A cloud computing power analysis method, cloud computing power platform and system

Abstract

This invention provides a cloud computing power analysis method, cloud computing power platform, and system. It includes constructing a cloud computing power resource center to effectively acquire optimal cloud computing power resources when achieving a target task, thereby ensuring efficiency in completing the target task and saving resources, improving adaptability to different target tasks, and dynamically updating cloud computing power resources according to the execution process until the target task is completed. This effectively ensures that the target task standard is met within the expected completion time, thus effectively guaranteeing the accuracy and effectiveness of task completion.

Description

Technical Field

[0001] This invention relates to the field of cloud computing power data processing technology, and in particular to a cloud computing power parsing method, cloud computing power platform and system. Background Technology

[0002] Currently, with the rapid development of information technology, cloud computing has become a crucial infrastructure for modern enterprises and research institutions to process massive amounts of data and run complex applications. In many fields such as big data analytics, artificial intelligence training, and scientific computing, the demand for computing power is experiencing explosive growth.

[0003] However, in the existing cloud computing environment, the management and allocation of computing resources face many problems. On the one hand, different users and applications have different needs for computing power in terms of type, scale and time. On the other hand, cloud service providers often have a variety of types and specifications of computing equipment. How to effectively integrate the computing power of these devices to meet the diverse needs of different users has become an urgent problem to be solved.

[0004] Therefore, in order to overcome the above-mentioned technical problems, the present invention provides a cloud computing power analysis method, cloud computing power platform and system. Summary of the Invention

[0005] This invention provides a cloud computing power analysis method, cloud computing power platform, and system. By constructing a cloud computing power resource center, it effectively achieves the acquisition of optimal cloud computing power resources when accomplishing target tasks, thereby ensuring the efficiency of completing target tasks and saving resources, improving adaptability to different target tasks, and by dynamically updating cloud computing power resources according to the execution process until the target task is completed, it can effectively ensure that the target task standards are met within the expected completion time, and effectively ensure the accuracy and effectiveness of task completion.

[0006] A cloud computing power analysis method includes:

[0007] Step 1: Build a cloud computing resource management center. At the same time, based on the user terminal inputting the target task, obtain the task requirement information of the target task.

[0008] Step 2: Evaluate available cloud computing resources in the cloud computing resource management center based on the task requirements information;

[0009] Step 3: Analyze the available cloud computing resources, obtain the optimal cloud computing resources, and execute the target task input by the user terminal based on the optimal cloud computing resources;

[0010] Step 4: Collect the execution process and dynamically update the cloud computing resources based on the execution process until the target task is completed.

[0011] Preferably, in a cloud computing power resolution method, step 1 involves constructing a cloud computing power resource management center, including:

[0012] Read several cloud computing resources, and extract the resource characteristics and resource tags of each cloud computing resource respectively;

[0013] Read the feature types contained in the resource characteristics and determine the feature labels based on the feature types;

[0014] A horizontal record chain is generated based on feature labels, and a vertical record chain is generated based on resource labels.

[0015] Several cloud computing resources are mapped and associated in the horizontal and vertical record chains according to feature tags and resource tags to generate a comprehensive cloud computing resource node.

[0016] The cloud computing resource integration nodes are analyzed to determine the splitting markers for the cloud computing resource integration nodes. Based on the splitting markers, the cloud computing resource integration nodes are split and stored to build a cloud computing resource management center.

[0017] Preferably, a cloud computing power parsing method analyzes the integrated nodes of cloud computing power resources, determines the splitting markers for the integrated nodes, and splits and stores the integrated nodes of cloud computing power resources according to the splitting markers, including:

[0018] Read the cloud computing power resource integration node, determine the target similarity between the horizontal record chain of any cloud computing power resource in the cloud computing power resource integration node and the horizontal record chains of other cloud computing power resources, and mark the first position of any cloud computing power resource in the vertical record chain;

[0019] Mark the first target cloud computing resource when the target similarity reaches the preset condition among the remaining cloud computing resources, and locate the second position of the first target cloud computing resource in the vertical record chain;

[0020] Based on the first position and the corresponding second position, the cloud computing power resource integration node is split and marked to obtain multiple sub-cloud computing power resource integration nodes;

[0021] Construct storage intervals and store each sub-cloud computing power resource integrated node in the corresponding storage interval, and add resource tags to the storage intervals.

[0022] Preferably, in a cloud computing power analysis method, step 1 involves inputting a target task from a user terminal and obtaining the task requirement information for that target task, including:

[0023] The target task is determined based on the user terminal, and the target task upload request is determined based on the target task;

[0024] The cloud computing platform verifies the eligibility of upload requests for target tasks, and once the eligibility verification is passed, it reads the upload request for the target task to determine the target task.

