A visual virtual component intelligent upgrading method based on upgrading demand priority

Abstract

This patent proposes a visual virtual component intelligent upgrade method based on upgrade demand priority. Its innovation points include using mesh topology to visually display the dependency relationship between virtual components, each node contains detailed component information, and the consumption of virtual components is visually displayed through a heat map. It supports time dimension data analysis and provides two upgrade modes: full automatic and manual. The full automatic mode calculates the upgrade order according to the component load and upgrade reward, while the manual mode relies on human decision-making. A detailed upgrade reward calculation formula is defined, which considers the benefits, costs and risks brought by component upgrade. A detailed upgrade process is provided, including software package upload, sending upgrade request, generating upgrade instruction, and executing upgrade. It supports upgrade success confirmation and result feedback. This method is structured and intuitive, automated and intelligent, significantly improving the efficiency and effectiveness of virtual component management.

Description

Technical Field

[0001] This invention belongs to the field of computer science and technology, and specifically relates to a method for intelligent upgrading of visualized virtual components based on upgrade requirement priority. Background Technology

[0002] In today's rapidly evolving information technology environment, the construction and application of virtual components have become a crucial part of the informatization process across various industries. With the continuous improvement of cloud computing technology, big data analytics, and graphics processing capabilities, virtualization technology is widely used in multiple areas such as server clusters, network storage, and application deployment, leading to a significant increase in the number and complexity of virtual components.

[0003] Traditional methods for upgrading virtual components often rely on manual intervention or preset rules. When faced with large-scale, highly dynamic virtual environments, this approach can suffer from low upgrade efficiency, management difficulties, and unintuitive status monitoring. Therefore, the industry urgently needs an innovative method to address these issues and achieve more refined, automated, and visualized intelligent upgrade management of virtual components. Summary of the Invention

[0004] In view of the above, this patent proposes a visualized intelligent upgrade method for virtual components based on upgrade requirement priority. This method aims to overcome the shortcomings of existing technologies by using advanced data processing and graphical interface display technologies to visually represent the complex structure of virtual components and their upgrade process. This allows administrators to clearly grasp the real-time status of system components and perform efficient and accurate resource allocation and version update operations, thereby improving the overall system's operational efficiency and service quality. This method has significant practical value in simplifying operation and maintenance processes, reducing operation and maintenance costs, and improving user satisfaction.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for intelligently upgrading visualized virtual components based on upgrade requirement priority, comprising the following steps in fully automatic upgrade mode:

[0007] Step 1: The system creates an upgrade list. Each element in the upgrade list includes: virtual component number, virtual component version, and virtual component upgrade requirement.

[0008] Step 2: The system sorts the virtual components to be upgraded in the upgrade list according to the upgrade requirement of each virtual component calculated by the formula, and sorts them in descending order of upgrade requirement.

[0009] Step 3: Locate the virtual components at the top of the upgrade list;

[0010] Step 4: Upload the software package containing the new version of the virtual component to the system backend server;

[0011] Step 5: The system sends an upgrade request to the Virtual Component Manager, carrying information about the new virtual component version. This request includes key data such as the version number of the new virtual component to be upgraded to.

[0012] Step 6: After receiving the upgrade request, the virtual component manager will generate the corresponding upgrade instruction and then send the instruction to the virtual component upgrade module.

[0013] Step 7: After receiving the upgrade instruction, the virtual component upgrade module is responsible for executing the virtual component upgrade operation.

[0014] Step 8, which includes downloading the specified new version of the virtual component package from the server, stopping the currently running virtual component instance, and installing and configuring the new version of the virtual component;

[0015] Step 9: When the new version of the virtual component is successfully deployed and running stably, the virtual component upgrade module will confirm that the virtual component upgrade has been successfully completed and send this result back to the virtual component manager.

[0016] Step 10: After receiving confirmation of successful virtual component upgrade, the virtual component manager sends an upgrade completion notification to the system front-end, indicating that the virtual component upgrade process has been successfully completed.

[0017] A method for intelligently upgrading visualized virtual components based on upgrade requirement priority includes the following steps in manual upgrade mode:

[0018] Step 1: The operator views the heat map and, based on actual usage, selects the virtual components that need to be upgraded.

[0019] Step 2: Upload the software package containing the new version of the virtual component to the system backend server.

[0020] Step 3: The system sends an upgrade request to the Virtual Component Manager, carrying information about the new virtual component version. This request includes key data such as the version number of the new virtual component to be upgraded to.

[0021] Step 4: After receiving the upgrade request, the Virtual Component Manager will generate the corresponding upgrade instruction and then send the instruction to the Virtual Component Upgrade Module.

