the second multi-dimensional attribute information, the transmission efficiency range information of the first target transmission node within a preset first time period is predicted.

[0134] In an embodiment of the present invention, optionally, the above-mentioned first multi-dimensional attribute information may also include but is not limited to at least one of type information determined based on different application scenarios, network topology information of nodes, communication protocol information, broadband network information, packet loss rate information, delay information, jitter information, access control information, data encryption information, and data processing logic information.

[0135] In the embodiment of the present invention, optionally, the above-mentioned transmission efficiency range information may include key indicators such as maximum transmission speed, average transmission speed, and transmission delay;

[0136] It can be seen that the implementation of this optional embodiment can further analyze the multi-dimensional optional first multi-dimensional attribute information of each first target transmission node including at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information according to the second data processing range information of each first target transmission node analyzed as above, thereby improving the comprehensiveness and accuracy of the analysis and understanding of the first target transmission node, and by determining the environmental information within a preset range of each first target transmission node in a preset first time period, analyzing at least one interference factor used to represent the interference factor to the first target transmission node within the preset range in the preset first time period, thereby further improving the comprehensiveness and accuracy of the analysis and understanding of the first target transmission node, and calculating, based on all interference factors, the environmental information used to represent all interference factors within the preset range in the preset first time period. An interference target value of each first target transmission node is used to determine the degree of interference to the first target transmission node in a time period. According to the interference target value, second multi-dimensional attribute information corresponding to the first multi-dimensional attribute information in a preset first time period of each first target transmission node is calculated to obtain the actual multi-dimensional attribute information of the first target transmission node within a preset range, a preset first time period, and under the background of interference factors to the first target transmission node. Then, according to the second multi-dimensional attribute information, the transmission efficiency range information of the first target transmission node in the preset first time period is predicted, so as to improve the comprehensiveness and accuracy of the understanding and analysis of each first target transmission node, and improve the accuracy of the analysis of the transmission capacity and potential bottlenecks of the transmission nodes of the expected transmission link, which is conducive to further improving the accuracy of the analysis and generation of the target transmission link, and is conducive to improving the accuracy and stability of the task processing of the computing power nodes.

[0137] 105. According to the computing power resource demand information, all transmission efficiency range information and the expected transmission link, the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link are analyzed. The target transmission link corresponds to the expected transmission link. The computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node.

[0138] In an embodiment of the present invention, optionally, the above-mentioned target transmission link corresponds to the expected transmission link, that is, the above-mentioned target transmission link includes a target computing power transmission link and a target task processing transmission link, wherein the target computing power transmission link includes a computing power node and a target computing power resource node of the computing power node, and the target task processing transmission link includes a computing power node and a target task node of the computing power node. It should be noted that the target task node at this time may also be different from the target task node in the above-mentioned expected transmission link, but when different, a direct or indirect connection relationship needs to exist between the two nodes, which is specifically related to the actual application scenario, and the embodiment of the present invention does not make specific limitations on this.

[0139] In the embodiment of the present invention, optionally, the above-mentioned target transmission link may not be limited to one. When there are multiple links, the above-mentioned target computing power transmission link and / or target task processing transmission link may be multiple. Furthermore, the dynamic transmission mode of computing power resources may also be one or more dynamic transmission modes such as block transmission, stream transmission, and time-sharing transmission. In the embodiment of the present invention, the above-mentioned limitation is the dynamic transmission of computing power resources, that is, the process of transmitting computing power resources to computing power nodes through the target computing power transmission link. However, the actual transmission may not be a resource transmission at the physical level, but may be a fixed-point transmission of data, which is essentially a resource allocation. It is related to the actual application scenario, and the embodiment of the present invention does not make specific limitations on this.

[0140] Furthermore, the target task processing transmission link mentioned above may also have a dynamic transmission mode, that is, dynamically transmit task data, specifically, it may correspond to the dynamic transmission mode of computing power resources mentioned above.