[0025] Read the target task and extract the keywords required for the task;

[0026] Based on the key requirements of the task, determine the task requirements information for the target task.

[0027] Preferably, in a cloud computing power analysis method, step 2 involves assessing available cloud computing resources in the cloud computing power resource management center based on task requirement information, including:

[0028] Read the task requirement information and determine the requirement dimensions and the requirement standards under each requirement dimension.

[0029] Input the demand dimensions and the demand criteria under each demand dimension into the cloud computing power resource management center for matching, and determine the second target cloud computing power resource that meets the demand criteria.

[0030] Real-time monitoring of the working status of the second target cloud computing resources;

[0031] Extract the third target cloud computing resources that are in a non-working state from the working state of the second target cloud computing resources. The third target cloud computing resources are the available cloud computing resources.

[0032] Preferably, in a cloud computing power analysis method, step 3 involves analyzing available cloud computing resources to obtain the optimal cloud computing resources, and executing the target task input by the user terminal based on the optimal cloud computing resources, including:

[0033] The target task is read, the execution steps to complete the target task are determined, and the target task is divided according to the execution steps to obtain multiple sub-target tasks;

[0034] Read the resource requirement standards for each sub-target task;

[0035] Available cloud computing resources are pooled and managed to obtain a target resource pool, which includes a set of available cloud computing resources configurations.

[0036] Based on the resource requirement standards of each sub-target task, a matching process is performed in the target resource pool to obtain the target configuration sequence corresponding to each sub-target task;

[0037] The target configuration sequence corresponding to each sub-target task is sorted according to the execution order of the execution steps, and the target configuration sequence corresponding to each sub-target task is arranged and combined according to the sorting result to obtain multiple configuration combinations to complete the target task.

[0038] Select the target configuration combination from multiple configuration combinations as the best cloud computing resources, and execute the target task based on the best cloud computing resources.

[0039] Preferably, a cloud computing power analysis method selects a target configuration combination as the optimal cloud computing power resource from multiple configuration combinations, and executes the target task based on the optimal cloud computing power resource, including:

[0040] Obtain the task parameters for executing the target task, and simulate the task parameters for executing the target task in the computer. At the same time, simulate the execution of the target task in the computer based on multiple configuration combinations, and obtain the completion efficiency of each configuration combination.

[0041] The top two configuration combinations in terms of completion efficiency are selected, and the configuration combination with the highest completion efficiency is selected as the best cloud computing power resource. Meanwhile, the configuration combination with the second highest completion efficiency is selected as the alternative cloud computing power resource.

[0042] The target task input by the user terminal is executed based on the best cloud computing resources, and alternative cloud computing resources are activated when the best cloud computing resources cannot be used.

[0043] Preferably, in a cloud computing power analysis method, step 4 involves collecting the execution process and dynamically updating cloud computing power resources based on the execution process until the target task is completed, including:

[0044] When executing a target task based on the best cloud computing resources, the execution process of the target task is collected in real time to determine the real-time progress of the target task.

[0045] The remaining execution volume and execution time of the target task are determined based on the real-time progress of the task.

[0046] Obtain the optimal execution speed of cloud computing resources, and determine the remaining time to complete the target task based on the optimal execution speed of cloud computing resources and the remaining execution volume of the target task;

[0047] Obtain the expected completion time for the target task, and calculate the target difference between the expected completion time and the execution time.

[0048] Compare the remaining time with the target difference time to determine whether cloud computing resources need to be updated.

[0049] If the remaining time is less than or equal to the target difference time, it is determined that cloud computing resources do not need to be updated.

[0050] Otherwise, it is determined that cloud computing resources need to be updated, and cloud computing resources that meet the target difference time are retrieved from the cloud computing resource management center. At the same time, the current best cloud computing resources are updated based on the retrieval results.

[0051] A cloud computing power platform includes: steps for performing any one of the cloud computing power parsing methods.

[0052] A cloud computing power analysis system includes:

[0053] The module is used to build a cloud computing resource management center. At the same time, it obtains the task requirements information of the target task based on the user terminal input of the target task.

[0054] The evaluation module is used to evaluate available cloud computing resources in the cloud computing resource management center based on task requirements information;

[0055] The analysis module is used to analyze available cloud computing resources, obtain the best cloud computing resources, and execute the target task input to the user terminal based on the best cloud computing resources.

