AI-based cloud service cost-benefit analysis system

Abstract

The invention provides an AI-based cloud service cost-benefit analysis system, which belongs to the technical field of cloud computing and comprises data acquisition, data preprocessing, data mining and analysis, machine learning and prediction, intelligent optimization and decision making, deep learning and feature extraction and result display and report. Through the modules, the system can provide accurate cloud service cost and benefit prediction for enterprises, and helps the enterprises optimize resource configuration, reduce cost and improve benefits. Advantages of the system include high automation, accurate prediction, real-time monitoring, and cross-cloud platform compatibility and personalized management, which together improve cost benefits of enterprises.

Description

Technical Field

[0001] The present invention relates to the intersection of cloud computing and artificial intelligence (AI) technology, and in particular to a system for cost-benefit analysis of cloud services based on AI. Background Art

[0002] With the rapid development of cloud computing technology, more and more enterprises are migrating their businesses to cloud platforms. The rapid development of cloud computing technology provides enterprises with flexible and scalable computing resources, enabling them to quickly respond to market changes and improve business efficiency. However, as enterprises continue to increase their demand for cloud services, while enjoying the benefits of cloud services, the issue of cloud service cost management is becoming increasingly prominent. How to effectively manage cloud service costs and improve the benefits of using cloud services is a challenge. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a system for cost-benefit analysis of cloud services based on AI. By collecting relevant data on the use of cloud services by enterprises, such as resource usage, service fees, etc., and using data mining technology to process and analyze these data, information on the cost and benefit of cloud services can be obtained. By analyzing this information, enterprises can fully understand the cost and benefit of cloud services, and optimize resource allocation based on the analysis results, reduce costs, and improve benefits.

[0004] The technical solution of the present invention is:

[0005] A system for cost-benefit analysis of cloud services based on AI, comprising:

[0006] The data collection and preprocessing module collects data related to the use of cloud services by enterprises, processes and analyzes these data using data mining technology, and can obtain information about the cost and benefits of cloud services;

[0007] Data mining and analysis module, which conducts in-depth analysis on pre-processed data to mine information and patterns;

[0008] AI learning and prediction module, which uses machine learning models to predict the costs and benefits of cloud services to analyze data and predict future resource requirements and costs;

[0009] Intelligent optimization and decision-making module provides users with cost optimization suggestions based on the results of AI analysis models;

[0010] Deep learning and feature extraction module, which uses deep learning technology to automatically extract features of cloud service data;

[0011] The result display and reporting module displays the analysis results to enterprise users in a visual way and provides detailed reports and optimization suggestions;

[0012] Automation and integration, which can be integrated into IT management and financial systems to achieve automated reporting and early warning functions;

[0013] The security and compliance module ensures that the system's data collection, storage, and analysis processes comply with relevant laws, regulations, and best practices.

[0014] Furthermore,

[0015] The data collection and preprocessing module also needs to integrate business data, including user visits and transaction volumes, in order to conduct cost-benefit analysis.

[0016] Data mining methods include cluster analysis, association rule mining and time series analysis.

[0017] Preprocess the data, including data cleaning, deduplication and missing value processing.

[0018] The AI ​​learning and prediction module predicts the cost and benefits of cloud services by building machine learning models, including linear regression, support vector machines, and neural networks, and adjusts resource usage strategies in advance based on the prediction results. It predicts the usage trend and cost changes of cloud service resources based on historical data and business development.

[0019] Automatically extract features of cloud service data through convolutional neural network (CNN) and recurrent neural network (RNN).

[0020] The security and compliance module needs to have data protection and privacy protection capabilities.

[0021] 1. Intelligent data analysis: The system uses artificial intelligence technologies, including data mining, machine learning, and deep learning, to conduct intelligent analysis of cloud service usage data to identify cost-saving opportunities and strategies to improve efficiency.

[0022] 2. Predictive modeling: The system uses machine learning models to predict the costs and benefits of cloud services, enabling enterprises to make more accurate decisions based on future trends.

[0023] 3. Resource optimization suggestions: Based on intelligent optimization algorithms, the system provides personalized resource allocation suggestions to help enterprises optimize cloud service resource configuration, reduce costs and improve efficiency.

[0024] 4. Comprehensive monitoring mechanism: The system monitors resource utilization, network traffic, expense expenditure and service level agreement compliance in real time to ensure transparency and compliance of enterprise cloud service use.

[0025] 5. Automated alerts and responses: The system has an automatic alert function that can promptly alert the enterprise when potential cost waste or performance issues are detected, and recommend corresponding optimization measures.

[0026] 6. User-friendly interactive interface: The system provides intuitive dashboards and reports, allowing business users to easily understand complex cost data and make decisions based on visual information.

[0027] 7. Cross-cloud platform compatibility: The system is designed with multi-cloud and hybrid cloud environments in mind, and is able to perform cost-benefit analysis across different cloud service providers, providing enterprises with a comprehensive perspective.

[0028] 8. Scalability and adaptability: The system architecture is flexible and can be expanded and adjusted as the enterprise business develops and the cloud service market changes.