[0022] Step 5: After receiving the upgrade instruction, the virtual component upgrade module is responsible for executing the virtual component upgrade operation.

[0023] Step 6 includes downloading the specified new version of the virtual component package from the server, stopping the currently running virtual component instance, and installing and configuring the new version of the virtual component.

[0024] Step 7: When the new version of the virtual component is successfully deployed and running stably, the virtual component upgrade module will confirm that the virtual component upgrade has been successfully completed and send this result back to the virtual component manager.

[0025] Step 8: After receiving confirmation of successful virtual component upgrade, the virtual component manager sends an upgrade completion notification to the system front-end, indicating that the virtual component upgrade process has been successfully completed. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating the construction process of a mesh topology and heatmap for a visual virtual component as described in this invention.

[0027] Figure 2 This is a flowchart of a visual virtual component intelligent upgrade method based on upgrade requirement priority, as described in this invention.

[0028] Figure 3 This is a model architecture diagram of a visualized virtual component intelligent upgrade method based on upgrade requirement priority, as described in this invention. Detailed Implementation

[0029] The technical solutions in the implementation of this invention will be clearly and completely described below with reference to specific examples.

[0030] Example 1: Using a mesh topology to display the dependencies between virtual components and using a heatmap to map the load on virtual components, including:

[0031] The application of mesh topology in visualizing virtual component dependencies significantly improves the efficiency and effectiveness of component management. By employing a structured and intuitive mesh representation, this invention provides an effective means to visually represent the interdependencies between virtual components such as virtual machines, storage, and network devices. Using the mesh topology proposed in this invention, users can clearly identify connection paths, dependencies, and potential performance bottlenecks between components, thereby enabling better management and upgrades of virtual components.

[0032] In the mesh topology described above, each node cleverly represents a specific virtual component, such as a virtual machine, storage device, or network device. More importantly, these nodes are not merely simple identifiers, but contain specific information about the virtual component.

[0033] Specifically, each node contains identification information for the virtual component, such as its name or unique identifier, as well as a series of detailed information about the component's attributes. This attribute information may include, but is not limited to, the component's type, state, configuration parameters, version, and connection relationships with other components.

[0034] In this invention, we introduce an innovative heatmap display mechanism to intuitively reveal hotspots in virtual component consumption. This heatmap display method uses color gradients to visually present the degree of component consumption, enabling decision-makers to quickly identify bottlenecks and hotspots in component usage, thereby providing strong support for component upgrade and optimization decisions.

[0035] Specifically, the colored blocks in the heatmap represent the consumption of virtual components; the darker the color, the greater the consumption of that virtual component, and vice versa. In this way, decision-makers can intuitively understand which areas have high component utilization and which areas may have idle components.

[0036] This example demonstrates how to use a mesh topology to show the dependencies between virtual components and uses a heatmap to map the load of virtual components. The steps to set it up are as follows:

[0037] Step 1: Establish an information matrix to store specific information for each virtual private component. The size of the information matrix depends on the number of virtual components. The number of rows is equal to the number of virtual components, and the number of columns is equal to the specific information of the virtual components, including but not limited to the name of the virtual component, firmware version, etc.

[0038] Step 2: Establish a connection matrix to store the dependencies between nodes. The connection matrix is ​​a matrix with an equal number of rows and columns, where each column represents the dependency of other virtual components on that component. For example, row 1, column 4 indicates that virtual component 4 depends on virtual component 1.

[0039] Step 3: Create a data table to store various data used to calculate the upgrade reward value of virtual components, as well as the load status of virtual components in different time periods.

[0040] Step 3: The system front-end reads the connection matrix and graphically represents the dependencies between virtual components in the form of a mesh topology diagram.

[0041] Step 4: The system front end reads the load data of each virtual component and overlays a heat map layer on the original mesh topology.

[0042] The heatmap features a color gradient mechanism. To accurately quantify the load of virtual components, the colors are divided into 100 blocks, which correspond to the load of virtual components from 0% to 100%.

[0043] When displayed in a dark color on a heatmap, it indicates that the virtual component is under high load.

[0044] When displayed in a light color on a heatmap, it indicates that the virtual component is in a low-load or no-load state.

[0045] When displayed in gray on a heatmap, it indicates that the virtual component is offline.

[0046] Step 5: Build a sliding window on the system front end to display the load status of each load in different time periods.

[0047] Decision-makers can observe the changing trends of component consumption hotspots over time by sliding the timeline, gaining a deeper understanding of component usage.

