Business-oriented computing power resource integration method and device

Abstract

The invention relates to the technical field of information, and discloses a business-oriented computing power resource integration method and device, and the method comprises the steps: determining recommended computing power resource distribution information adaptive to business attribute information according to the acquired business attribute information of a target business, the recommended computing power resource allocation information is used for indicating at least one recommended computing power resource node adapted to the service attribute information, and the recommended computing power resource node is planned to allocate computing power resources to a service platform corresponding to the target service in a time-sharing manner according to the recommended computing power resource allocation information; generating a computing power resource integration condition which is adapted to the target service and comprises at least one computing power constraint index according to the obtained service demand information of the target service; and according to the computing power resource integration condition, at least one target node is determined in all the recommended computing power resource nodes, and the computing power resource corresponding to the target node is a target computing power resource adapted to the target service. Therefore, the business-oriented computing power resource integration accuracy can be improved by implementing the business-oriented computing power resource integration method and device.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a business-oriented computing power resource integration method and device. Background Art

[0002] In today's digital age, information technology has penetrated into all walks of life and become a key driving force for users to gain competitive advantages and innovation.

[0003] However, as users' dependence on information technology continues to increase, the demand for computing power is also becoming increasingly urgent. In the practice process, due to the different levels of informatization between different businesses, the corresponding computing power requirements are also different. When users face different business scenarios, there are often situations of insufficient or redundant computing power resources. On the one hand, it causes the computing power resources to be overloaded and unable to meet the business requirements. On the other hand, some resources may be in an idle state and not fully utilized, resulting in a waste of computing power resources.

[0004] It can be seen that how to improve the accuracy of business-oriented computing power resource integration is particularly important. Summary of the Invention

[0005] The present invention provides a business-oriented computing power resource integration method and device, which can improve the accuracy of business-oriented computing power resource integration.

[0006] To solve the above technical problems, a first aspect of the present invention discloses a business-oriented computing power resource integration method, and the method includes:

[0007] According to the obtained business attribute information of the target business, determine the recommended computing power resource allocation information adapted to the business attribute information, where the recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the business attribute information, and the recommended computing power resource node is intended to allocate computing power resources to the business platform corresponding to the target business at different times according to the recommended computing power resource allocation information;

[0008] According to the obtained business demand information of the target business, generate the computing power resource integration conditions adapted to the target business, where the computing power resource integration conditions include at least one computing power constraint index;

[0009] According to the computing power resource integration conditions, determine at least one target node among all the recommended computing power resource nodes, and the computing power resources corresponding to the target node are the target computing power resources adapted to the target business.

[0010] As an alternative implementation, in the first aspect of the present invention, the service attribute information includes service process information and service scenario information. Determining recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service includes:

[0011] According to the service process information, determine the object sorting information of the target service. The target service corresponds to at least one acting object, and the acting object executes the target service based on the corresponding service platform. The object sorting information is used to sort the acting objects in the order of executing the target service;

[0012] For each acting object, according to the service scenario information, determine the task volume information of the acting object for the target service; according to the task volume information, determine the recommended computing power information of the acting object, and the recommended computing power information is used to represent the recommended computing power situation adapted to the task volume information;

[0013] According to all the recommended computing power information and the object sorting information, determine the recommended computing power resource allocation information adapted to the service attribute information.

[0014] As an alternative implementation, in the first aspect of the present invention, the service attribute information further includes service efficiency information, and the service efficiency information is used to represent the preset standard execution efficiency situation of the target service. Determining the recommended computing power information of the acting object according to the task volume information includes:

[0015] Obtain the first resource information of the acting object, and the first resource information is used to represent the first existing resource distribution situation of the acting object;

[0016] According to the first resource information and the service scenario information, determine the second resource information of the acting object, and the second resource information is used to represent the second existing resource distribution situation of the acting object for executing the target service;

[0017] According to the task volume information, the service efficiency information, the service scenario information and the second resource information, match the third resource information of the acting object, and the third resource information is used to represent the required updated resource situation of the acting object for executing the target service. The third resource information and the second resource information are matched with the service efficiency information;

[0018] According to the second resource information and the third resource information, determine the recommended computing power information of the acting object.

[0019] As an alternative implementation manner, in the first aspect of the present invention, matching the third resource information of the acting object according to the task volume information, the service efficiency information, the service scenario information, and the second resource information includes:

[0020] Analyzing the first predicted execution efficiency information of the second resource information according to the task volume information;

[0021] Analyzing the second predicted execution efficiency information of the acting object according to the service efficiency information and the first predicted execution efficiency information;

[0022] Matching the third resource information of the acting object according to the second predicted execution efficiency information and the service scenario information, and the third resource information matches the second predicted execution efficiency information.

[0023] As an alternative implementation manner, in the first aspect of the present invention, determining the recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information includes:

[0024] For each piece of the recommended computing power information, according to the required configuration information of the recommended computing power information, determining at least one target object among all the acting objects, where the target object meets the configuration conditions corresponding to the required configuration information; according to the object sorting information, matching the matching object corresponding to the recommended computing power information among all the target objects;

[0025] Determining the recommended computing power resource allocation information adapted to the service attribute information according to all the matching objects.

[0026] As an alternative implementation manner, in the first aspect of the present invention, the service demand information includes at least one of the expected coverage range information of the computing power resource node, the security demand information, the first computing power processing efficiency information, and the first service execution frequency information. Generating the computing power resource integration conditions adapted to the target service according to the obtained service demand information of the target service includes:

[0027] Analyzing the set of computing power constraint conditions adapted to the target service according to the obtained service demand information of the target service, where the set of computing power constraint conditions includes at least one computing power constraint index such as the constraint coverage range information of the computing power resource node, the security configuration information, the protocol configuration information, the resource node credibility information, the bandwidth configuration information, the sleep configuration information, the resource node stable interval configuration information, the second computing power processing efficiency information, and the second service execution frequency information. The first computing power processing efficiency information corresponds to the second computing power processing efficiency information, and the first service execution frequency information corresponds to the second service execution frequency information;

[0028] Generate computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions.

[0029] As an optional implementation manner, in the first aspect of the present invention, the generating computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions includes:

[0030] For each of the computing power constraint indicators, match a target priority value of the computing power constraint indicator according to the service attribute information and the service requirement information, where the target priority value is used to represent the influence degree of the computing power constraint indicator on the target service;

[0031] Generate computing power resource integration conditions adapted to the target service according to all the computing power constraint indicators and the corresponding target priority values;

[0032] And, the determining at least one target node from all the recommended computing power resource nodes according to the computing power resource integration conditions includes:

[0033] Calculate a screening threshold of the computing power resource node for the target service according to all the computing power constraint indicators and the corresponding target priority values;

[0034] For each of the recommended computing power resource nodes, calculate an index matching degree value of the recommended computing power resource node according to all the computing power constraint indicators, where the index matching degree value is used to represent the matching degree between the recommended computing power resource node and all the computing power constraint indicators; determine whether the index matching degree value is greater than or equal to the screening threshold of the computing power resource node, and when it is determined that the index matching degree value is greater than or equal to the screening threshold of the computing power resource node, determine that the recommended computing power resource node is a target node.

