Container cloud data sharing method with autonomous routing control

Abstract

The invention discloses a container cloud data sharing method with autonomous routing control, which comprises the following steps: acquiring user request data, performing identity authentication on a user, and acquiring an authentication result; based on the authentication result, the priority weight of the server is dynamically calculated, the optimal route is selected, and the request data is transmitted; and monitoring the transmission state of the request data, determining whether the request data is successfully transmitted, and completing data sharing. According to the method, the priority weight of the server can be dynamically calculated and the optimal route is selected, so that the data transmission time is remarkably shortened and the transmission efficiency is improved. The transmission process is monitored in real time, the routing strategy is adjusted in time, and the problem of data transmission interruption caused by uneven load of the server or poor network condition is effectively avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of cloud computing, and in particular relates to a container cloud data sharing method with autonomous routing control. Background Art

[0002] In the current cloud computing environment, container cloud, as a lightweight virtualization technology, is widely used in data sharing and service deployment. However, with the increase in the number of users and the sharp growth in data volume, how to efficiently and stably share data among multiple container cloud servers has become an urgent problem to be solved. Traditional data sharing methods often rely on fixed routing strategies and cannot dynamically adjust routing according to real-time information such as server status and network quality, resulting in low data transmission efficiency and serious waste of resources. In addition, when the server load is uneven or the network condition is poor, the data sharing process is easily affected, and even leads to service interruption. Summary of the invention

[0003] To solve the above technical problems, the present invention proposes a container cloud data sharing method with autonomous routing control. By real-time evaluation of the server's idle status, network quality, server resource utilization, and distance to the user, the server priority weight is dynamically calculated, and the optimal route is selected accordingly to achieve efficient and stable data sharing, thereby improving user experience and overall system performance.

[0004] To achieve the above object, the present invention provides a container cloud data sharing method with autonomous routing control, comprising:

[0005] Obtain user request data, authenticate the user, and obtain the authentication result;

[0006] Based on the authentication result, dynamically calculate the server priority weight and select the best route to transmit the request data;

[0007] The transmission status of the requested data is monitored to determine whether the requested data is successfully transmitted, thereby completing data sharing.

[0008] Optionally, based on the authentication result, dynamically calculating the server priority weight and selecting the best route includes:

[0009] Obtaining an impact factor, and performing normalization processing on the impact factor;

[0010] Calculate the server priority weight based on the processed impact factor;

[0011] Based on the priority weights, the best route is selected.

[0012] Optionally, the influencing factors include: server idleness, network delay, CPU usage, and distance from the user.

[0013] Optionally, the method for normalizing the impact factor is:

[0014]

[0015] Among them, Normalized_Factor is the normalized factor, Factor_Value is the actual value of the influencing factor, Factor_Min and Factor_Max are the minimum and maximum values ​​of the corresponding influencing factors respectively.

[0016] Optionally, the method for calculating the server priority weight is:

[0017]

[0018] Among them, Weight is the server priority weight, w1 corresponds to the weight of the server's idle state, w2 corresponds to the weight of the network delay, w3 corresponds to the weight of the CPU usage, w4 corresponds to the weight of the distance from the user, Idle_State is the server's idle state, Latency is the network delay, CPU_Usage is the CPU usage, and Distance is the distance from the user.

[0019] Optionally, determining whether the requested data is successfully transmitted includes:

[0020] If the requested data is successfully transmitted, data sharing is completed;

[0021] If the requested data transmission fails, the server priority and routing strategy are adjusted to reselect the optimal route.

[0022] Compared with the prior art, the present invention has the following advantages and technical effects:

[0023] The container cloud data sharing method with autonomous routing control provided by the present invention can significantly shorten the data transmission time and improve the transmission efficiency by dynamically calculating the server priority weight and selecting the best route. The transmission process is monitored in real time, and the routing strategy is adjusted in time to effectively avoid the problem of data transmission interruption caused by uneven server load or poor network conditions. Resources are dynamically allocated according to the real-time status of the server to avoid resource waste and improve the overall performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0025] Figure 1 It is a flow chart of a container cloud data sharing method with autonomous routing control according to an embodiment of the present invention;

[0026] Figure 2 The server priority calculation and routing selection flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0027] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0028] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0029] The present invention proposes a container cloud data sharing method with autonomous routing control, such as Figure 1 As shown, the specific steps include:

[0030] Obtain user request data, authenticate the user, and obtain the authentication result;

[0031] Based on the authentication results, the server priority weight is dynamically calculated and the best route is selected to transmit the request data;

[0032] Monitor the transmission status of the requested data, determine whether the requested data is transmitted successfully, and complete data sharing.