[0056] The update module is used to collect the execution process and dynamically update the cloud computing resources based on the execution process until the target task is completed.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0058] By constructing a cloud computing resource center, it is possible to effectively acquire the best cloud computing resources when achieving the target task, thereby ensuring the efficiency of completing the target task and saving resources, improving the adaptability to different target tasks, and by dynamically updating cloud computing resources according to the execution process until the target task is completed, it can effectively ensure that the target task standard is achieved within the expected completion time, and effectively ensure the accuracy and effectiveness of task completion.

[0059] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in this application.

[0060] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0061] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0062] Figure 1 This is a flowchart illustrating the steps of a cloud computing power analysis method in an embodiment of the present invention;

[0063] Figure 2 This is a flowchart of step 1 in a cloud computing power analysis method according to an embodiment of the present invention;

[0064] Figure 3 This is a structural diagram of a cloud computing power analysis system according to an embodiment of the present invention. Detailed Implementation

[0065] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0066] Example 1:

[0067] This embodiment provides a cloud computing power analysis method, such as... Figure 1 As shown, it includes:

[0068] Step 1: Build a cloud computing resource management center. At the same time, based on the user terminal inputting the target task, obtain the task requirement information of the target task.

[0069] Step 2: Evaluate available cloud computing resources in the cloud computing resource management center based on the task requirements information;

[0070] Step 3: Analyze the available cloud computing resources, obtain the optimal cloud computing resources, and execute the target task input by the user terminal based on the optimal cloud computing resources;

[0071] Step 4: Collect the execution process and dynamically update the cloud computing resources based on the execution process until the target task is completed.

[0072] In this embodiment, the cloud computing power resource management center is applicable to one or more of the following fields: technology development, technical consulting, technical services, and technology transfer in the fields of data technology, network technology, intelligent technology, electromechanical technology, and computer technology; application software services and basic software services; energy performance contracting; sales of electromechanical equipment, communication equipment, building materials, metal materials, instruments and meters, electronic products, computer hardware and software and auxiliary equipment; computer information system integration; investment, operation and management of transmission network infrastructure; database processing; design and construction of building engineering, security engineering, decoration engineering, and electronic intelligent engineering; exhibition planning; value-added telecommunications services; and broadband user access network services.

[0073] In this embodiment, the cloud computing resource management center is used to manage different cloud computing resources. By using the cloud computing resource management center, different cloud computing resources can be allocated for different target tasks, so as to maximize the utilization of cloud computing resources.

[0074] In this embodiment, executing the target task input to the user terminal based on the best cloud computing resources refers to matching the computing resources that can complete the target task in the cloud computing resource management center, and then using the matching computing resources as available computing resources. The best computing resources are then determined from the available computing resources, so that the target task can be completed by using the best cloud computing resources. This helps to complete the target task in a highly efficient and resource-saving way.

[0075] In this embodiment, the collection of execution process refers to the process data when the target task is completed, including execution progress, etc.

[0076] In this embodiment, dynamically updating cloud computing resources based on the execution process means determining whether the remaining tasks can be completed within a specified time through the execution process. If they cannot be completed within the specified time, the cloud computing resources management center will re-determine the cloud computing resources that meet the requirements and update them to ensure the successful completion of the target tasks.

[0077] In this embodiment, the target task is the task that needs to be completed (e.g., the data scale and processing in data processing, the model architecture and data volume in artificial intelligence training, etc.), and the target task requirements are the requirements for completing the target task, such as the expected completion time, the required computational accuracy, etc.

[0078] The working principle and beneficial effects of the above technical solution are as follows: by constructing a cloud computing power resource center, the optimal cloud computing power resources can be obtained when achieving the target task, thereby ensuring the efficiency of completing the target task and saving resources, improving the adaptability to different target tasks, and by dynamically updating the cloud computing power resources according to the execution process until the target task is completed, the standard of the target task can be effectively guaranteed to be achieved within the expected completion time, and the accuracy and effectiveness of completing the task can be effectively guaranteed.

[0079] Example 2:

[0080] Based on Example 1, this example provides a cloud computing power analysis method, such as... Figure 2 As shown, step 1 involves constructing a cloud computing resource management center, including:

[0081] S101: Read several cloud computing resources, and at the same time, extract the resource characteristics and resource tags of each cloud computing resource.

[0082] S102: Read the feature types contained in the resource features and determine the feature labels based on the feature types;

[0083] S103: Generate a horizontal record chain based on feature labels, and at the same time, generate a vertical record chain based on resource labels;

[0084] S104: Based on feature tags and resource tags, several cloud computing resources are respectively mapped in the horizontal and vertical record chains to generate a comprehensive cloud computing resource node.