[0141] It can be seen that the implementation of the embodiment of the present invention can analyze the expected transmission links of the computing power nodes including the expected computing power transmission links and the expected task processing transmission links according to the acquired computing power resource demand information, thereby determining the computing power nodes and the target task nodes, as well as the computing power nodes and the expected computing power resource nodes, by determining at least one first target transmission node in the above-mentioned expected transmission links, and based on the first multi-dimensional attribute information of each first target transmission node, predicting the transmission efficiency range information of each first target transmission node in a preset first time period, thereby improving the comprehensiveness and accuracy of the understanding and analysis of the expected transmission links of the computing power nodes, and facilitating further understanding of the transmission capacity and potential bottlenecks of the transmission nodes of the expected transmission links, and according to the computing power resource demand information The computing power node can obtain information about the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link used to indicate the dynamic transmission mode of the computing power resources of the computing power node, so as to dynamically adjust the task processing full link of the computing power node including the computing power resource transmission link and the task processing transmission link in combination with the computing power resource demand information, improve the analysis and generation accuracy of the target transmission link, improve the allocation flexibility and accuracy of computing power resources and the utilization efficiency of computing power resources, and further improve the task processing efficiency, accuracy and stability of computing power resources, so that the computing power node can adapt to more dimensional application scenarios and task requirements, and improve the task processing response efficiency and robustness of the computing power node.

[0142] Embodiment 2

[0143] See also Figure 2 , Figure 2 1 is a flow chart of another task processing method of a computing node disclosed in an embodiment of the present invention. Figure 2 The task processing method of the computing node described can be applied to computing node devices, which can have basic data processing capabilities, and can also be applied to intelligent devices related to computing node devices, such as but not limited to cloud devices, edge computing devices, relay devices, base station devices, city management devices, intelligent network devices, and smart home devices. The embodiments of the present invention do not limit this. Figure 2 As shown, the task processing method of the computing power node may include the following operations:

[0144] 201. Obtain computing resource demand information of computing nodes;

[0145] 202. Analyze the expected transmission link of the computing power node according to the computing power resource demand information. The expected transmission link includes an expected computing power transmission link and an expected task processing transmission link. The expected computing power transmission link includes the computing power node and the expected computing power resource node of the computing power node. The expected task processing transmission link includes the computing power node and the target task node of the computing power node.

[0146] 203. Determine at least one first target transmission node in the expected transmission link, where the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node;

[0147] 204. For each first target transmission node, predict the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node;

[0148] In the embodiment of the present invention, for the supplementary description of step 201 to step 204, please refer to the supplementary description of step 101 to step 104 in the first embodiment, and the embodiment of the present invention will not elaborate on this.

[0149] 205. Analyze the required transmission efficiency range information of the computing power node for the expected transmission link according to the computing power resource demand information;

[0150] 206. Generate actual transmission efficiency range information of the expected transmission link according to all transmission efficiency range information;

[0151] 207. Calculate a second target distance value between the actual transmission efficiency range information and the required transmission efficiency range information, where the second target distance value is used to indicate a mismatch between the actual transmission efficiency range information and the required transmission efficiency range information;

[0152] 208. Determine whether the second target distance value is greater than or equal to a preset second target distance threshold. When it is determined that the second target distance value is greater than or equal to the preset second target distance threshold, step 209 and step 210 are triggered to execute; when it is determined that the second target distance value is less than the preset second target distance threshold, step 211 and step 212 are triggered to execute;

[0153] 209. Determine at least one second target transmission node according to the second target distance value;

[0154] In the embodiment of the present invention, as an optional implementation manner, the determining at least one second target transmission node according to the second target distance value includes:

[0155] For each transmission efficiency range information, a third target distance value between the transmission efficiency range information and the required transmission efficiency range information is calculated, where the third target distance value is used to indicate the degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information;

[0156] According to all the third target distance values, determine at least one third target transmission node among all the first target transmission nodes, the third target distance value of the third target transmission node is greater than or equal to a third target distance threshold, and the third target distance threshold is determined according to the second target distance value;

[0157] For each third target transmission node, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node.

[0158] It can be seen that the implementation of this optional embodiment can, when it is judged that the second target distance value is greater than or equal to the preset second target distance threshold, calculate the third target distance value used to represent the degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information based on the predicted transmission efficiency range information of each first target transmission node in the preset first time period, and determine at least one third target transmission node among all first target transmission nodes according to all third target distance values, the third target distance value of the third target transmission node is greater than or equal to the third target distance threshold, and the third target distance threshold is determined according to the second target distance value; thereby improving the recognition accuracy of the transmission node and the exchange control accuracy of the transmission node, for each third target transmission node, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node, which can further improve the analysis and generation accuracy of the target transmission link while improving the analysis and generation efficiency of the target transmission link, thereby improving the task processing efficiency of the computing power node, which is conducive to improving the actual task processing experience and sense of security of the user.