[0033] Specifically, the present invention proposes a container cloud data sharing method with autonomous routing control. It starts with a user initiating a data sharing request to the system, and the system is then initialized and prepared to process this request. First, the system strictly verifies the user's identity to ensure the legitimacy of the request source and prevents illegal requests from threatening the system security and data integrity. If the verification fails, the system will immediately notify the user and terminate the processing flow to ensure the security of the data. Subsequently, the system collects user location information to evaluate the network quality and the utilization of current server resources. This information provides a key basis for the system to select the optimal server and data transmission path in the future. After comprehensively considering multiple factors such as server idleness, distance between the user and the server, network quality, and CPU load, the system calculates the priority weight of each server and determines the server that best meets the current data transmission needs. Then, the system uses an autonomous routing algorithm to select the best data transmission path based on the server priority weight. Data is transmitted safely and efficiently through this path, and the system monitors the transmission status in real time to ensure that the integrity and security of the data are not compromised. Once the data transmission is completed, the system adjusts the weight distribution and path selection strategy according to whether the data is successfully received to continuously optimize the data transmission efficiency. In addition, the system also collects user feedback to further improve system performance and enhance user experience.

[0034] Specifically, the method for monitoring the transmission status of the requested data is as follows: First, the reliable transmission characteristics of the TCP protocol are used to monitor whether the data packet has successfully reached the other party through the confirmation response (ACK) mechanism. Secondly, the system will continue to monitor the status of the TCP connection during the transmission process, including connection establishment, data transmission, connection closure, and any possible exceptions (including timeouts and retransmissions). At the same time, the network status information provided by the IP layer (including network delay and packet loss rate) is used to evaluate the quality of data transmission. Finally, the status information of the TCP connection is combined with the data of the IP layer to comprehensively analyze the real-time status of the transmission to achieve comprehensive monitoring of the status of the requested data transmission.

[0035] Further, based on the authentication result, selecting the best route includes:

[0036] Obtain the impact factor and perform normalization on the impact factor;

[0037] Based on the processed impact factors, calculate the server priority weight;

[0038] Based on the priority weights, the best route is selected.

[0039] Specifically, Figure 2As shown, the influencing factors in the present invention refer to factors and conditions that affect the transmission efficiency during the data transmission process. Due to the diversity of influencing factors, it is necessary to normalize the influencing factors first to eliminate the influence of different dimensions, calculate the server priority weights based on the influencing factors, select the server that can provide the best data transmission performance as the target server, and determine the best data transmission path from the user to the server, that is, the best route. It can achieve fast and stable data transmission, while avoiding the inefficiency and waste of resources caused by traditional fixed routing strategies. The application of autonomous routing algorithms makes the data transmission process more flexible and efficient, further improving the user experience and overall system performance.

[0040] Furthermore, the influencing factors include: server idleness, network delay, CPU usage, and distance from the user.

[0041] Furthermore, the method for normalizing the impact factor is:

[0042]

[0043] Among them, Normalized_Factor is the normalized factor, Factor_Value is the actual value of the influencing factor, Factor_Min and Factor_Max are the minimum and maximum values ​​of the corresponding influencing factors respectively.

[0044] Furthermore, the method for calculating the server priority weight is:

[0045]

[0046] Among them, Weight is the server priority weight, w1 corresponds to the weight of the server's idle state (Idle_State), w2 corresponds to the weight of the network delay (Latency), w3 corresponds to the weight of the CPU usage (CPU_Usage), and w4 corresponds to the weight of the distance from the user (Distance). Idle_State is the server's idle state, Latency is the network delay, CPU_Usage is the CPU usage, and Distance is the distance from the user.

[0047] Further, determining whether the requested data is successfully transmitted includes:

[0048] If the requested data transmission is successful, proceed to the next step;

[0049] If the requested data transmission fails, the server priority and routing strategy are adjusted to reselect the best route.

[0050] Specifically, TCP uses the ACK mechanism to ensure the correct reception of data packets. After the sender sends data, the receiver will reply with an ACK packet to inform the sender that the data has been successfully received.