[0035] The second aspect of the present invention discloses a service-oriented computing power resource integration device, and the device includes:

[0036] A determination module, configured to determine recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service, where the recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the service attribute information, and the recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service in a time-sharing manner according to the recommended computing power resource allocation information;

[0037] A generation module, configured to generate computing power resource integration conditions adapted to the target service according to the obtained service requirement information of the target service, where the computing power resource integration conditions include at least one computing power constraint indicator;

[0038] The determining module is further configured to determine at least one target node from all the recommended computing power resource nodes according to the computing power resource integration condition, and the computing power resource corresponding to the target node is the target computing power resource adapted to the target service.

[0039] As an optional implementation manner, in the second aspect of the present invention, the service attribute information includes service process information and service scenario information. The specific manner for the determining module to determine the recommended computing power resource allocation information adapted to the service attribute information according to the service attribute information of the target service obtained is as follows:

[0040] According to the service process information, determine the object sorting information of the target service. The target service corresponds to at least one acting object, and the acting object executes the target service based on the corresponding service platform. The object sorting information is used to sort the acting objects in the order of executing the target service;

[0041] For each acting object, according to the service scenario information, determine the task volume information of the acting object for the target service; according to the task volume information, determine the recommended computing power information of the acting object, and the recommended computing power information is used to represent the recommended computing power situation adapted to the task volume information;

[0042] According to all the recommended computing power information and the object sorting information, determine the recommended computing power resource allocation information adapted to the service attribute information.

[0043] As an optional implementation manner, in the second aspect of the present invention, the service attribute information further includes service efficiency information, and the service efficiency information is used to represent the preset standard execution efficiency situation of the target service. The specific manner for the determining module to determine the recommended computing power information of the acting object according to the task volume information is as follows:

[0044] Obtain the first resource information of the acting object, and the first resource information is used to represent the first existing resource distribution situation of the acting object;

[0045] According to the first resource information and the service scenario information, determine the second resource information of the acting object, and the second resource information is used to represent the second existing resource distribution situation of the acting object for executing the target service;

[0046] According to the task volume information, the service efficiency information, the service scenario information and the second resource information, match the third resource information of the acting object, and the third resource information is used to represent the required updated resource situation of the acting object for executing the target service. The third resource information and the second resource information are matched with the service efficiency information;

[0047] Determine the recommended computing power information of the affected object according to the second resource information and the third resource information.

[0048] As an alternative implementation, in the second aspect of the present invention, the specific manner in which the determination module matches the third resource information of the affected object according to the task amount information, the service efficiency information, the service scenario information, and the second resource information includes:

[0049] Analyze the first predicted execution efficiency information of the second resource information according to the task amount information;

[0050] Analyze the second predicted execution efficiency information of the affected object according to the service efficiency information and the first predicted execution efficiency information;

[0051] Match the third resource information of the affected object according to the second predicted execution efficiency information and the service scenario information, and the third resource information matches the second predicted execution efficiency information.

[0052] As an alternative implementation, in the second aspect of the present invention, the specific manner in which the determination module determines the recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information includes:

[0053] For each piece of the recommended computing power information, according to the required configuration information of the recommended computing power information, determine at least one target object among all the affected objects, where the target object satisfies the configuration conditions corresponding to the required configuration information; according to the object sorting information, match the matching object corresponding to the recommended computing power information among all the target objects;

[0054] Determine the recommended computing power resource allocation information adapted to the service attribute information according to all the matching objects.

[0055] As an alternative implementation, in the second aspect of the present invention, the service requirement information includes at least one of the expected coverage range information of the computing power resource node, the security requirement information, the first computing power processing efficiency information, and the first service execution frequency information. The specific manner in which the generation module generates the computing power resource integration conditions adapted to the target service according to the obtained service requirement information of the target service includes:

[0056] According to the business requirement information of the target service obtained, analyze the set of computing power constraint conditions adapted to the target service. The set of computing power constraint conditions includes at least one computing power constraint index such as the constraint coverage range information of the computing power resource node, security configuration information, protocol configuration information, resource node credibility information, bandwidth configuration information, sleep configuration information, resource node stable interval configuration information, second computing power processing efficiency information, and second service execution frequency information. The first computing power processing efficiency information corresponds to the second computing power processing efficiency information, and the first service execution frequency information corresponds to the second service execution frequency information;

[0057] Generate computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions.

[0058] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the generation module generates computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions includes:

[0059] For each of the computing power constraint indexes, match the target priority value of the computing power constraint index according to the service attribute information and the business requirement information. The target priority value is used to represent the influence degree of the computing power constraint index on the target service;

[0060] Generate computing power resource integration conditions adapted to the target service according to all the computing power constraint indexes and the corresponding target priority values;

[0061] Moreover, the specific manner in which the determination module determines at least one target node among all the recommended computing power resource nodes according to the computing power resource integration conditions includes:

[0062] Calculate the screening threshold of the computing power resource node of the target service according to all the computing power constraint indexes and the corresponding target priority values;

[0063] For each of the recommended computing power resource nodes, calculate the index matching degree value of the recommended computing power resource node according to all the computing power constraint indexes. The index matching degree value is used to represent the matching degree between the recommended computing power resource node and all the computing power constraint indexes; determine whether the index matching degree value is greater than or equal to the screening threshold of the computing power resource node. When it is determined that the index matching degree value is greater than or equal to the screening threshold of the computing power resource node, determine that the recommended computing power resource node is a target node.

[0064] A third aspect of the present invention discloses another service-oriented computing power resource integration device, and the device includes:

[0065] A memory storing executable program code;

[0066] A processor coupled to the memory;

[0067] The processor calls the executable program code stored in the memory and executes the business-oriented computing power resource integration method disclosed in the first aspect of the present invention.

[0068] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which are used to execute the business-oriented computing power resource integration method disclosed in the first aspect of the present invention when called.