[0159] 210. Analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to all the second target transmission nodes and the second target distance values;

[0160] 211. Determine the expected transmission link as the target transmission link of the computing power node;

[0161] 212. Based on all transmission efficiency range information, analyze the computing power transmission mode information of the target transmission link; wherein the target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node.

[0162] It can be seen that the implementation of the embodiment of the present invention can specifically predict the transmission efficiency range information of each first target transmission node within the preset first time period, and then calculate the second target distance value used to represent the mismatch between the actual transmission efficiency range information of the expected transmission link and the required transmission efficiency range information of the expected transmission link analyzed based on the computing power resource demand information, so as to determine the target transmission link of the computing power node including the above-mentioned target computing power transmission link and the target task processing transmission link and its computing power transmission mode information, thereby improving the analysis and generation efficiency of the target transmission link. Simultaneously, when it is judged that the second target distance value is greater than or equal to the preset second target distance threshold, at least one second target transmission node is determined according to the second target distance value, and the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link are analyzed according to all the second target transmission nodes and the second target distance values, thereby improving the analysis and generation accuracy of the target transmission link, improving the allocation flexibility and accuracy of computing power resources and the utilization efficiency of computing power resources, and further improving the task processing efficiency, accuracy and stability of computing power resources, so that the computing power node can adapt to more dimensional application scenarios and task requirements, and improve the task processing response efficiency and robustness of the computing power node.

[0163] Embodiment 3

[0164] See also Figure 3 , Figure 3 It is a structural diagram of a task processing device of a computing node disclosed in an embodiment of the present invention. The task processing device of the computing node can be applied to a computing node device, which can have basic data processing capabilities, and can also be applied to intelligent devices related to computing node devices, which include but are not limited to cloud devices, edge computing devices, relay devices, base station devices, city management devices, intelligent network devices, and one or more of smart home devices, which are not limited in the embodiment of the present invention. Figure 3 As shown, the task processing device of the computing power node may include:

[0165] The acquisition module 301 is used to obtain the computing resource demand information of the computing node;

[0166] The analysis module 302 is used to analyze the expected transmission link of the computing power node according to the computing power resource demand information, the expected transmission link includes the expected computing power transmission link and the expected task processing transmission link, the expected computing power transmission link includes the computing power node and the expected computing power resource node of the computing power node, and the expected task processing transmission link includes the computing power node and the target task node of the computing power node;

[0167] A determination module 303 is used to determine at least one first target transmission node in the desired transmission link, where the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node;

[0168] A prediction module 304 is configured to predict, for each first target transmission node, transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node;

[0169] The analysis module 302 is also used to analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link based on the computing power resource demand information, all transmission efficiency range information and the expected transmission link. The target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node.

[0170] It can be seen that the implementation of the embodiment of the present invention can analyze the expected transmission links of the computing power nodes including the expected computing power transmission links and the expected task processing transmission links according to the acquired computing power resource demand information, thereby determining the computing power nodes and the target task nodes, as well as the computing power nodes and the expected computing power resource nodes, by determining at least one first target transmission node in the above-mentioned expected transmission links, and based on the first multi-dimensional attribute information of each first target transmission node, predicting the transmission efficiency range information of each first target transmission node in a preset first time period, thereby improving the comprehensiveness and accuracy of the understanding and analysis of the expected transmission links of the computing power nodes, and facilitating further understanding of the transmission capacity and potential bottlenecks of the transmission nodes of the expected transmission links, and according to the computing power resource demand information The computing power node can obtain information about the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link used to indicate the dynamic transmission mode of the computing power resources of the computing power node, so as to dynamically adjust the task processing full link of the computing power node including the computing power resource transmission link and the task processing transmission link in combination with the computing power resource demand information, improve the analysis and generation accuracy of the target transmission link, improve the allocation flexibility and accuracy of computing power resources and the utilization efficiency of computing power resources, and further improve the task processing efficiency, accuracy and stability of computing power resources, so that the computing power node can adapt to more dimensional application scenarios and task requirements, and improve the task processing response efficiency and robustness of the computing power node.