[0085] S105: Analyze the cloud computing power resource integrated nodes, determine the splitting marks of the cloud computing power resource integrated nodes, split and store the cloud computing power resource integrated nodes according to the splitting marks, and build a cloud computing power resource management center.

[0086] In this embodiment, resource characteristics represent information such as the type and value of cloud computing resources.

[0087] In this embodiment, resource tags are markers used to distinguish cloud computing resources.

[0088] In this embodiment, the feature type is used to represent the classification results of multiple different attributes in the resource features, such as the computing power, storage capacity and network bandwidth of cloud computing resources. One attribute corresponds to one feature type, and one feature type corresponds to one feature label.

[0089] In this embodiment, the horizontal recording chain is used to record the feature tags of cloud computing resources, and the vertical recording chain is used to record the resource tags of cloud computing resources. By performing data association mapping between feature tags and resource tags in the horizontal and vertical recording chains, a comprehensive cloud computing resource node is effectively generated.

[0090] The working principle and beneficial effects of the above technical solution are as follows: by determining the resource characteristics and resource tags of each cloud computing resource, data association mapping of different cloud computing resources is realized based on resource characteristics and resource tags, and then the integrated cloud computing resources are analyzed. This enables the integrated nodes of the integrated cloud computing resources to be split and stored, providing a reliable guarantee for cloud computing power analysis.

[0091] Example 3:

[0092] Based on Example 2, this example provides a cloud computing power analysis method, which analyzes the cloud computing power resource integration nodes, determines the splitting markers for the cloud computing power resource integration nodes, and splits and stores the cloud computing power resource integration nodes according to the splitting markers, including:

[0093] Read the cloud computing power resource integration node, determine the target similarity between the horizontal record chain of any cloud computing power resource in the cloud computing power resource integration node and the horizontal record chains of other cloud computing power resources, and mark the first position of any cloud computing power resource in the vertical record chain;

[0094] Mark the first target cloud computing resource when the target similarity reaches the preset condition among the remaining cloud computing resources, and locate the second position of the first target cloud computing resource in the vertical record chain;

[0095] Based on the first position and the corresponding second position, the cloud computing power resource integration node is split and marked to obtain multiple sub-cloud computing power resource integration nodes;

[0096] Construct storage intervals and store each sub-cloud computing power resource integrated node in the corresponding storage interval, and add resource tags to the storage intervals.

[0097] In this embodiment, the target similarity is used to characterize the degree of similarity between the horizontal record chain of any cloud computing power resource and the horizontal record chain of other cloud computing power resources. The larger the value, the more similar they are.

[0098] In this embodiment, the first position refers to the specific position information of different cloud computing resources in the vertical record chain.

[0099] In this embodiment, the preset conditions are set in advance.

[0100] In this embodiment, the first target cloud computing resource refers to the cloud computing resource that, when performing similarity determination, is based on any cloud computing resource as a benchmark and performs similarity analysis on other cloud computing resources, and is not unique.

[0101] In this embodiment, the second position refers to the specific position of other cloud computing resources in the vertical record chain when the determined target similarity reaches the preset condition.

[0102] In this embodiment, the sub-cloud computing power resource integrated node refers to the different cloud computing power resource integrated nodes obtained after splitting and marking the cloud computing power resource integrated node.

[0103] In this embodiment, resource tags refer to the marking symbols used to distinguish different sub-cloud computing power resource integration nodes.

[0104] The working principle and beneficial effects of the above technical solution are as follows: By analyzing the integrated nodes of cloud computing resources, the positions of different cloud computing resources in the horizontal and vertical record chains are determined. Finally, the integrated nodes of cloud computing resources are split and marked according to the determined positions, thereby locking multiple sub-cloud computing resource integrated nodes. Finally, the obtained multiple sub-cloud computing resource integrated nodes are stored in the constructed storage area, ensuring accurate and reliable integration of cloud computing resources and providing guarantee and convenience for cloud computing analysis.

[0105] Example 4:

[0106] Based on Example 1, this example provides a cloud computing power analysis method. In step 1, based on the user terminal inputting the target task, the task requirement information of the target task is obtained, including:

[0107] The target task is determined based on the user terminal, and the target task upload request is determined based on the target task;

[0108] The cloud computing platform verifies the eligibility of upload requests for target tasks, and once the eligibility verification is passed, it reads the upload request for the target task to determine the target task.

[0109] Read the target task and extract the keywords required for the task;

[0110] Based on the key requirements of the task, determine the task requirements information for the target task.

[0111] In this embodiment, the target task upload request is related to the type of the target task and the services it can handle, and is an introductory parameter of the target task sent to the cloud computing platform.