[0051] In order to ensure the integrity and security of the data transmission process, the present invention also implements a series of real-time monitoring and feedback mechanisms. During the data transmission process, the system monitors the transmission status in real time to determine whether the data is successfully transmitted. If the transmission fails or an abnormality occurs, the system will immediately start the corresponding recovery mechanism and adjust the weight distribution and path selection strategy to reselect the best route. At the same time, the system will also collect user feedback and data usage to further improve system performance and optimize routing strategies. In the container cloud data sharing method of the present invention, the routing strategy is formulated based on the server priority weight. The system will select the server with the highest priority as the target server for data transmission based on the calculated server priority weight, and use the autonomous routing algorithm to calculate the best transmission path from the source server to the target server. This routing strategy can ensure that the data can avoid congested links during transmission and select the best path for transmission, thereby improving the efficiency and reliability of data transmission. When an abnormal situation occurs during data transmission or the server status changes, the system will adjust the routing strategy in time and reselect the best route to ensure the continuity and stability of data transmission. In addition to the above technical measures, the present invention also focuses on improving the scalability and compatibility of the system. In the design process, the differences in the requirements of container cloud environments of different scales and types for data sharing methods are fully considered. Therefore, the technical solution proposed by the present invention can be flexibly applied to various container cloud environments to achieve efficient and stable data sharing. At the same time, with the continuous development and evolution of container cloud technology, the technical solution of the present invention can also be expanded and upgraded accordingly to adapt to new technical environments and requirements.

[0052] Example

[0053] First, Enterprise A conducted a comprehensive assessment of its existing container cloud environment to ensure that the present invention can be seamlessly integrated with its existing technical architecture. Subsequently, Enterprise A deployed the user authentication mechanism of the present invention to conduct strict security authentication for all users requesting data sharing, thereby ensuring the security of data transmission. Next, Enterprise A used the comprehensive evaluation method of the present invention to collect and analyze the resource utilization, network quality and idle state of each server in real time, and constructed a detailed weight table to more accurately evaluate the real-time status of the server. On this basis, Enterprise A adopted the autonomous routing algorithm of the present invention to dynamically calculate and select the best data transmission path according to the priority weight of the server, thereby achieving fast and stable data transmission. Finally, Enterprise A also implemented the real-time monitoring and feedback mechanism of the present invention to continuously monitor the data transmission process, and immediately start the recovery mechanism when an abnormality occurs, while continuously optimizing the system's performance and routing strategy based on user feedback and data usage. Through this series of steps, Enterprise A successfully applied the present invention to its actual container cloud environment, achieving efficient, stable and secure data sharing.

[0054] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A container cloud data sharing method with autonomous routing control, characterized in that: include: Obtain user request data, authenticate the user, and obtain the authentication result; Based on the authentication result, dynamically calculate the server priority weight and select the best route to transmit the request data; The transmission status of the requested data is monitored to determine whether the requested data is successfully transmitted, thereby completing data sharing.

2. A container cloud data sharing method with autonomous routing control according to claim 1, characterized in that: Based on the authentication result, dynamically calculating the server priority weight and selecting the best route includes: Obtaining an impact factor, and performing normalization processing on the impact factor; Calculate the server priority weight based on the processed impact factor; Based on the priority weights, the best route is selected.

3. A container cloud data sharing method with autonomous routing control according to claim 2, characterized in that: The influencing factors include: server idleness, network delay, CPU usage, and distance from the user.

4. A container cloud data sharing method with autonomous routing control according to claim 2, characterized in that: The method for normalizing the impact factor is: Among them, Normalized_Factor is the normalized factor, Factor_Value is the actual value of the influencing factor, Factor_Min and Factor_Max are the minimum and maximum values ​​of the corresponding influencing factors respectively.

5. A container cloud data sharing method with autonomous routing control according to claim 2, characterized in that: The method for calculating the server priority weight is: Among them, Weight is the server priority weight, w1 corresponds to the weight of the server's idle state, w2 corresponds to the weight of the network delay, w3 corresponds to the weight of the CPU usage, w4 corresponds to the weight of the distance from the user, Idle_State is the server's idle state, Latency is the network delay, CPU_Usage is the CPU usage, and Distance is the distance from the user.

6. A container cloud data sharing method with autonomous routing control according to claim 1, characterized in that: Determining whether the requested data is successfully transmitted includes: If the requested data is successfully transmitted, data sharing is completed; If the requested data transmission fails, the server priority and routing strategy are adjusted to reselect the optimal route.

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