[0029] The beneficial effects of the present invention are

[0030] 1. Cost transparency and control: The system improves cost transparency by clearly displaying the cost structure of cloud services, enabling enterprises to more effectively monitor and control cloud service expenditures.

[0031] 2. Benefit measurement and optimization: The system can quantify the business value brought by cloud services and help enterprises comprehensively evaluate cost-effectiveness, thereby achieving optimal resource allocation and improvement of business processes.

[0032] 3. Improved forecasting and planning capabilities: Using predictive analysis based on AI technology, enterprises can more accurately predict future cloud service demand and costs, providing a basis for resource planning and budget management.

[0033] 4. Automated resource optimization: The system automatically adjusts resource allocation to meet the business needs of the enterprise at the lowest cost, reducing the need for manual intervention and improving efficiency and accuracy.

[0034] 5. Personalized and intelligent recommendations: The system provides personalized cost optimization recommendations that take into account the unique needs of the enterprise and help the enterprise formulate a cloud service strategy based on its own situation.

[0035] 6. Performance and reliability enhancement: By monitoring the performance indicators of cloud services, the system can promptly detect potential problems and take measures to prevent service interruptions, thereby improving the overall service reliability and user experience.

[0036] 7.SLA compliance monitoring: The system monitors the cloud service provider’s compliance with the service level agreement to ensure that the enterprise obtains the promised service quality and reduces losses caused by substandard services.

[0037] 8. Network traffic and cost monitoring: The system monitors network traffic and costs to help companies avoid unnecessary expenses, such as high data transmission costs.

[0038] In summary, the AI-based cloud service cost-benefit analysis system and method has brought significant benefits to enterprises, including cost savings, resource optimization, improved forecasting capabilities, enhanced decision support, and improved overall operational efficiency. With the continuous advancement of technology, these effects will be further enhanced, bringing greater value to enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the system workflow of the present invention;

[0040] Figure 2 It is an overview of the functions of each module of the system and a schematic diagram of their connections;

[0041] Figure 3 It is the key technical effect diagram of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0043] The present invention provides a system for cost-benefit analysis of cloud services based on AI, with the aim of providing an efficient and accurate cloud service cost management solution to help enterprises achieve cost optimization and benefit maximization when using cloud service resources, aiming to solve the following problems:

[0044] 1. Cost transparency: Enterprises often lack a clear understanding of their actual expenditures on cloud services, especially when using multiple cloud service providers. One of the purposes of the invention is to provide a system that can clearly display the cost structure of an enterprise on cloud services, including the costs of different service types and providers, thereby improving cost transparency.

[0045] 2. Benefit measurement: In addition to costs, enterprises also need to evaluate the benefits of their cloud service investments. The purpose of this system and method is to provide a method that can quantify the business value brought by cloud services, such as improving operational efficiency and enhancing business flexibility, so that enterprises can comprehensively evaluate the cost-effectiveness of cloud services.

[0046] 3. Forecasting and planning: Enterprises need to be able to predict future cloud service demand and costs in order to conduct effective resource planning and budget management. One of the purposes of the invention is to use AI technologies, such as machine learning and time series analysis, to predict cloud service usage patterns and cost trends to help enterprises make more accurate decisions.

[0047] 4. Automated Optimization: Manual optimization of cloud service resource allocation is time-consuming and error-prone. The purpose of this system and method is to achieve automated resource optimization, dynamically adjust resource allocation through intelligent algorithms, and meet the business needs of enterprises at the lowest cost.

[0048] 5. Personalized and intelligent suggestions: Different enterprises have different business needs and cost tolerance. One of the purposes of the invention is to provide personalized cost optimization suggestions, use AI technology to analyze the unique needs of enterprises, and provide customized cloud service configurations and cost-saving strategies.

[0049] To sum up, the purpose of the invention of this system and method is to provide a comprehensive cloud service cost-benefit analysis tool through the application of AI technology, to help enterprises achieve cost control and benefit improvement, and ultimately support enterprises to gain competitive advantages in the digital economy era.

[0050] The system structure of the present invention includes the following modules:

[0051] Data acquisition and preprocessing module;

[0052] Data mining and analysis module;

[0053] AI learning and prediction module;

[0054] Intelligent optimization and decision-making module;

[0055] Deep learning and feature extraction module;

[0056] Results display and reporting module;

[0057] Automation and integration;

[0058] Security and Compliance Module;

[0059] in,

[0060] Data acquisition and preprocessing module:

[0061] Data mining and analysis are the basis of cost-benefit analysis of cloud services. The system needs to collect cloud service usage data, including but not limited to the usage of computing resources, storage resources, and network resources, as well as related cost information. By collecting relevant data on the use of cloud services by enterprises, such as resource usage, service fees, etc., and using data mining technology to process and analyze these data, information about the cost and benefits of cloud services can be obtained.

[0062] At the same time, it is also necessary to integrate business data, such as user visits, transaction volume, etc., in order to conduct a more comprehensive cost-benefit analysis.

[0063] Commonly used data mining methods include cluster analysis, association rule mining and time series analysis.