[0112] In this embodiment, qualification verification refers to verifying the compliance and permissions of the target task upload request through the cloud computing power platform.

[0113] In this embodiment, the task requirement keywords refer to the data fragments that represent the purpose or specific business processes of the target task after parsing the target task.

[0114] The working principle and beneficial effects of the above technical solution are as follows: by verifying the eligibility of the target task upload request of the user terminal, and parsing the target task upload request after the eligibility verification is passed, the task requirement information of the target task of the user terminal can be accurately and effectively determined according to the parsing result. This facilitates the allocation of cloud computing resources according to the task requirement information, and ensures the processing effect and reliability of the target task of the user terminal.

[0115] Example 5:

[0116] Based on Example 1, this example provides a cloud computing power analysis method. In step 2, the available cloud computing power resources are evaluated in the cloud computing power resource management center according to the task requirement information, including:

[0117] Read the task requirement information and determine the requirement dimensions and the requirement standards under each requirement dimension.

[0118] Input the demand dimensions and the demand criteria under each demand dimension into the cloud computing power resource management center for matching, and determine the second target cloud computing power resource that meets the demand criteria.

[0119] Real-time monitoring of the working status of the second target cloud computing resources;

[0120] Extract the third target cloud computing resources that are in a non-working state from the working state of the second target cloud computing resources. The third target cloud computing resources are the available cloud computing resources.

[0121] In this embodiment, the requirement dimension refers to the different aspects of analyzing the task. The requirement standard corresponding to each requirement dimension is the execution condition and the purpose of executing and completing the task corresponding to the current requirement dimension.

[0122] In this embodiment, the second target cloud computing power resource is a cloud computing power resource used to characterize the task requirements that can be executed in accordance with the requirements dimension and the requirements standards under the requirements dimension.

[0123] In this embodiment, the third target cloud computing power resource is the cloud computing power resource in the second target cloud computing power resource that is in a non-working state.

[0124] The working principle and beneficial effects of the above technical solution are as follows: By parsing the task requirement information, the requirement dimensions corresponding to the task requirement information and the requirement standards under each requirement dimension are accurately and effectively determined. Secondly, based on the requirement dimensions and requirement standards, a second target cloud computing power resource that meets the requirement standards is matched from the cloud computing power resource management center, and the working status of the second target cloud computing power resource is determined in real time. This enables the effective acquisition of a third target cloud computing power resource that is not in a working state from the second target cloud computing power resource. Finally, the available cloud computing power resources are determined, providing convenience and guarantee for determining the optimal cloud computing power resources.

[0125] Example 6:

[0126] Based on Example 1, this example provides a cloud computing power analysis method. In step 3, the available cloud computing power resources are analyzed to obtain the optimal cloud computing power resources, and the target task input by the user terminal is executed based on the optimal cloud computing power resources, including:

[0127] The target task is read, the execution steps to complete the target task are determined, and the target task is divided according to the execution steps to obtain multiple sub-target tasks;

[0128] Read the resource requirement standards for each sub-target task;

[0129] Available cloud computing resources are pooled and managed to obtain a target resource pool, which includes a set of available cloud computing resources configurations.

[0130] Based on the resource requirement standards of each sub-target task, a matching process is performed in the target resource pool to obtain the target configuration sequence corresponding to each sub-target task;

[0131] The target configuration sequence corresponding to each sub-target task is sorted according to the execution order of the execution steps, and the target configuration sequence corresponding to each sub-target task is arranged and combined according to the sorting result to obtain multiple configuration combinations to complete the target task.

[0132] Select the target configuration combination from multiple configuration combinations as the best cloud computing resources, and execute the target task based on the best cloud computing resources.

[0133] In this embodiment, the sub-target task is the result of splitting the target task according to the execution steps, with one execution step corresponding to one sub-target task.

[0134] In this embodiment, pooling management of available cloud computing resources is the result of centralizing and managing available cloud computing resources such as CPUs and GPUs, and forming a target resource pool.

[0135] The working principle and beneficial effects of the above technical solution are as follows: By analyzing the target task, the execution steps of the target task are determined, thereby dividing the target task into multiple sub-target tasks based on the execution steps. Secondly, the resource requirement standards for each sub-target task are determined and matched with the target resource pool after pooling available cloud computing resources, thereby locking the target configuration sequence corresponding to each sub-target task and providing a guarantee for determining the cloud computing resources corresponding to the target task. Finally, the target configuration sequence corresponding to each sub-target task is arranged and combined according to the execution order of the execution steps, thereby accurately and reliably determining the optimal cloud computing resources, thus ensuring the reliability, accuracy, and efficiency of the execution of the target task.