[0171] In the embodiment of the present invention, as an optional implementation, the above-mentioned acquisition module 301 is also used to obtain the target task information of the computing power node and the first state information of the computing power node before the acquisition module 301 obtains the computing power resource demand information of the computing power node, the target task information includes task content information and task node information, the task node information is used to indicate the task process node situation, and the task node information includes task time node information and task docking object node information;

[0172] The analysis module 302 is further used to analyze the task preparation information of the computing power node according to the task content information and the first state information, where the task preparation information is used to indicate the preparation status of the computing power node for the target task information;

[0173] The prediction module 304 is also used to predict the preparation timeliness information of the task preparation information, and the preparation timeliness information is used to indicate the time consumption of the preparation work of the computing power node for the target task information;

[0174] The prediction module 304 is further used to predict the current processing time information of the computing power resources for the target task information according to the preparation time information and the task node information;

[0175] Optional, such as Figure 4 As shown, the device also includes:

[0176] A calculation module 305, used to calculate a first target distance value between the current processing time information and the task node information, the first target distance value being used to indicate a mismatch degree between the current processing time information and the task node information;

[0177] The analysis module 302 is also used to analyze the computing resource demand information of the computing node based on the first target distance value and the task preparation information.

[0178] It can be seen that the implementation of this optional embodiment can further analyze the task preparation information of the computing power node used to represent the preparation status of the computing power node for the target task information based on the acquired target task information of the computing power node and the above-mentioned multi-dimensional optional first status information of the computing power node, and then predict the preparation timeliness information of the above-mentioned task preparation information, and predict the current processing time information of the computing power resources for the target task information based on the preparation timeliness information and the task node information; calculate the first target distance value used to represent the degree of mismatch between the current processing time information and the task node information, and analyze the computing power resource demand information of the computing power node based on the first target distance value and the task preparation information, which can further improve the degree of automation, scientificity and comprehensiveness of the analysis of the computing power resource demand information, and is conducive to further improving the task processing accuracy and efficiency of the computing power nodes.

[0179] In the embodiment of the present invention, as another optional implementation, the specific manner in which the above-mentioned analysis module 302 analyzes the expected transmission link of the computing power node according to the computing power resource demand information includes:

[0180] According to the computing power resource demand information, first attribute information of the computing power node and second attribute information of the target task node of the computing power node are analyzed, where the first attribute information includes at least one of current node processing efficiency information, computing power resource application cost information, first location information, to-be-processed data volume information, to-be-processed data type information, to-be-processed data conversion logic information, and first network environment information, and the second attribute information includes at least one of second location information and second network environment information;

[0181] Analyze the third attribute information of the computing power node according to the first attribute information, where the third attribute information includes at least one of the required computing power resource type information, required computing power resource amount information, required computing power resource application scenario information, and computing power demand change trend information, where the computing power demand change trend information is used to indicate the change trajectory of the computing power node's demand for computing power resources within a preset second time period;

[0182] According to the third attribute information and the second attribute information, the expected transmission link of the computing power node is analyzed.

[0183] It can be seen that the implementation of this optional embodiment can analyze the computing power node's multi-dimensional optional first attribute information including at least one of the current node processing efficiency information, computing power resource application cost information, first position information, data volume information to be processed, data type information to be processed, data conversion logic information to be processed, and first network environment information according to the analyzed computing power resource demand information, and the target task node's multi-dimensional optional second attribute information including at least one of the second position information and second network environment information, thereby improving the accuracy and comprehensiveness of the understanding and analysis of the computing power nodes and the target task nodes. According to the above-mentioned first attribute information, the computing power node's multi-dimensional optional third attribute information including at least one of the required computing power resource type information, required computing power resource volume information, required computing power resource application scenario information, and computing power demand change trend information is analyzed. By further combining the second attribute information, the expected transmission link of the computing power node is analyzed to improve the analysis accuracy and automation of the expected transmission link of the computing power node.