[0069] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0070] In the embodiments of the present invention, according to the obtained business attribute information of the target business, the recommended computing power resource allocation information adapted to the business attribute information is determined. The recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the business attribute information, and the recommended computing power resource node is planned to allocate computing power resources to the business platform corresponding to the target business in a time-sharing manner according to the recommended computing power resource allocation information; according to the obtained business demand information of the target business, the computing power resource integration conditions adapted to the target business are generated, and the computing power resource integration conditions include at least one computing power constraint index; according to the computing power resource integration conditions, at least one target node is determined among all the recommended computing power resource nodes, and the computing power resources corresponding to the target node are the target computing power resources adapted to the target business. It can be seen that implementing the present invention can first determine the recommended computing power resource allocation information adapted to the business attribute information according to the obtained business attribute information of the target business, so as to indicate at least one recommended computing power resource node adapted to the business attribute information that is planned to allocate computing power resources to the business platform corresponding to the target business in a time-sharing manner according to the recommended computing power resource allocation information, so that there are available computing power resource nodes for the target business, improving the convenience, accuracy of computing power resource matching for the target business, and the execution stability of the target business. On this basis, according to the obtained business demand information of the target business, the computing power resource integration conditions adapted to the target business are generated, and the computing power resource integration conditions include at least one computing power constraint index. Furthermore, according to the generated computing power resource integration conditions adapted to the target business, at least one target node corresponding to the target computing power resources adapted to the target business is determined among all the recommended computing power resource nodes, so as to improve the accuracy, adaptability, flexibility and comprehensiveness of business-oriented computing power resource integration through a flexible resource integration method of centralized management + allocation, and further improve the available dimension, available breadth, flexibility and stability of computing power resources, improve the execution efficiency, stability and security of the target business, help reduce the occurrence of computing power resource waste and target business paralysis, improve the user experience, and at the same time improve the development stability and development efficiency of various industry businesses. Brief Description of the Drawings

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0072] Figure 1 is a schematic flowchart of a service-oriented computing power resource integration method disclosed in an embodiment of the present invention;

[0073] Figure 2 is a schematic flowchart of another service-oriented computing power resource integration method disclosed in an embodiment of the present invention;

[0074] Figure 3 is a schematic structural diagram of a service-oriented computing power resource integration device disclosed in an embodiment of the present invention;

[0075] Figure 4 is a schematic structural diagram of another service-oriented computing power resource integration device disclosed in an embodiment of the present invention. Detailed Embodiments

[0076] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0077] The terms "first", "second", etc. in the specification and claims of the present invention and the above drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or terminal including a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or terminals.

[0078] 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.

[0079] The present invention discloses a business-oriented computing power resource integration method and device, which can first determine recommended computing power resource allocation information suitable for the business attribute information based on the business attribute information of the target business, so as to indicate at least one recommended computing power resource node suitable for the business attribute information to allocate computing power resources to the business platform corresponding to the target business in time-sharing according to the recommended computing power resource allocation information, so that the target business has computing power resource nodes available, improves the convenience and accuracy of computing power resource matching of the target business and the execution stability of the target business, and on this basis, generates computing power resource integration conditions suitable for the target business based on the business demand information of the target business. The component includes at least one computing power constraint indicator, and then according to the generated computing power resource integration conditions suitable for the target business, at least one target node corresponding to the target computing power resource suitable for the target business is determined among all the recommended computing power resource nodes, so as to improve the accuracy, adaptability, flexibility and comprehensiveness of business-oriented computing power resource integration through the flexible resource integration method of centralized management + allocation, thereby improving the available dimension, available breadth, flexibility and stability of computing power resources, improving the execution efficiency, stability and security of target business, which is conducive to reducing the waste of computing power resources and the occurrence of paralysis of target business, improving the user experience, and improving the development stability and efficiency of business in various industries. The following are detailed explanations.

[0080] Embodiment 1

[0081] See also Figure 1 , Figure 1 : is a flow chart of a business-oriented computing resource integration method disclosed in an embodiment of the present invention. Figure 1 The business-oriented computing resource integration method described can be applied to the user's business platform, and can also be applied to smart devices associated with the user's business platform. The smart devices include but are not limited to one or more of cloud devices, edge computing devices, relay devices, base station devices, city management devices, smart network devices, and smart home devices, and the embodiments of the present invention are not limited thereto.

[0082] like Figure 1 As shown, the business-oriented computing resource integration method may include the following operations:

[0083] 101. Determine the recommended computing power resource allocation information adapted to the service attribute information of the target service according to the obtained service attribute information of the target service. The recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the service attribute information, and the recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service at different times according to the recommended computing power resource allocation information.

[0084] In an embodiment of the present invention, optionally, the acquisition of the above-mentioned target service / service attribute information may be implemented by a user upload. Further optionally, it may also be implemented by sensing through a sensing device. The above-mentioned sensing device includes, but is not limited to, one or more of a platform sensing device, a radar, a base station, a router, a mobile portable communication device, a wearable device with communication functions, etc. Further optionally, specifically, the above-mentioned sensing device may include a wireless communication module inside, such as: a Wifi module. Further optionally, specifically, the above-mentioned sensing device may include a voice sensing module to implement voice interaction with the user and identify the voice command triggered by the user. The above-mentioned sensing device may collect the above-mentioned target service / service attribute information based on a communication sensing fusion frame structure.

[0085] In an embodiment of the present invention, as an optional implementation manner, the above-mentioned service attribute information includes service process information and service scenario information. Determining the recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service includes:

[0086] According to the service process information, determine the object sorting information of the target service. The target service corresponds to at least one acting object, and the acting object executes the target service based on the corresponding service platform. The object sorting information is used to sort the acting objects in the order of executing the target service.

[0087] For each acting object, determine the task volume information of the acting object for the target service according to the service scenario information; according to the task volume information, determine the recommended computing power information of the acting object. The recommended computing power information is used to represent the recommended computing power situation adapted to the task volume information.

[0088] According to all the recommended computing power information and the object sorting information, determine the recommended computing power resource allocation information adapted to the service attribute information.

[0089] It can be seen that implementing this optional embodiment can sort at least one object of action for executing the target service according to the service process information in the order of execution of the target service, so as to obtain the object sorting information of the target service. For each object of action, according to the service scenario information, the task volume information of the object of action for the target service is determined. Furthermore, according to the task volume information, the recommended computing power information adapted to the task volume information of the object of action is determined, improving the accuracy of determining the recommended computing power situation of each object of action. Finally, according to all the recommended computing power information and combining the above object sorting information, the recommended computing power resource allocation information adapted to the service attribute information is determined, so as to improve the accuracy and scientificity of the proposed allocation of the recommended computing power resource nodes, which is beneficial to improving the accuracy of integrating computing power resources for services, the matching accuracy of computing power resources, and the execution stability of the target service.