[0136] Example 7:

[0137] Based on Example 6, this example provides a cloud computing power analysis method, which extracts a target configuration combination as the optimal cloud computing power resource from multiple configuration combinations, and executes the target task based on the optimal cloud computing power resource, including:

[0138] Obtain the task parameters for executing the target task, and simulate the task parameters for executing the target task in the computer. At the same time, simulate the execution of the target task in the computer based on multiple configuration combinations, and obtain the completion efficiency of each configuration combination.

[0139] The top two configuration combinations in terms of completion efficiency are selected, and the configuration combination with the highest completion efficiency is selected as the best cloud computing power resource. Meanwhile, the configuration combination with the second highest completion efficiency is selected as the alternative cloud computing power resource.

[0140] The target task input by the user terminal is executed based on the best cloud computing resources, and alternative cloud computing resources are activated when the best cloud computing resources cannot be used.

[0141] In this embodiment, task parameters refer to parameters such as the amount of computation and processing speed required to complete the target task.

[0142] In this embodiment, alternative cloud computing resources are used as candidate resources for the best cloud computing resources. Secondly, based on the ranking results, the same logic can be applied. When alternative cloud computing resources are used as the best cloud computing resources, if the best cloud computing resources cannot be executed, then the configuration combination ranked third in efficiency is determined, etc., until the execution of the target task is completed.

[0143] The working principle and beneficial effects of the above technical solution are as follows: by determining the completion efficiency, the optimal cloud computing resources and alternative cloud computing resources can be effectively determined, which can ensure the effectiveness and accuracy of executing the target task, thereby ensuring the efficient completion of the target task.

[0144] Example 8:

[0145] Based on Example 1, this example provides a cloud computing power analysis method. In step 4, the execution process is collected, and cloud computing power resources are dynamically updated according to the execution process until the target task is completed, including:

[0146] When executing a target task based on the best cloud computing resources, the execution process of the target task is collected in real time to determine the real-time progress of the target task.

[0147] The remaining execution volume and execution time of the target task are determined based on the real-time progress of the task.

[0148] Obtain the optimal execution speed of cloud computing resources, and determine the remaining time to complete the target task based on the optimal execution speed of cloud computing resources and the remaining execution volume of the target task;

[0149] Obtain the expected completion time for the target task, and calculate the target difference between the expected completion time and the execution time.

[0150] Compare the remaining time with the target difference time to determine whether cloud computing resources need to be updated.

[0151] If the remaining time is less than or equal to the target difference time, it is determined that cloud computing resources do not need to be updated.

[0152] Otherwise, it is determined that cloud computing resources need to be updated, and cloud computing resources that meet the target difference time are retrieved from the cloud computing resource management center. At the same time, the current best cloud computing resources are updated based on the retrieval results.

[0153] In this embodiment, the remaining time to complete the target task can be determined based on the execution speed of the optimal cloud computing resources and the remaining execution amount of the target task: Remaining execution amount / execution speed = Remaining time to complete the target task.

[0154] In this embodiment, retrieving cloud computing resources that meet the target time difference from the cloud computing resource management center is equivalent to determining cloud computing resources in the cloud computing resource management center that can complete the task within the target time difference.

[0155] The working principle and beneficial effects of the above technical solution are as follows: by collecting and executing data in real time, the real-time progress of completing the target task can be effectively grasped, thereby effectively determining the remaining time to complete the target task. By determining the target difference between the expected completion time and the execution time and comparing it with the remaining time, the measurement of whether to update cloud computing resources can be effectively realized, which is conducive to ensuring the smooth progress of the target task.

[0156] Example 9:

[0157] This embodiment provides a cloud computing power platform, including: steps for performing a cloud computing power parsing method as described in any one of embodiments 1 to 8.

[0158] The working principle and beneficial effects of the above technical solution are as follows: by constructing a cloud computing power resource center, the optimal cloud computing power resources can be obtained when achieving the target task, thereby ensuring the efficiency of completing the target task and saving resources, improving the adaptability to different target tasks, and by dynamically updating the cloud computing power resources according to the execution process until the target task is completed, the standard of the target task can be effectively guaranteed to be achieved within the expected completion time, and the accuracy and effectiveness of completing the task can be effectively guaranteed.

[0159] Example 10:

[0160] This embodiment provides a cloud computing power analysis system, such as Figure 3 As shown, it includes:

[0161] The module is used to build a cloud computing resource management center. At the same time, it obtains the task requirements information of the target task based on the user terminal input of the target task.