[0184] In the embodiment of the present invention, as another optional implementation, the specific manner in which the above-mentioned determination module 303 determines at least one first target transmission node in the desired transmission link includes:

[0185] Determine at least one transmission node and a transmission node sequence set in the expected transmission link, where the transmission node sequence set is used to represent the data processing order of all transmission nodes in the expected transmission link and the data processing logic of the expected transmission link;

[0186] For each transmission node, the first data processing range information of the transmission node is determined according to the transmission node sequence set; the second state information of the transmission node and the application scenario set of the transmission node are obtained, and the application scenario set includes at least one application scenario of the transmission node; the second data processing range information of the transmission node is analyzed according to the second state information and the application scenario set; it is determined whether the second data processing range information matches the first data processing range information, and when it is determined that the second data processing range information matches the first data processing range information, the transmission node is determined as the first target transmission node.

[0187] It can be seen that the implementation of this optional embodiment can determine whether the transmission node is the first target transmission node by judging whether the data processing range that the transmission node should theoretically achieve in the expected transmission link matches the actual data processing range of the transmission node, that is, whether the transmission node has the above-mentioned optional characteristics of ensuring stable and secure data transmission, which can improve the analysis efficiency of further understanding the transmission capacity and potential bottlenecks of the transmission node of the expected transmission link, which is conducive to improving the analysis and generation efficiency of the target transmission link, and also improves the allocation and utilization efficiency of computing resources.

[0188] In this optional embodiment, as an optional implementation manner, the specific manner in which the prediction module 304 predicts the transmission efficiency range information of the first target transmission node within the preset first time period according to the first multi-dimensional attribute information of the first target transmission node for each first target transmission node includes:

[0189] Analyze first multi-dimensional attribute information of the first target transmission node according to the second data processing range information of the first target transmission node, where the first multi-dimensional attribute information includes at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information;

[0190] Determine environmental information within a preset range of the first target transmission node within a preset first time period;

[0191] Analyze at least one interference factor of the first target transmission node according to the environmental information, where the interference factor is used to represent the interference factor to the first target transmission node within a preset range and in a preset first time period;

[0192] Calculate the interference target value of the first target transmission node according to all interference factors, where the interference target value is used to indicate the interference degree of all interference factors within a preset range on the first target transmission node in a preset first time period;

[0193] Calculate, according to the interference target value, second multi-dimensional attribute information of the first target transmission node in a preset first time period, where the second multi-dimensional attribute information corresponds to the first multi-dimensional attribute information;

[0194] According to the second multi-dimensional attribute information, the transmission efficiency range information of the first target transmission node within a preset first time period is predicted.

[0195] It can be seen that the implementation of this optional embodiment can further analyze the multi-dimensional optional first multi-dimensional attribute information of each first target transmission node including at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information according to the second data processing range information of each first target transmission node analyzed as above, thereby improving the comprehensiveness and accuracy of the analysis and understanding of the first target transmission node, and by determining the environmental information within a preset range of each first target transmission node in a preset first time period, analyzing at least one interference factor used to represent the interference factor to the first target transmission node within the preset range in the preset first time period, thereby further improving the comprehensiveness and accuracy of the analysis and understanding of the first target transmission node, and calculating, based on all interference factors, the environmental information used to represent all interference factors within the preset range in the preset first time period. An interference target value of each first target transmission node is used to determine the degree of interference to the first target transmission node in a time period. According to the interference target value, second multi-dimensional attribute information corresponding to the first multi-dimensional attribute information in a preset first time period of each first target transmission node is calculated to obtain the actual multi-dimensional attribute information of the first target transmission node within a preset range, a preset first time period, and under the background of interference factors to the first target transmission node. Then, according to the second multi-dimensional attribute information, the transmission efficiency range information of the first target transmission node in the preset first time period is predicted, so as to improve the comprehensiveness and accuracy of the understanding and analysis of each first target transmission node, and improve the accuracy of the analysis of the transmission capacity and potential bottlenecks of the transmission nodes of the expected transmission link, which is conducive to further improving the accuracy of the analysis and generation of the target transmission link, and is conducive to improving the accuracy and stability of the task processing of the computing power nodes.