[0090] In this optional embodiment, as an optional implementation manner, the above service attribute information further includes service efficiency information, and the service efficiency information is used to represent the preset standard execution efficiency situation of the target service. Determining the recommended computing power information of the object of action according to the task volume information includes:

[0091] Obtain the first resource information of the object of action, where the first resource information is used to represent the first existing resource distribution situation of the object of action;

[0092] According to the first resource information and the service scenario information, determine the second resource information of the object of action, where the second resource information is used to represent the second existing resource distribution situation of the object of action for executing the target service;

[0093] According to the task volume information, service efficiency information, service scenario information, and second resource information, match the third resource information of the object of action, where the third resource information is used to represent the required updated resource situation of the object of action for executing the target service, and the third resource information and the second resource information are matched with the service efficiency information;

[0094] According to the second resource information and the third resource information, determine the recommended computing power information of the object of action.

[0095] In the embodiment of the present invention, the range of the above first existing resource distribution situation is larger than that of the second existing resource distribution situation; the fact that the third resource information and the second resource information are matched with the service efficiency information is used to indicate that the object of action meets the preset standard execution efficiency indicated by the service efficiency information based on the third resource information and the second resource information.

[0096] It can be seen that implementing this optional embodiment can further determine, based on the obtained first resource information representing the first existing resource distribution of the acting object, in combination with the service scenario information, the second resource information representing the second existing resource distribution of the acting object for executing the target service. According to the task volume information, service efficiency information, service scenario information, and the second resource information, match the third resource information representing the required updated resource situation of the acting object for executing the target service. According to the second resource information and the third resource information, determine the recommended computing power information of the acting object, thereby further improving the determination accuracy of the recommended computing power information of each acting object in combination with the service efficiency information representing the preset standard execution efficiency of the target service, and then facilitating the improvement of the determination accuracy of the recommended computing power resource allocation information, further improving the allocation accuracy and scientificity of the recommended computing power resource nodes, facilitating the improvement of the integration accuracy of computing power resources for services and the matching accuracy of computing power resources, and improving the execution stability of the target service.

[0097] In this optional embodiment, as another optional implementation manner, the above-mentioned matching of the third resource information of the acting object according to the task volume information, service efficiency information, service scenario information, and the second resource information includes:

[0098] Analyze the first predicted execution efficiency information of the second resource information according to the task volume information;

[0099] Analyze the second predicted execution efficiency information of the acting object according to the service efficiency information and the first predicted execution efficiency information;

[0100] Match the third resource information of the acting object according to the second predicted execution efficiency information and the service scenario information, and the third resource information is matched with the second predicted execution efficiency information.

[0101] It can be seen that implementing this optional embodiment can analyze, according to the task volume information, the first predicted execution efficiency information of the acting object for executing the target service under the above task volume information based on the second resource information, and based on the service efficiency information and the first predicted execution efficiency information, analyze the second predicted execution efficiency information of the acting object to meet the service efficiency information on the basis of the first predicted execution efficiency information. Then, in combination with the service scenario information, match the third resource information representing the required updated resource situation of the acting object for executing the target service, improving the matching accuracy and scientificity of the third resource information, and facilitating the improvement of the integration accuracy of computing power resources for services.

[0102] In this optional embodiment, as yet another optional implementation manner, the above-mentioned determination of the recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information includes:

[0103] For each piece of recommended computing power information, according to the required configuration information of the recommended computing power information, determine at least one target object among all the objects in question, and the target object satisfies the configuration condition corresponding to the required configuration information; according to the object sorting information, match the matching object corresponding to the recommended computing power information among all the target objects;

[0104] Based on all matching objects, the recommended computing power resource allocation information suitable for the business attribute information is determined.

[0105] It can be seen that the implementation of this optional embodiment can further determine at least one target object that meets the configuration conditions corresponding to the required configuration information for each recommended computing power information among all the objects after calculating the recommended computing power information of each object, based on the required configuration information of the recommended computing power information, so as to further improve the allocation accuracy of the recommended computing power resource nodes by considering the actual configuration adaptation problem of each recommended computing power information, and prevent the recommended computing power information determined based on the above-mentioned task volume information and business efficiency information of each object from reducing the utilization efficiency and stability of computing power resources due to configuration adaptation problems. On this basis, according to the above-mentioned generated object sorting information, among all the target objects, the matching objects corresponding to the recommended computing power information are matched, which can further improve the allocation accuracy of the recommended computing power resource nodes that are intended to allocate computing power resources to the business platform corresponding to the target business in time-sharing according to the recommended computing power resource allocation information. Finally, according to all the matching objects, the recommended computing power resource allocation information adapted to the business attribute information is determined, which can further help to improve the allocation accuracy of the recommended computing power resource nodes in the proposed allocation stage, and improve the accuracy, adaptability, flexibility and comprehensiveness of business-oriented computing power resource integration.

[0106] 102. Generate computing power resource integration conditions suitable for the target business based on the acquired business demand information of the target business, where the computing power resource integration conditions include at least one computing power constraint indicator;

[0107] 103. According to the computing power resource integration conditions, at least one target node is determined among all the recommended computing power resource nodes, and the computing power resources corresponding to the target node are target computing power resources suitable for the target business.

[0108] In the embodiment of the present invention, the above-mentioned target node can be used as a standby node before the target service is actually executed, or it can be generated and deployed in real time for real time use, which is related to the actual application scenario and will not be elaborated in the embodiment of the present invention.

[0109] It can be seen that implementing the embodiments of the present invention can first determine the recommended computing power resource allocation information adapted to the service attribute information of the target service according to the obtained service attribute information of the target service, so as to indicate at least one recommended computing power resource node adapted to the service attribute information, and the recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service according to the recommended computing power resource allocation information at different times, so that there are available computing power resource nodes for the target service, improving the convenience, accuracy of matching computing power resources for the target service, and the execution stability of the target service. On this basis, according to the obtained service demand information of the target service, a computing power resource integration condition adapted to the target service is generated, and the computing power resource integration condition includes at least one computing power constraint index. Furthermore, according to the generated computing power resource integration condition adapted to the target service, at least one target node corresponding to the target computing power resource adapted to the target service is determined among all the recommended computing power resource nodes, so as to improve the accuracy, adaptability, flexibility and comprehensiveness of computing power resource integration for services through a flexible resource integration method of centralized management + allocation, and further improve the available dimension, available breadth, flexibility and stability of computing power resources, improve the execution efficiency, stability and security of the target service, facilitate reducing the occurrence of computing power resource waste and target service paralysis, improve the user experience, and at the same time improve the development stability and development efficiency of various industry services.

[0110] Embodiment 2

[0111] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of another service-oriented computing power resource integration method disclosed in the embodiments of the present invention. Among them, Figure 2 the described service-oriented computing power resource integration method can be applied to the service platform of the user, and can also be applied to intelligent devices associated with the service platform of the user. The intelligent devices include, but are not limited to, one or more of cloud devices, edge computing devices, relay devices, base station devices, urban management devices, intelligent network-connected devices, and smart home devices, which are not limited in the embodiments of the present invention.