[0064] These data are preprocessed, including data cleaning, deduplication and missing value processing, to ensure data quality.

[0065] Data mining and analysis module:

[0066] Through data mining techniques, such as cluster analysis, association rule mining and time series analysis, the pre-processed data is deeply analyzed to mine valuable information and rules.

[0067] AI learning and prediction module:

[0068] Machine learning technology also plays an important role in the cost-benefit analysis of cloud services. Machine learning models are used to predict the costs and benefits of cloud services to analyze data and predict future resource requirements and costs. By building machine learning models such as linear regression, support vector machines, and neural networks, the costs and benefits of cloud services can be predicted. Based on the prediction results, enterprises can adjust resource usage strategies in advance to achieve cost optimization.

[0069] The model needs to be able to predict the usage trends and cost changes of cloud service resources based on historical data and business development.

[0070] Intelligent optimization and decision-making module:

[0071] Intelligent optimization algorithms can help enterprises maximize costs and benefits under limited resource constraints. Common intelligent optimization algorithms include genetic algorithms, ant colony algorithms, and particle swarm optimization. Through these algorithms, enterprises can find the best resource allocation plan, reduce costs, and improve benefits.

[0072] The system should be able to provide users with cost optimization suggestions based on the results of the AI ​​analysis model, such as adjusting resource allocation, optimizing service types, and selecting a more economical billing model.

[0073] Deep learning and feature extraction module:

[0074] The application of deep learning technology in cloud service cost-benefit analysis is mainly reflected in feature extraction and model construction. Deep learning technology is used to automatically extract the features of cloud service data and improve the accuracy of cost-benefit analysis.

[0075] Through deep learning models such as convolutional neural networks (CNN) and recurrent neural networks (RNN), the features of cloud service data can be automatically extracted to improve the accuracy of cost-benefit analysis.

[0076] Results display and reporting module:

[0077] The analysis results are presented to business users in a visual way, providing detailed reports and optimization suggestions so that users can easily understand and take action.

[0078] Automation and integration modules:

[0079] The system can be integrated into the enterprise's IT management and financial systems to achieve automated reporting and early warning functions.

[0080] Security and Compliance Module:

[0081] Ensure that the system's data collection, storage and analysis processes comply with relevant laws, regulations and best practices, especially requirements in terms of data protection and privacy protection.

[0082] When implementing such a system, key technical points to consider include:

[0083] Big data processing capabilities: Ability to process and analyze large-scale data sets.

[0084] Real-time analysis and feedback: The system should be able to provide real-time or near real-time analysis to quickly respond to market changes.

[0085] Model accuracy and adaptability: AI models need to continuously learn and adapt to new data to improve the accuracy of predictions.

[0086] User-friendliness: Ensure that the system is easy to use and lower the threshold for users.

[0087] The AI-based methods and technologies of the present invention provide new ideas and means for cloud service cost-benefit analysis, which is expected to help enterprises better manage cloud service costs and improve the efficiency of cloud service use. With the continuous advancement and application of AI technology, the AI-based cloud service cost-benefit analysis system and method will play an increasingly important role in enterprise cloud service management.

[0088] The above description is only a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, and is not used to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A system for cost-benefit analysis of cloud services based on AI, characterized in that: include: The data collection and preprocessing module collects data related to the use of cloud services by enterprises, processes and analyzes these data using data mining technology, and can obtain information about the cost and benefits of cloud services; Data mining and analysis module, which conducts in-depth analysis on pre-processed data to mine information and patterns; AI learning and prediction module, which uses machine learning models to predict the costs and benefits of cloud services to analyze data and predict future resource requirements and costs; Intelligent optimization and decision-making module provides users with cost optimization suggestions based on the results of AI analysis models; Deep learning and feature extraction module, which uses deep learning technology to automatically extract features of cloud service data; The result display and reporting module displays the analysis results to enterprise users in a visual way and provides detailed reports and optimization suggestions; Automation and integration, which can be integrated into IT management and financial systems to achieve automated reporting and early warning functions; The security and compliance module ensures that the system's data collection, storage, and analysis processes comply with relevant laws, regulations, and best practices.

2. The system according to claim 1, characterized in that The data collection and preprocessing module also needs to integrate business data, including user visits and transaction volumes, in order to conduct cost-benefit analysis.

3. The system according to claim 1, characterized in that Data mining methods include cluster analysis, association rule mining and time series analysis.

4. The system according to claim 1, characterized in that Preprocess the data, including data cleaning, deduplication and missing value processing.

5. The system according to claim 1, characterized in that The AI ​​learning and prediction module predicts the costs and benefits of cloud services by building machine learning models, including linear regression, support vector machines, and neural networks, and adjusts resource usage strategies in advance based on the prediction results.

6. The system according to claim 5, characterized in that Predict usage trends and cost changes of cloud service resources based on historical data and business development.

7. The system according to claim 1, characterized in that Automatically extract features of cloud service data through convolutional neural network (CNN) and recurrent neural network (RNN).

8. The system according to claim 1, characterized in that The security and compliance module needs to have data protection and privacy protection capabilities.

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