[0196] In an optional embodiment, the above-mentioned analysis module 302 analyzes the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all transmission efficiency range information and the expected transmission link. The specific method includes:

[0197] According to the computing power resource demand information, analyze the required transmission efficiency range information of the computing power node for the expected transmission link;

[0198] Generating actual transmission efficiency range information of the desired transmission link according to all transmission efficiency range information;

[0199] Calculating a second target distance value between the actual transmission efficiency range information and the required transmission efficiency range information, the second target distance value being used to indicate a degree of mismatch between the actual transmission efficiency range information and the required transmission efficiency range information;

[0200] Determine whether the second target distance value is greater than or equal to a preset second target distance threshold, and when it is determined that the second target distance value is greater than or equal to the preset second target distance threshold, determine at least one second target transmission node according to the second target distance value; and analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to all the second target transmission nodes and the second target distance values;

[0201] When it is determined that the second target distance value is less than the preset second target distance threshold, the expected transmission link is determined as the target transmission link of the computing power node, and based on all transmission efficiency range information, the computing power transmission mode information of the target transmission link is analyzed.

[0202] It can be seen that the implementation of the embodiment of the present invention can specifically predict the transmission efficiency range information of each first target transmission node within the preset first time period, and then calculate the second target distance value used to represent the mismatch between the actual transmission efficiency range information of the expected transmission link and the required transmission efficiency range information of the expected transmission link analyzed based on the computing power resource demand information, so as to determine the target transmission link of the computing power node including the above-mentioned target computing power transmission link and the target task processing transmission link and its computing power transmission mode information, thereby improving the analysis and generation efficiency of the target transmission link. Simultaneously, when it is judged that the second target distance value is greater than or equal to the preset second target distance threshold, at least one second target transmission node is determined according to the second target distance value, and the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link are analyzed according to all the second target transmission nodes and the second target distance values, thereby improving the analysis and generation accuracy of the target transmission link, improving the allocation flexibility and accuracy of computing power resources and the utilization efficiency of computing power resources, and further improving the task processing efficiency, accuracy and stability of computing power resources, so that the computing power node can adapt to more dimensional application scenarios and task requirements, and improve the task processing response efficiency and robustness of the computing power node.

[0203] In this optional embodiment, as an optional implementation manner, the specific manner in which the above-mentioned analysis module 302 determines at least one second target transmission node according to the second target distance value includes:

[0204] For each transmission efficiency range information, a third target distance value between the transmission efficiency range information and the required transmission efficiency range information is calculated, where the third target distance value is used to indicate the degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information;

[0205] According to all the third target distance values, determine at least one third target transmission node among all the first target transmission nodes, the third target distance value of the third target transmission node is greater than or equal to a third target distance threshold, and the third target distance threshold is determined according to the second target distance value;

[0206] For each third target transmission node, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node.

[0207] It can be seen that the implementation of this optional embodiment can, when it is judged that the second target distance value is greater than or equal to the preset second target distance threshold, calculate the third target distance value used to represent the degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information based on the predicted transmission efficiency range information of each first target transmission node in the preset first time period, and determine at least one third target transmission node among all first target transmission nodes according to all third target distance values, the third target distance value of the third target transmission node is greater than or equal to the third target distance threshold, and the third target distance threshold is determined according to the second target distance value; thereby improving the recognition accuracy of the transmission node and the exchange control accuracy of the transmission node, for each third target transmission node, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node, which can further improve the analysis and generation accuracy of the target transmission link while improving the analysis and generation efficiency of the target transmission link, thereby improving the task processing efficiency of the computing power node, which is conducive to improving the actual task processing experience and sense of security of the user.

[0208] Embodiment 4

[0209] See also Figure 5 , Figure 5It is a structural diagram of another task processing device of a computing node disclosed in an embodiment of the present invention. The task processing device of the computing node can be applied to a computing node device, which can have basic data processing capabilities, and can also be applied to intelligent devices related to computing node devices, which include but are not limited to cloud devices, edge computing devices, relay devices, base station devices, city management devices, intelligent network devices, and one or more of smart home devices, which are not limited in the embodiment of the present invention. Figure 5 As shown, the task processing device of the computing power node may include:

[0210] The memory 401 stores executable program codes.

[0211] A processor 402 is coupled to the memory 401 .