[0048] In steps 1 and 2, the information matrix and the connection matrix can be created as separate data tables in the database for easy retrieval later.

[0049] Example 2: A visual virtual component intelligent upgrade method based on upgrade requirement priority, the upgrade steps of which are as follows:

[0050] Step 1: The system creates an upgrade list. Each element in the upgrade list includes: virtual component number, virtual component version, and virtual component upgrade requirement.

[0051] The upgrade list reads all virtual components into the upgrade list by reading the information matrix.

[0052] Step 2: The system calculates the upgrade requirement of each virtual component according to the formula, sorts the virtual components to be upgraded in the upgrade list, and sorts them in descending order of upgrade requirement.

[0053] The upgrade requirement for virtual components is calculated using the following formula:

[0054] U d =α*U s (s) 2 +β*R(s) 2 +γ*SScore(s) 2

[0055] in,

[0056] U s (s) represents the average load of virtual component s, which can be obtained directly from the data stored in the database.

[0057] R(s) represents the upgrade reward of virtual component s, which needs to be calculated using a formula.

[0058] SScore(s) represents the security score of virtual component s, which needs to be calculated using a formula.

[0059] α represents the proportion of average load in the upgrade demand, which is determined based on the specific usage.

[0060] β represents the proportion of upgrade rewards in the upgrade demand, which is determined based on the specific usage.

[0061] γ represents the weight of the security score in the upgrade requirement, which is determined based on the specific usage.

[0062] The formula for calculating the virtual component security score SScore(s) of virtual component s is as follows:

[0063] SScore(s) = (1 - VR(s)) * IM(s)

[0064] Where VR(s) represents the severity of the security vulnerability in virtual component s, and IM(s) represents the security improvement effect of virtual component s after the vulnerability is fixed.

[0065] The formula for calculating the severity of security vulnerabilities in virtual components is as follows:

[0066]

[0067] Among them, v i (s) is a severity score for security vulnerabilities in virtual components, p i (s) is the probability that the vulnerability occurs on the component, and MaxRisk is the preset maximum risk value used to normalize the risk score.

[0068] The formula for calculating the security improvement effect of virtual component s after patching vulnerabilities is as follows:

[0069]

[0070] FixI(i) represents the security improvement impact value brought about by fixing the vulnerability, FixP(i) represents the probability that the known vulnerability will be fixed after the upgrade, InR(j) represents the impact of the new risk that the new version may introduce, RP(j) represents the actual probability of the risk introduced by the new version, and MaxImprovement represents the maximum possible security improvement value, which is used to normalize the security improvement score.

[0071] The formula for calculating the upgrade reward R(s) of virtual component s is as follows:

[0072]

[0073] Wherein, B(s) represents the benefit that virtual component s can bring after upgrading, which is calculated by the virtual component upgrade reward formula.

[0074] C(s) represents the cost required to upgrade the virtual component s, which is calculated using the formula for the cost of upgrading the virtual component.

[0075] F(s) represents the risk that may arise from upgrading the virtual component s, which is calculated using the formula for the risk of upgrading the virtual component.

[0076] SF represents the scaling factor determined based on the specific use case. For example, when calculating revenue, the more users there are, the greater the reward value will be. Therefore, the SF value should also be increased to reduce the final calculated reward value, making it easier to analyze later.

[0077] The formula for calculating the upgrade benefit B(s) of virtual component s is as follows:

[0078] B(s)=△U(s)*N(s)*P

[0079] in,

[0080] △U(s) represents the increase in user satisfaction brought about by the upgrade of virtual component s. Since there was no initial data before the upgrade, the upgrade satisfaction of all virtual components was set to 1 by default during the first virtual component upgrade. The satisfaction of subsequent upgrades was obtained through user surveys.

[0081] N(s) represents the number of users using the virtual component s.

[0082] P represents the probability of a successful virtual component upgrade. This probability is the average upgrade probability, calculated by averaging multiple upgrade results. Its initial value is 1 during the first upgrade.

[0083] The upgrade cost C(s) of virtual component s can be divided into two categories: resource cost and time cost.

[0084] The formula for calculating the resource cost RC(s) of virtual component upgrades is as follows:

[0085] RC(s)=Σ(r i *c i )

[0086] in,

[0087] r i This indicates the number of resource types i required for upgrading the virtual component.

[0088] c i This represents the cost of resource type i.

[0089] The formula for calculating the time cost TC(s) of virtual component upgrades is as follows:

[0090] TC(s)=(TC s *P)

[0091] in,

[0092] TC s This represents the system upgrade time cost for upgrading virtual components, derived from system timekeeping.