[0112] As Figure 2 shown, the service-oriented computing power resource integration method may include the following operations:

[0113] 201. According to the obtained service attribute information of the target service, determine the recommended computing power resource allocation information adapted to the service attribute information. The recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the service attribute information, and the recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service according to the recommended computing power resource allocation information at different times;

[0114] In the embodiments of the present invention, for the supplementary description of step 201, please refer to the supplementary description of step 101 in Embodiment 1, and the embodiments of the present invention will not elaborate on this again.

[0115] 202. Analyze a set of computing power constraint conditions adapted to the target service according to the obtained service requirement information of the target service;

[0116] In the embodiments of the present invention, optionally, the above-mentioned service requirement information includes at least one of the expected coverage range information of computing power resource nodes, security requirement information, first computing power processing efficiency information, and first service execution frequency information. Further optionally, the above-mentioned set of computing power constraint conditions includes at least one computing power constraint index such as the constraint coverage range information of computing power resource nodes, security configuration information, protocol configuration information, resource node credibility information, bandwidth configuration information, sleep configuration information, resource node stable interval configuration information, second computing power processing efficiency information, and second service execution frequency information. The first computing power processing efficiency information corresponds to the second computing power processing efficiency information, and the first service execution frequency information corresponds to the second service execution frequency information;

[0117] 203. Generate computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions.

[0118] In the embodiments of the present invention, as an optional implementation manner, the above-mentioned generating computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions includes:

[0119] For each computing power constraint index, match the target priority value of the computing power constraint index according to the service attribute information and service requirement information. The target priority value is used to represent the influence degree of the computing power constraint index on the target service;

[0120] Generate computing power resource integration conditions adapted to the target service according to all computing power constraint indexes and the corresponding target priority values;

[0121] In the embodiments of the present invention, optionally, the specific values / degrees of different computing power constraint indexes in the above-mentioned computing power resource integration conditions are different and are positively correlated with the above-mentioned target priority values.

[0122] In the embodiments of the present invention, it should be noted that it cannot be simply considered that the set of computing power constraint conditions and the computing power resource integration conditions both include the above-mentioned computing power constraint indexes and are the same. The set may only include indexes, while the conditions are further combinations of the indexes to achieve the purpose of determining at least one target node among all recommended computing power resource nodes according to the computing power resource integration conditions. In the embodiments of the present invention, one of the combination criteria is the above-mentioned target priority value used to represent the influence degree of the computing power constraint index on the target service.

[0123] It can be seen that after analyzing a multi-dimensional optional set of computing power constraint conditions adapted to the target service based on the service requirement information of the target service obtained, the implementation of this optional embodiment can further determine the target priority value representing the degree of influence on the target service for each computing power constraint index in the set of computing power constraint conditions analyzed according to the service attribute information and the service requirement information. Thus, based on the target priority value, a computing power resource integration condition including at least one computing power constraint index can be generated more scientifically and accurately, further improving the accuracy and scientific nature of the generation of the computing power resource integration condition, which is beneficial to improving the accuracy and scientific nature of the computing power resource integration for the service.

[0124] 204. According to the computing power resource integration condition, among all the recommended computing power resource nodes, determine at least one target node, and the computing power resources corresponding to the target node are the target computing power resources adapted to the target service.

[0125] It can be seen that the implementation of the embodiments of the present invention can, after determining the recommended computing power resource allocation information adapted to the service attribute information based on the service requirement information of the target service obtained, further analyze a multi-dimensional optional set of computing power constraint conditions adapted to the target service according to the service requirement information of the target service obtained. Thus, it can only improve the comprehensiveness, accuracy and scientific nature of the generation of the computing power resource integration condition, which is beneficial to improving the accuracy, adaptability, flexibility and comprehensiveness of the computing power resource integration for the service, and further improving the available dimension, available breadth, flexibility and stability of the computing power resources, improving the execution efficiency, stability and security of the target service, being beneficial to reducing the occurrence of waste of computing power resources and paralysis of the target service, improving the user experience while improving the development stability and development efficiency of the services in various industries.

[0126] In the embodiments of the present invention, as another optional implementation manner, the above-mentioned determining at least one target node among all the recommended computing power resource nodes according to the computing power resource integration condition includes:

[0127] Calculate the screening threshold of the computing power resource nodes of the target service according to all the computing power constraint indexes and the corresponding target priority values;

[0128] For each recommended computing power resource node, calculate the index matching degree value of the recommended computing power resource node according to all the computing power constraint indexes. The index matching degree value is used to represent the matching degree between the recommended computing power resource node and all the computing power constraint indexes; determine whether the index matching degree value is greater than or equal to the screening threshold of the computing power resource nodes. When it is determined that the index matching degree value is greater than or equal to the screening threshold of the computing power resource nodes, then determine that the recommended computing power resource node is the target node.

[0129] In an embodiment of the present invention, optionally, when it is determined that all the index matching degree values are less than the computing power resource node screening threshold, a preset number of recommended computing power resource nodes closest to the computing power resource node screening threshold can be determined as target nodes, and the above-mentioned preset number is related to the target service;

[0130] Further optionally, the above-mentioned computing power resource node screening threshold can also be adjusted, and the operation of determining whether the index matching degree value is greater than or equal to the computing power resource node screening threshold is triggered again.

[0131] It can be seen that implementing this optional embodiment can, after generating the computing power resource integration conditions, calculate the computing power resource node screening threshold of the target service according to all the computing power constraint indicators and the corresponding target priority values, so as to improve the accuracy, service adaptability, and scientificity of the computing power resource integration for the service. For each recommended computing power resource node, according to all the computing power constraint indicators, calculate the index matching degree value indicating the matching degree between the recommended computing power resource node and all the computing power constraint indicators. And when it is determined that the index matching degree value is greater than or equal to the computing power resource node screening threshold, then determine that the recommended computing power resource node is a target node, thereby further improving the determination accuracy and determination security of the target node, which is beneficial to further improving the accuracy, adaptability, flexibility, and comprehensiveness of the computing power resource integration for the service, improving the available dimension, available breadth, flexibility, and stability of the computing power resources, and improving the execution efficiency, stability, and security of the target service.