[0162] The evaluation module is used to evaluate available cloud computing resources in the cloud computing resource management center based on task requirements information;

[0163] The analysis module is used to analyze available cloud computing resources, obtain the best cloud computing resources, and execute the target task input to the user terminal based on the best cloud computing resources.

[0164] The update module is used to collect the execution process and dynamically update the cloud computing resources based on the execution process until the target task is completed.

[0165] The working principle and beneficial effects of the above technical solution are as follows: by constructing a cloud computing power resource center, the optimal cloud computing power resources can be obtained when achieving the target task, thereby ensuring the efficiency of completing the target task and saving resources, improving the adaptability to different target tasks, and by dynamically updating the cloud computing power resources according to the execution process until the target task is completed, the standard of the target task can be effectively guaranteed to be achieved within the expected completion time, and the accuracy and effectiveness of completing the task can be effectively guaranteed.

[0166] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A cloud computing power resolution method, characterized in that, The application comprises the following steps: Step 1: Constructing a cloud computing resource management center, inputting a target task based on a user terminal, and obtaining task demand information of the target task; Step 2: Evaluating available cloud computing resources in the cloud computing resource management center according to the task demand information; Step 3: Analyzing the available cloud computing resources, obtaining the best cloud computing resources, and executing the target task input by the user terminal based on the best cloud computing resources; Step 4: Collecting the execution process and dynamically updating the cloud computing resources according to the execution process until the target task is completed. In step 1, the cloud computing resource management center is constructed, comprising: Reading a plurality of cloud computing resources, and extracting the resource characteristics and resource labels of each cloud computing resource; Reading the feature types contained in the resource characteristics, and determining the feature labels according to the feature types; Generating a horizontal record chain according to the feature labels, and generating a vertical record chain according to the resource labels; Data association mapping of the plurality of cloud computing resources in the horizontal record chain and the vertical record chain according to the feature labels and the resource labels to generate a cloud computing resource comprehensive node; Analyzing the cloud computing resource comprehensive node, determining the split mark of the cloud computing resource comprehensive node, and splitting and storing the cloud computing resource comprehensive node according to the split mark to construct the cloud computing resource management center; Analyzing the cloud computing resource comprehensive node, determining the split mark of the cloud computing resource comprehensive node, and splitting and storing the cloud computing resource comprehensive node according to the split mark, comprising: Reading the cloud computing resource comprehensive node, determining the target similarity between the horizontal record chain of any cloud computing resource in the cloud computing resource comprehensive node and the horizontal record chain of the remaining cloud computing resources, and marking the first position of any cloud computing resource in the vertical record chain; Marking the first target cloud computing resource when the target similarity reaches a preset condition among the remaining cloud computing resources, and positioning the second position of the first target cloud computing resource in the vertical record chain; Splitting and marking the cloud computing resource comprehensive node according to the first position and the corresponding second position to obtain a plurality of sub-cloud computing resource comprehensive nodes; Constructing a storage interval and storing each sub-cloud computing resource comprehensive node in the corresponding storage interval, and adding a resource label in the storage interval. 2.The cloud computing power resolution method of claim 1, wherein, In step 1, the target task is input based on the user terminal, and the task demand information of the target task is obtained, comprising: Determining the target task based on the user terminal, and determining the target task upload request according to the target task; Qualification verification of the target task upload request based on the cloud computing platform, and reading the target task upload request when the qualification verification is passed to determine the target task; Reading the target task and extracting the task demand keywords; Determining the task demand information of the target task according to the task demand key.

3. The cloud computing power resolution method of claim 1, wherein, In step 2, the available cloud computing resources in the cloud computing resource management center are evaluated according to the task demand information, comprising: Reading the task demand information to determine the demand dimensions in the task demand information and the demand standards under each demand dimension; The demand dimensions and the demand standards under each demand dimension are input into the cloud computing resource management center for matching to determine the second target cloud computing resource that meets the demand standards; The working state of the second target cloud computing resource is read in real time; The third target cloud computing resource in the non-working state in the working state of the second target cloud computing resource is extracted, wherein the third target cloud computing resource is the available cloud computing resource.