[0093] P represents the probability of a successful upgrade of a virtual component. This probability is the average upgrade probability, which is calculated by averaging the results of multiple upgrades. Its initial value is 1 by default during the first upgrade.

[0094] Taking into account the resource and time costs mentioned above, the formula for calculating the total cost of upgrading virtual component s is as follows:

[0095] C(s) = RC(s) + TC(s)

[0096] The upgrade risk F(s) of virtual component s can be divided into virtual component service interruption risk and virtual component data loss risk.

[0097] The formula for calculating the risk of virtual component service interruption (IR(s)) during virtual component upgrades is as follows:

[0098] IR(s)=P i *DT i +(1-P i )*DT u

[0099] in,

[0100] P i This indicates the probability that a virtual component service upgrade will cause a planned interruption. This probability is the average upgrade probability, which is calculated by averaging the results of multiple upgrades. Its initial value is 1 by default during the first upgrade.

[0101] DT i This represents the average time of planned downtime caused by virtual component service upgrades. This average time is calculated by averaging the results of multiple upgrades and is obtained through internal system timing.

[0102] DT u This represents the average time of unplanned interruptions caused by virtual component service upgrades. This probability is an average time calculated by averaging multiple upgrade results and obtained through internal system timing.

[0103] The formula for calculating the risk of data loss (DR(s)) of virtual component services during virtual component upgrades is as follows:

[0104] DR(s)=P d *DL

[0105] in,

[0106] P d This represents the probability of data loss due to virtual component upgrades. This probability is an average probability, calculated by averaging the results of multiple upgrades. Its initial value is 1 by default during the first upgrade.

[0107] DL represents the average amount of data lost due to virtual component upgrades, with an initial default value of 0.

[0108] Considering both the risks of virtual component interruption and virtual component data loss, the total risk arising from upgrading virtual component s is calculated using the following formula:

[0109] F(s) = IR(s) + DR(s)

[0110] Step 3: Locate the virtual component at the top of the upgrade list and note its unique identifier.

[0111] Step 4: The administrator uses a secure authentication protocol to transfer the new version of the software package, which includes the latest features and improvements, to the designated storage path via FTP (File Transfer Protocol). This ensures that the software package can be reliably distributed and applied to the corresponding virtual component instances under the control of the virtual component management system.

[0112] FTP is a standard protocol for file transfer over the Internet, allowing users to reliably and efficiently exchange and manage files between different computers over a network. FTP is based on a client-server architecture, operates at the application layer, and relies on the TCP / IP protocol to ensure reliable data transmission.

[0113] Step 5: Once the new version software package is ready, the system will construct an upgrade request instruction, which includes the unique identifier of the virtual component to be upgraded and the corresponding new version number parameter. This request, carrying detailed upgrade information, will then be sent to the virtual component management system for subsequent scheduling and execution.

[0114] Step 6: Upon receiving an upgrade request, the virtual component management system, acting as the core scheduling unit, generates a detailed instruction set for each specific virtual component upgrade requirement based on the received information. These instructions are then directed to the module specifically responsible for the virtual component upgrade process to ensure that the upgrade operation proceeds in an orderly manner according to the preset strategy.

[0115] Step 7: When the virtual component upgrade module receives the above instructions, it initiates the actual upgrade execution process. According to the instructions, the module first securely downloads the specified new version of the virtual component software package from the FTP server.

[0116] Step 8: After the download is complete, the upgrade module processes each virtual component instance sequentially according to the predetermined steps. The first step is to safely stop the currently running virtual component instance, then execute the installer for the new software package, and strictly reconfigure and initialize the components according to the new version configuration specifications to ensure that the new version components can operate smoothly and have full functionality.

[0117] Step 9: After successfully deploying the new version of the virtual component and undergoing a series of built-in stability and compatibility tests, if the new component exhibits the expected performance indicators and has no abnormal behavior, the virtual component upgrade module will officially record this upgrade operation as a success and send this confirmation result back to the virtual component management system.

[0118] Step 10: After the Virtual Component Manager receives the confirmation signal of successful upgrade, it will trigger the front-end notification mechanism to display a clear and unambiguous "Upgrade Complete" notification message to system users and related services. This means that the entire virtual component upgrade process involved in this invention has been successfully completed, and the updated virtual components are ready to provide enhanced service capabilities and feature support.

[0119] A visual virtual component intelligent upgrade method based on upgrade demand priority is proposed. In manual upgrade mode, the first three steps of the fully automatic mode are not required. The operator only needs to view the heat map, combine it with the actual usage situation, select the virtual component that needs to be upgraded, and note its number. The subsequent steps are the same as those in the fully automatic mode.