[0212] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the task processing method of the computing power node described in the first embodiment of the present invention or the second embodiment of the present invention.

[0213] Embodiment 5

[0214] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps in the task processing method of the computing power node described in Embodiment 1 or Embodiment 2 of the present invention.

[0215] Embodiment 6

[0216] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps in the task processing method of a computing power node described in Embodiment 1 or Embodiment 2.

[0217] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0218] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0219] Finally, it should be noted that the task processing method and device of a computing node disclosed in the embodiment of the present invention only discloses the preferred embodiment of the present invention, which is 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 aforementioned embodiments, ordinary technicians in this field should understand that it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A task processing method for a computing power node, characterized in that: The method comprises: Obtain computing resource demand information of computing nodes; Analyze the expected transmission link of the computing power node according to the computing power resource demand information, the expected transmission link includes an expected computing power transmission link and an expected task processing transmission link, the expected computing power transmission link includes the computing power node and the expected computing power resource node of the computing power node, and the expected task processing transmission link includes the computing power node and the target task node of the computing power node; Determine at least one first target transmission node in the expected transmission link, where the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node; For each of the first target transmission nodes, predicting the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node; According to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link, analyzing the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link, the target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node; And, analyzing the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link, includes: Analyzing the required transmission efficiency range information of the computing power node for the expected transmission link according to the computing power resource requirement information; Generating actual transmission efficiency range information of the desired transmission link according to all the transmission efficiency range information; Calculating a second target distance value between the actual transmission efficiency range information and the required transmission efficiency range information, wherein the second target distance value is used to indicate a degree of mismatch between the actual transmission efficiency range information and the required transmission efficiency range information; Determine whether the second target distance value is greater than or equal to a preset second target distance threshold, and when it is determined that the second target distance value is greater than or equal to the preset second target distance threshold, determine at least one second target transmission node according to the second target distance value; and analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to all the second target transmission nodes and the second target distance value; When it is determined that the second target distance value is less than the preset second target distance threshold, the expected transmission link is determined as the target transmission link of the computing power node, and based on all the transmission efficiency range information, the computing power transmission mode information of the target transmission link is analyzed.

2. The task processing method of a computing node according to claim 1, characterized in that: Before obtaining the computing resource demand information of the computing node, the method further includes: Obtain target task information of a computing power node and first status information of the computing power node, wherein the target task information includes task content information and task node information, wherein the task node information is used to indicate the task process node status, and the task node information includes task time node information and task docking object node information; Analyze the task preparation information of the computing power node according to the task content information and the first status information, wherein the task preparation information is used to indicate the preparation status of the computing power node for the target task information; Predicting preparation timeliness information of the task preparation information, where the preparation timeliness information is used to indicate the time consumption of the computing power node for the preparation of the target task information; Predicting the current processing time information of the target task information by the computing resources according to the preparation time information and the task node information; Calculating a first target distance value between the current processing time information and the task node information, wherein the first target distance value is used to indicate a mismatch degree between the current processing time information and the task node information; According to the first target distance value and the task preparation information, the computing resource demand information of the computing power node is analyzed.

3. The task processing method of a computing node according to claim 1, characterized in that: The analyzing the expected transmission link of the computing power node according to the computing power resource demand information includes: According to the computing power resource demand information, analyzing the first attribute information of the computing power node and the second attribute information of the target task node of the computing power node, the first attribute information includes at least one of current node processing efficiency information, computing power resource application cost information, first location information, to-be-processed data volume information, to-be-processed data type information, to-be-processed data conversion logic information, and first network environment information, and the second attribute information includes at least one of second location information and second network environment information; According to the first attribute information, analyzing the third attribute information of the computing power node, the third attribute information includes at least one of the required computing power resource type information, the required computing power resource amount information, the required computing power resource application scenario information, and the computing power demand change trend information, the computing power demand change trend information is used to indicate the change trajectory of the computing power node's demand for computing power resources within a preset second time period; According to the third attribute information and the second attribute information, the expected transmission link of the computing power node is analyzed.