[0132] Embodiment III

[0133] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of a service-oriented computing power resource integration device disclosed in an embodiment of the present invention. Among them, this service-oriented computing power resource integration device can be applied to the service platform of a user, and can also be applied to intelligent devices associated with the service platform of the user. The intelligent devices include, but are not limited to, one or more of cloud devices, edge computing devices, relay devices, base station devices, urban management devices, intelligent network-connected devices, and smart home devices, which are not limited in the embodiments of the present invention. As Figure 3 shown, this service-oriented computing power resource integration device may include:

[0134] A determination module 301, configured to determine recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service. The recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the service attribute information. The recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service in a time-sharing manner according to the recommended computing power resource allocation information;

[0135] A generation module 302, configured to generate computing power resource integration conditions adapted to the target service according to the obtained service requirement information of the target service, where the computing power resource integration conditions include at least one computing power constraint index;

[0136] A determination module 301 is further configured to determine at least one target node from all the recommended computing power resource nodes according to the computing power resource integration conditions, and the computing power resources corresponding to the target nodes are the target computing power resources adapted to the target service.

[0137] It can be seen that implementing the embodiments of the present invention can first determine the recommended computing power resource allocation information adapted to the service attribute information of the target service according to the obtained service attribute information of the target service, so as to indicate at least one recommended computing power resource node that is applicable to the service attribute information and is to allocate computing power resources to the service platform corresponding to the target service according to the recommended computing power resource allocation information in a time-sharing manner, so that there are available computing power resource nodes for the target service, improving the convenience, accuracy of matching computing power resources for the target service, and the execution stability of the target service. On this basis, according to the obtained service requirement information of the target service, generate computing power resource integration conditions adapted to the target service, where the computing power resource integration conditions include at least one computing power constraint index, and then determine at least one target node corresponding to the target computing power resources adapted to the target service from all the recommended computing power resource nodes according to the generated computing power resource integration conditions adapted to the target service, so as to improve the accuracy, adaptability, flexibility and comprehensiveness of computing power resource integration for services through a flexible resource integration method of centralized management + allocation, and further improve the available dimension, available breadth, flexibility and stability of computing power resources, improve the execution efficiency, stability and security of the target service, be conducive to reducing the occurrence of computing power resource waste and target service paralysis, improve the user experience while improving the development stability and development efficiency of various industry services.

[0138] In the embodiments of the present invention, as an optional implementation manner, the above service attribute information includes service process information and service scenario information. The specific manner for the determination module 301 to determine the recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service includes:

[0139] According to the service process information, determine the object sorting information of the target service. The target service corresponds to at least one acting object, and the acting object executes the target service based on the corresponding service platform. The object sorting information is used to sort the acting objects in the order of executing the target service;

[0140] For each acting object, according to the service scenario information, determine the task amount information of the acting object for the target service; according to the task amount information, determine the recommended computing power information of the acting object, and the recommended computing power information is used to represent the recommended computing power situation adapted to the task amount information;

[0141] Determine the recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information.

[0142] It can be seen that implementing this optional embodiment can sort at least one object acting on the target service based on the corresponding service platform according to the service process information in the order of executing the target service, to obtain the object sorting information of the target service. For each acting object, according to the service scenario information, determine the task volume information of the acting object for the target service, and then according to the task volume information, determine the recommended computing power information of the acting object adapted to the task volume information, improving the determination accuracy of the recommended computing power situation of each acting object. Finally, according to all the recommended computing power information and in combination with the above object sorting information, determine the recommended computing power resource allocation information adapted to the service attribute information, so as to improve the accuracy and scientificity of the proposed allocation of the recommended computing power resource nodes, which is conducive to improving the integration accuracy of the computing power resources for the service, the matching accuracy of the computing power resources, and the execution stability of the target service.

[0143] In this optional embodiment, as an optional implementation manner, the above service attribute information further includes service efficiency information, and the service efficiency information is used to represent the preset standard execution efficiency situation of the target service. The specific manner for the determination module 301 to determine the recommended computing power information of the acting object according to the task volume information includes:

[0144] Obtain the first resource information of the acting object, where the first resource information is used to represent the first existing resource distribution situation of the acting object;

[0145] According to the first resource information and the service scenario information, determine the second resource information of the acting object, where the second resource information is used to represent the second existing resource distribution situation of the acting object for executing the target service;

[0146] According to the task volume information, service efficiency information, service scenario information, and the second resource information, match the third resource information of the acting object, where the third resource information is used to represent the required updated resource situation of the acting object for executing the target service, and the third resource information and the second resource information are matched with the service efficiency information;

[0147] According to the second resource information and the third resource information, determine the recommended computing power information of the acting object.

[0148] It can be seen that implementing this optional embodiment can further determine, based on the obtained first resource information representing the first existing resource distribution of the acting object and in combination with the service scenario information, the second resource information representing the second existing resource distribution of the acting object for executing the target service. According to the task volume information, service efficiency information, service scenario information, and the second resource information, the third resource information representing the required updated resource situation of the acting object for executing the target service is matched. According to the second resource information and the third resource information, the recommended computing power information of the acting object is determined, thereby further improving the accuracy of determining the recommended computing power information of each acting object in combination with the service efficiency information representing the preset standard execution efficiency of the target service, and further facilitating improving the accuracy of determining the recommended computing power resource allocation information, further improving the accuracy and scientificity of the proposed allocation of the recommended computing power resource nodes, and being conducive to improving the integration accuracy of the computing power resources for the service, the matching accuracy of the computing power resources, and the execution stability of the target service.

[0149] In this optional embodiment, as another optional implementation manner, the specific method for the above-mentioned determination module 301 to match the third resource information of the acting object according to the task volume information, service efficiency information, service scenario information, and the second resource information includes:

[0150] Analyze the first predicted execution efficiency information of the second resource information according to the task volume information;

[0151] Analyze the second predicted execution efficiency information of the acting object according to the service efficiency information and the first predicted execution efficiency information;

[0152] Match the third resource information of the acting object according to the second predicted execution efficiency information and the service scenario information, and the third resource information is matched with the second predicted execution efficiency information.

[0153] It can be seen that implementing this optional embodiment can analyze, according to the task volume information, the first predicted execution efficiency information of the acting object for executing the target service under the above-mentioned task volume information based on the second resource information, and based on the service efficiency information and the first predicted execution efficiency information, analyze the second predicted execution efficiency information of the acting object to meet the service efficiency information on the basis of the above-mentioned first predicted execution efficiency information. Then, in combination with the service scenario information, the third resource information representing the required updated resource situation of the acting object for executing the target service is matched, improving the matching accuracy of the third resource information while improving the matching scientificity of the third resource information, and being conducive to improving the integration accuracy of the computing power resources for the service.

[0154] In this optional embodiment, as another optional implementation manner, the specific manner for the determining module 301 to determine the recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information includes:

[0155] For each piece of recommended computing power information, according to the required configuration information of the recommended computing power information, at least one target object is determined among all the acting objects, and the target object satisfies the configuration conditions corresponding to the required configuration information; according to the object sorting information, the matching object corresponding to the recommended computing power information is matched among all the target objects;

[0156] According to all the matching objects, the recommended computing power resource allocation information adapted to the service attribute information is determined.