Claims

1. A method for intelligent upgrading of visualized virtual components based on upgrade requirement priority, characterized in that, After selecting the virtual components that need to be upgraded, the upgrade steps include: Step 1: Upload the software package containing the new version of the virtual components to the system backend server; Step 2: The system sends an upgrade request carrying the new virtual component version information to the virtual component manager; the upgrade request includes the new virtual component version number to which it will be upgraded. Step 3: Upon receiving the upgrade request, the virtual component manager generates an upgrade instruction and sends it to the virtual component upgrade module; Step 4: After receiving the upgrade instruction, the virtual component upgrade module executes the virtual component upgrade operation; Step 5: Download the specified new version of the virtual component package from the server, stop the currently running virtual component instance, and install and configure the new version of the virtual component; Step 6: When the new version of the virtual component is successfully deployed and running stably, the virtual component upgrade module confirms that the virtual component upgrade has been successfully completed and sends this result back to the virtual component manager. Step 7: After receiving confirmation of successful virtual component upgrade, the virtual component manager sends an upgrade completion notification to the system front-end, indicating that the entire virtual component upgrade process has been successfully completed.

2. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority as described in claim 1, characterized in that, The steps for selecting the virtual components that need to be upgraded include: S1, create an upgrade list and read all virtual components into the upgrade list by reading the information matrix; S2, the system sorts the virtual components to be upgraded in the upgrade list from high to low according to the calculated upgrade demand of each virtual component; S3, locate the virtual component at the top of the upgrade list and note its unique identifier.

3. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority as described in claim 2, characterized in that, Each element in the upgrade list includes: virtual component number, virtual component version, and virtual component upgrade requirement.

4. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority as described in claim 2, characterized in that, The upgrade requirement U of the virtual component d The calculation formula is: U d =α*U s (s) 2 +β*R(s) 2 +γ*SScore(s) 2 Among them, U s R(s) represents the average load of virtual component s, R(s) represents the upgrade reward of virtual component s, SScore(s) represents the security score of virtual component s; α is the proportion of average load in upgrade demand, β is the proportion of upgrade reward in upgrade demand, and γ is the proportion of security score in upgrade demand.

5. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority according to claim 4, characterized in that, The formula for calculating the upgrade reward R(s) of the virtual component s is as follows: Where B(s) represents the benefits that virtual component s can bring after upgrading; C(s) represents the cost required to upgrade virtual component s; F(s) represents the total risk brought about by upgrading virtual component s; and SF represents the scaling factor determined according to the specific use case.

6. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority as described in claim 5, characterized in that, The formula for calculating the benefit B(s) that the virtual component s can bring after upgrading is: B(s)=△U(s)*N(s)*P Where △U(s) represents the increase in user satisfaction brought about by the upgrade of virtual component s; N(s) represents the number of users using virtual component s; and P represents the probability of successful upgrade of virtual component s.

7. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority as described in claim 5, characterized in that, The formula for calculating the upgrade cost C(s) of the virtual component s is: C(s) = RC(s) + TC(s) RC(s) = Σ(r i *w i ) TC(s)=(TC s *P) Where RC(s) is the resource cost and TC(s) is the time cost; r i Indicates the quantity of resource type i required for the virtual component upgrade; c i TC represents the cost of resource type i; s P represents the system upgrade time cost of upgrading virtual components, and P represents the probability of a successful virtual component upgrade.

8. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority according to claim 5, characterized in that, The total risk F(s) resulting from the upgrade of the virtual component s is calculated using the following formula: F(s) = IR(s) + DR(s) IR(S)=P i *DT i +(1-P i )*DT u DR(s)=P d *DL Where IR(s) represents the risk of virtual component service interruption, and DR(s) represents the risk of virtual component service data loss; P i DT represents the probability of a planned outage caused by a virtual component service upgrade. i DT represents the average duration of planned outages caused by virtual component service upgrades. u P represents the average time of unplanned outages caused by virtual component service upgrades; d DL represents the probability of data loss due to virtual component upgrades, while DL represents the average amount of data loss due to virtual component upgrades.

9. The intelligent upgrade method for visualized virtual components based on upgrade requirement priority according to claim 1, characterized in that, The steps for selecting the virtual components that need to be upgraded include: viewing the heatmap and, in conjunction with the actual usage, selecting the virtual components that need to be upgraded and noting their numbers.

10. A computer storage medium storing a readable program, characterized in that, When the program runs, it can instruct the computing device to perform the intelligent upgrade method for visualized virtual components based on upgrade requirement priority as described in any one of claims 1-8.

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