4. The task processing method of a computing node according to any one of claims 1 to 3, characterized in that: The determining at least one first target transmission node in the desired transmission link includes: Determine at least one transmission node and a transmission node sequence set in the expected transmission link, where the transmission node sequence set is used to represent data processing ordering of all the transmission nodes in the expected transmission link and data processing logic of the expected transmission link; For each of the transmission nodes, determine the first data processing range information of the transmission node according to the transmission node sequence set; obtain the second state information of the transmission node and the application scenario set of the transmission node, wherein the application scenario set includes at least one application scenario of the transmission node; analyze the second data processing range information of the transmission node according to the second state information and the application scenario set; determine whether the second data processing range information matches the first data processing range information, and when it is determined that the second data processing range information matches the first data processing range information, determine the transmission node as the first target transmission node.

5. The task processing method of computing node according to claim 4, characterized in that: For each of the first target transmission nodes, predicting the transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node includes: Analyze the first multi-dimensional attribute information of the first target transmission node according to the second data processing range information of the first target transmission node, where the first multi-dimensional attribute information includes at least one of available space information, available time period information, processing rate peak information, processing rate mean information, processing rate variance information, and delay information; Determine environmental information within a preset range of the first target transmission node within a preset first time period; Analyze at least one interference factor of the first target transmission node according to the environmental information, where the interference factor is used to represent the interference factor to the first target transmission node within the preset range in the preset first time period; Calculate an interference target value of the first target transmission node according to all the interference factors, where the interference target value is used to indicate the interference degree of all the interference factors within the preset range on the first target transmission node in a preset first time period; Calculating, according to the interference target value, second multi-dimensional attribute information of the first target transmission node in the preset first time period, where the second multi-dimensional attribute information corresponds to the first multi-dimensional attribute information; The transmission efficiency range information of the first target transmission node within the preset first time period is predicted according to the second multi-dimensional attribute information.

6. The task processing method of a computing node according to claim 1, characterized in that: The determining at least one second target transmission node according to the second target distance value includes: For each of the transmission efficiency range information, calculating a third target distance value between the transmission efficiency range information and the required transmission efficiency range information, wherein the third target distance value is used to indicate a degree of mismatch between the transmission efficiency range information and the required transmission efficiency range information; According to all the third target distance values, determine at least one third target transmission node among all the first target transmission nodes, the third target distance value of the third target transmission node being greater than or equal to a third target distance threshold, and the third target distance threshold being determined according to the second target distance value; For each of the third target transmission nodes, determine the associated node of the third target transmission node, and determine the associated node as the second target transmission node; the associated transmission efficiency range information of the associated node is greater than or equal to the transmission efficiency range information of the third target transmission node, and the associated transmission efficiency range information of the associated node corresponds to the determination method of the transmission efficiency range information of the third target transmission node.

7. A task processing device for a computing node, characterized in that: The device is used to execute the task processing method of the computing power node according to any one of claims 1 to 6, and the device includes: The acquisition module is used to obtain the computing resource demand information of the computing node; An analysis module, configured to analyze the expected transmission link of the computing power node according to the computing power resource demand information, wherein the expected transmission link includes an expected computing power transmission link and an expected task processing transmission link, wherein the expected computing power transmission link includes the computing power node and an expected computing power resource node of the computing power node, and the expected task processing transmission link includes the computing power node and a target task node of the computing power node; a determination module, configured to determine at least one first target transmission node in the desired transmission link, wherein the first target transmission node includes first multi-dimensional attribute information, and the first multi-dimensional attribute information is related to an application scenario set of the first target transmission node; A prediction module, configured to predict, for each of the first target transmission nodes, transmission efficiency range information of the first target transmission node within a preset first time period according to the first multi-dimensional attribute information of the first target transmission node; The analysis module is also used to analyze the target transmission link of the computing power node and the computing power transmission mode information of the target transmission link according to the computing power resource demand information, all the transmission efficiency range information and the expected transmission link, the target transmission link corresponds to the expected transmission link, and the computing power transmission mode information is used to indicate the dynamic transmission mode of the computing power resources of the computing power node.

8. A task processing device for a computing node, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the task processing method of the computing power node as described in any one of claims 1-6.

9. A computer storage medium, characterized in that The computer storage medium stores computer instructions, which, when called, are used to execute the task processing method of the computing power node as described in any one of claims 1-6.

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