[0157] It can be seen that implementing this optional embodiment can further, after calculating the recommended computing power information of each acting object, for each piece of recommended computing power information, according to the required configuration information of the recommended computing power information, at least one target object that satisfies the configuration conditions corresponding to the required configuration information is determined among all the acting objects, so as to further improve the allocation accuracy of the recommended computing power resource nodes by considering the actual configuration adaptation problem of each piece of recommended computing power information, and prevent the recommended computing power information determined based on the task volume information and service efficiency information of each above-mentioned acting object from reducing the usage efficiency and usage stability of the computing power resources due to the configuration adaptation problem. On this basis, according to the generated object sorting information above, the matching object corresponding to the recommended computing power information is matched among all the target objects, which can further improve the allocation accuracy of the recommended computing power resource nodes that are intended to allocate computing power resources to the service platform corresponding to the target service according to the recommended computing power resource allocation information in a time-sharing manner. Finally, according to all the matching objects, the recommended computing power resource allocation information adapted to the service attribute information is determined, which can further contribute to improving the allocation accuracy in the stage of the recommended computing power resource nodes to be allocated, and improving the integration accuracy, adaptability, flexibility and comprehensiveness of the computing power resources for the service.

[0158] In an optional embodiment, the above-mentioned service demand information includes at least one of the expected coverage range information of the computing power resource nodes, the security demand information, the first computing power processing efficiency information, and the first service execution frequency information. The specific manner for the generating module 302 to generate the computing power resource integration conditions adapted to the target service according to the obtained service demand information of the target service includes:

[0159] According to the service requirement information of the target service obtained, analyze the set of computing power constraint conditions adapted to the target service. The set of computing power constraint conditions includes at least one computing power constraint index among the constraint coverage range information of computing power resource nodes, security configuration information, protocol configuration information, resource node credibility information, bandwidth configuration information, sleep configuration information, resource node stable interval configuration information, second computing power processing efficiency information, and second service execution frequency information. The first computing power processing efficiency information corresponds to the second computing power processing efficiency information, and the first service execution frequency information corresponds to the second service execution frequency information;

[0160] Generate computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions.

[0161] It can be seen that after determining the recommended computing power resource allocation information adapted to the service attribute information according to the service requirement information of the target service obtained in the embodiment of the present invention, it is also possible to analyze the multi-dimensional optional set of computing power constraint conditions adapted to the target service according to the service requirement information of the target service obtained, so as to only improve the comprehensiveness, accuracy and scientificity of the generation of computing power resource integration conditions, which is beneficial to improving the accuracy, adaptability, flexibility and comprehensiveness of computing power resource integration for services, and further improving the available dimensions, available breadth, flexibility and stability of computing power resources, improving the execution efficiency, stability and security of the target service, being beneficial to reducing the occurrence of computing power resource waste and target service paralysis, improving the user experience while improving the development stability and development efficiency of various industry services.

[0162] In this optional embodiment, as an optional implementation manner, the specific manner for the above-mentioned generating module 302 to generate computing power resource integration conditions adapted to the target service according to the set of computing power constraint conditions includes:

[0163] For each computing power constraint index, match the target priority value of the computing power constraint index according to the service attribute information and the service requirement information. The target priority value is used to represent the influence degree of the computing power constraint index on the target service;

[0164] Generate computing power resource integration conditions adapted to the target service according to all the computing power constraint indexes and the corresponding target priority values;

[0165] It can be seen that after analyzing the multi-dimensional optional computing power constraint condition set suitable for the target service according to the service requirement information of the target service obtained, the implementation of this optional embodiment can, according to the target priority value of each computing power constraint index in the computing power constraint condition set analyzed according to the service attribute information and the service requirement information, which is used to represent the influence degree on the target service, so as to generate the computing power resource integration condition including at least one computing power constraint index more scientifically and accurately according to the target priority value, thereby further improving the generation accuracy and scientificity of the computing power resource integration condition, which is beneficial to improving the accuracy and scientificity of the computing power resource integration for the service.

[0166] Optionally, the specific manner for the above-mentioned determining module 301 to determine at least one target node among all the recommended computing power resource nodes according to the computing power resource integration condition includes:

[0167] Calculate the screening threshold of the computing power resource nodes for the target service according to all the computing power constraint indexes and the corresponding target priority values;

[0168] For each recommended computing power resource node, calculate the index matching degree value of the recommended computing power resource node according to all the computing power constraint indexes, where the index matching degree value is used to represent the matching degree between the recommended computing power resource node and all the computing power constraint indexes; determine whether the index matching degree value is greater than or equal to the screening threshold of the computing power resource nodes. When it is determined that the index matching degree value is greater than or equal to the screening threshold of the computing power resource nodes, then determine that the recommended computing power resource node is a target node.

[0169] It can be seen that after generating the computing power resource integration condition, the implementation of this optional embodiment can calculate the screening threshold of the computing power resource nodes for the target service according to all the computing power constraint indexes and the corresponding target priority values, so as to improve the accuracy, service adaptability and scientificity of the computing power resource integration for the service. For each recommended computing power resource node, calculate the index matching degree value of the recommended computing power resource node, which is used to represent the matching degree between the recommended computing power resource node and all the computing power constraint indexes, and when it is determined that the index matching degree value is greater than or equal to the screening threshold of the computing power resource nodes, then determine that the recommended computing power resource node is a target node, thereby further improving the determination accuracy and determination security of the target node, which is beneficial to further improving the accuracy, adaptability, flexibility and comprehensiveness of the computing power resource integration for the service, improving the available dimension, available breadth, flexibility and stability of the computing power resources, and improving the execution efficiency, stability and security of the target service.

[0170] Embodiment 4

[0171] Please refer to Figure 4 , Figure 4It is a schematic structural diagram of another business-oriented computing power resource integration device disclosed in an embodiment of the present invention. Among them, the business-oriented computing power resource integration device can be applied to the user's business platform, and can also be applied to intelligent devices associated with the user's business platform. The intelligent devices include, but are not limited to, one or more of cloud devices, edge computing devices, relay devices, base station devices, urban management devices, intelligent network-connected devices, and smart home devices, which are not limited in the embodiments of the present invention. As Figure 4 shown, the business-oriented computing power resource integration device may include:

[0172] A memory 401 storing executable program code.

[0173] A processor 402 coupled to the memory 401.

[0174] The processor 402 invokes the executable program code stored in the memory 401 and executes the steps in the business-oriented computing power resource integration method described in Embodiment 1 or Embodiment 2 of the present invention.

[0175] Embodiment 5

[0176] An embodiment of the present invention discloses a computer storage medium. The computer storage medium stores computer instructions, and when the computer instructions are invoked, they are used to execute the steps in the business-oriented computing power resource integration method described in Embodiment 1 or Embodiment 2 of the present invention.