4. The cloud computing power resolution method of claim 1, wherein, In step 3, the available cloud computing resource is analyzed to obtain the best cloud computing resource, and the target task input by the user terminal is executed based on the best cloud computing resource, including: The target task is read to determine the execution steps for completing the target task, the target task is divided according to the execution steps, and a plurality of sub-target tasks are obtained; The resource demand standard of each sub-target task is read; The available cloud computing resource is managed in a pool to obtain a target resource pool, wherein the target resource pool includes a configuration set of the available cloud computing resource; Each sub-target task is matched in the target resource pool according to the resource demand standard of each sub-target task to obtain a target configuration sequence corresponding to each sub-target task; The target configuration sequence corresponding to each sub-target task is sorted according to the execution order of the execution steps, and the target configuration sequence corresponding to each sub-target task is arranged and combined according to the sorting result to obtain a plurality of configuration combinations for completing the target task; The target configuration combination is extracted from the plurality of configuration combinations as the best cloud computing resource, and the target task is executed according to the best cloud computing resource.

5. The cloud computing power resolution method of claim 4, wherein, The target configuration combination is extracted from the plurality of configuration combinations as the best cloud computing resource, and the target task is executed according to the best cloud computing resource, including: The task parameters for executing the target task are obtained, and the task parameters for executing the target task are simulated in the computer, and at the same time, the target task is simulated and executed in the computer based on the plurality of configuration combinations to obtain the completion efficiency of each configuration combination; The configuration combination with the second highest completion efficiency is extracted, and the configuration combination with the first highest completion efficiency is taken as the best cloud computing resource, and the configuration combination with the second highest completion efficiency is taken as the alternative cloud computing resource; The target task input by the user terminal is executed according to the best cloud computing resource, and when the best cloud computing resource cannot be executed, the alternative cloud computing resource is started.

6. The cloud computing power resolution method of claim 1, wherein, In step 4, the execution process is collected, and the cloud computing resource is dynamically updated according to the execution process until the target task is completed, including: When the target task is executed based on the best cloud computing resource, the execution process of executing the target task is collected in real time to determine the real-time progress of executing the target task; The remaining execution amount and the execution time of the target task are determined according to the real-time progress of executing the task; The execution speed of the best cloud computing resource is obtained, and the remaining time to complete the target task is determined according to the execution speed of the best cloud computing resource and the remaining execution amount of the target task; The expected completion time of completing the target task is obtained, and a target difference time between the expected completion time and the execution time is calculated; The remaining time and the target difference time are compared to determine whether the cloud computing resource needs to be updated; When the remaining time is less than or equal to the target difference time, it is determined that the cloud computing resource does not need to be updated; Otherwise, it is determined that cloud computing resources need to be updated, and cloud computing resources that meet the target difference time are retrieved from the cloud computing resource management center. At the same time, the current best cloud computing resources are updated based on the retrieval results.

7. A cloud computing platform, characterized by, include: The steps for performing a cloud computing power parsing method as described in any one of claims 1 to 6.

8. A cloud computing power resolution system, characterized in that, include: The module is used to build a cloud computing resource management center. At the same time, it obtains the task requirements information of the target task based on the user terminal input of the target task. The evaluation module is used to evaluate available cloud computing resources in the cloud computing resource management center based on task requirements information; The analysis module is used to analyze available cloud computing resources, obtain the best cloud computing resources, and execute the target task input to the user terminal based on the best cloud computing resources. The update module is used to collect the execution process and dynamically update the cloud computing resources according to the execution process until the target task is completed; The build module includes the construction of a cloud computing resource management center, comprising: Read several cloud computing resources, and extract the resource characteristics and resource tags of each cloud computing resource respectively; Read the feature types contained in the resource characteristics and determine the feature labels based on the feature types; A horizontal record chain is generated based on feature labels, and a vertical record chain is generated based on resource labels. Several cloud computing resources are mapped and associated in the horizontal and vertical record chains according to feature tags and resource tags to generate a comprehensive cloud computing resource node. Analyze the integrated nodes of cloud computing resources, determine the splitting markers for the integrated nodes of cloud computing resources, split and store the integrated nodes of cloud computing resources according to the splitting markers, and build a cloud computing resource management center; Analyze the integrated cloud computing resource nodes, determine the splitting markers for the integrated cloud computing resource nodes, and split and store the integrated cloud computing resource nodes according to the splitting markers, including: Read the cloud computing power resource integration node, determine the target similarity between the horizontal record chain of any cloud computing power resource in the cloud computing power resource integration node and the horizontal record chains of other cloud computing power resources, and mark the first position of any cloud computing power resource in the vertical record chain; Mark the first target cloud computing resource when the target similarity reaches the preset condition among the remaining cloud computing resources, and locate the second position of the first target cloud computing resource in the vertical record chain; Based on the first position and the corresponding second position, the cloud computing power resource integration node is split and marked to obtain multiple sub-cloud computing power resource integration nodes; Construct storage intervals and store each sub-cloud computing power resource integrated node in the corresponding storage interval, and add resource tags to the storage intervals.

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