[0177] Embodiment 6

[0178] An embodiment of the present invention discloses a computer program product. The computer program product includes a non-transitory computer storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the business-oriented computing power resource integration method described in Embodiment 1 or Embodiment 2.

[0179] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0180] Through the specific descriptions of the above embodiments, those skilled in the art can clearly understand that each embodiment 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 this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium capable of carrying or storing data.

[0181] Finally, it should be noted that: What is disclosed in an embodiment of a service-oriented computing power resource integration method and apparatus of the present invention is only a 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 foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; And these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A business-oriented computing power resource integration method, characterized in that The method includes: Determining recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service, where the recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the service attribute information, and the recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service in a time-sharing manner according to the recommended computing power resource allocation information; Generating computing power resource integration conditions adapted to the target service according to the obtained service demand information of the target service, where the computing power resource integration conditions include at least one computing power constraint index; Determining at least one target node from all the recommended computing power resource nodes according to the computing power resource integration conditions, where the computing power resources corresponding to the target node are the target computing power resources adapted to the target service.

2. The method for integrating computing power resources oriented to services according to claim 1, wherein The service attribute information includes service process information and service scenario information. The determining recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service includes: Determining object sorting information of the target service according to the service process information, where the target service corresponds to at least one acting object, and the acting object executes the target service based on the corresponding service platform, and the object sorting information is used to sort the acting objects in the order of executing the target service; For each acting object, determining the task volume information of the acting object for the target service according to the service scenario information; and determining the recommended computing power information of the acting object according to the task volume information, where the recommended computing power information is used to represent the recommended computing power situation adapted to the task volume information; Determining recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information.

3. The method for integrating computing power resources oriented to services according to claim 2, wherein The service attribute information further includes service efficiency information, which is used to represent the preset standard execution efficiency situation of the target service. The determining the recommended computing power information of the acting object according to the task volume information includes: Obtaining the first resource information of the acting object, where the first resource information is used to represent the first existing resource distribution situation of the acting object; Determining the second resource information of the acting object according to the first resource information and the service scenario information, where the second resource information is used to represent the second existing resource distribution situation of the acting object for executing the target service; Matching the third resource information of the acting object according to the task volume information, the service efficiency information, the service scenario information and the second resource information, where the third resource information is used to represent the required updated resource situation of the acting object for executing the target service, and the third resource information and the second resource information are matched with the service efficiency information; Determining the recommended computing power information of the acting object according to the second resource information and the third resource information.

4. The method for integrating computing power resources oriented to services according to claim 3, characterized in that Matching the third resource information of the object to be affected according to the task volume information, the service efficiency information, the service scenario information, and the second resource information includes: Analyzing the first predicted execution efficiency information of the second resource information according to the task volume information; Analyzing the second predicted execution efficiency information of the object to be affected according to the service efficiency information and the first predicted execution efficiency information; Matching the third resource information of the object to be affected according to the second predicted execution efficiency information and the service scenario information, where the third resource information matches the second predicted execution efficiency information.

5. The method for integrating computing power resources oriented to services according to any one of claims 2-4, characterized in that, Determining the recommended computing power resource allocation information adapted to the service attribute information according to all the recommended computing power information and the object sorting information includes: For each piece of the recommended computing power information, according to the required configuration information of the recommended computing power information, determining at least one target object among all the objects to be affected, where the target object meets the configuration conditions corresponding to the required configuration information; according to the object sorting information, matching the matching object corresponding to the recommended computing power information among all the target objects; Determining the recommended computing power resource allocation information adapted to the service attribute information according to all the matching objects.

6. The method for integrating computing power resources oriented to services according to any one of claims 1-4, characterized in that The service demand information includes at least one of the expected coverage range information of the computing power resource node, the security demand information, the first computing power processing efficiency information, and the first service execution frequency information. Generating the computing power resource integration conditions adapted to the target service according to the obtained service demand information of the target service includes: Analyzing the computing power constraint condition set adapted to the target service according to the obtained service demand information of the target service, where the computing power constraint condition set includes at least one computing power constraint index such as the constraint coverage range information of the computing power resource node, the security configuration information, the protocol configuration information, the resource node credibility information, the bandwidth configuration information, the sleep configuration information, the resource node stable interval configuration information, the second computing power processing efficiency information, and the second service execution frequency information, where the first computing power processing efficiency information corresponds to the second computing power processing efficiency information, and the first service execution frequency information corresponds to the second service execution frequency information; Generating the computing power resource integration conditions adapted to the target service according to the computing power constraint condition set.

7. The method for integrating computing power resources oriented to services according to claim 6, wherein, Generating the computing power resource integration conditions adapted to the target service according to the computing power constraint condition set includes: For each computing power constraint index, matching the target priority value of the computing power constraint index according to the service attribute information and the service demand information, where the target priority value is used to represent the influence degree of the computing power constraint index on the target service; Generating the computing power resource integration conditions adapted to the target service according to all the computing power constraint indexes and the corresponding target priority values; And determining at least one target node among all the recommended computing power resource nodes according to the computing power resource integration conditions includes: Calculate the screening threshold of computing power resource nodes for the target service according to all the computing power constraint indicators and the corresponding target priority values; For each of the recommended computing power resource nodes, calculate the index matching degree value of the recommended computing power resource node according to all the computing power constraint indicators. The index matching degree value is used to represent the matching degree between the recommended computing power resource node and all the computing power constraint indicators. Determine whether the index matching degree value is greater than or equal to the screening threshold of the computing power resource node. When it is determined that the index matching degree value is greater than or equal to the screening threshold of the computing power resource node, determine that the recommended computing power resource node is the target node.

8. A business-oriented computing power resource integration device, characterized in that, The device includes: A determination module, configured to determine recommended computing power resource allocation information adapted to the service attribute information according to the obtained service attribute information of the target service. The recommended computing power resource allocation information is used to indicate at least one recommended computing power resource node adapted to the service attribute information. The recommended computing power resource node is intended to allocate computing power resources to the service platform corresponding to the target service in a time-sharing manner according to the recommended computing power resource allocation information; A generation module, configured to generate computing power resource integration conditions adapted to the target service according to the obtained service demand information of the target service. The computing power resource integration conditions include at least one computing power constraint indicator; The determination module is further configured to determine at least one target node among all the recommended computing power resource nodes according to the computing power resource integration conditions. The computing power resources corresponding to the target node are the target computing power resources adapted to the target service.

9. A business-oriented computing power resource integration device, characterized in that, The device includes: A memory storing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory and executes the service-oriented computing power resource integration method according to any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which are used to execute the service-oriented computing power resource integration method according to any one of claims 1-7 when the computer instructions are called.

Images