Building information model collaborative clustering method based on load balancing

Abstract

The invention provides a building information model collaborative clustering method based on load balancing, and relates to the technical field of building information model design, the score of each Revit Server server is calculated through a load balancer according to the performance index of each Revit Server server, a user sends a request to the load balancer through a Revit client, and the Revit client sends the request to the load balancer. When the load balancer receives the request, the request is endowed with the IP address of the Revit Server server with the highest score, and the Revit client is connected with the Revit Server server with the highest score through the IP address, so that the connection between the Revit client and the Revit Server server is completed, the situation that too many users are connected with the same Revit Server server at the same time is avoided, and the user experience is improved. The method solves the problem that the design is affected by server overload possibly caused by the adoption of modeling software Revit in existing building information model design, and is suitable for building information model design.

Description

Technical Field

[0001] The present invention relates to the technical field of building information model design, and particularly to a building information model collaborative cluster method based on load balancing. Background Art

[0002] In the fields of architecture and engineering, Building Information Modeling (BIM) technology has become an important tool for improving design, construction, and operation efficiency. As the complexity and scale of projects continue to increase, the application scope of BIM is also expanding continuously. Especially in the 3D design collaborative work of large enterprises, BIM technology plays a crucial role. However, traditional BIM collaborative work models usually rely on a single or a small number of servers. This architecture often struggles to handle high-concurrency requests and data processing requirements when faced with simultaneous access by a large number of users and complex design tasks. Server overload not only leads to a decrease in system response speed but may also cause data conflicts and inconsistencies, seriously affecting the progress and quality of projects.

[0003] Revit, as a Building Information Modeling (BIM) modeling software widely used in architectural design, is widely applied to work such as design, construction, and management in the construction industry. The Revit Server allows multiple designers to collaborate and edit the same Revit model simultaneously, that is, the Building Information Model (BIM).

[0004] Existing Revit relies on a single Revit Server to process all user requests and collaborative work. Users edit the Revit model through this single server. Users need to fill in the IP address of the Revit Server in the Revit client. The Revit client accesses through the IP of the Revit Server and then conducts data sharing and real-time collaboration. The advantage of this solution is simple deployment, but when multiple people work simultaneously, the load on the server increases rapidly, resulting in performance degradation.

[0005] Revit Server is not designed as a cluster architecture. A single server undertakes all collaborative work tasks and there is no cluster management mechanism to dynamically adjust the load and task allocation. Even though Revit Server allows multiple users to access simultaneously, if collaborative tasks are too concentrated on a single server, it will lead to overload and cannot effectively guarantee system performance and stability. Summary of the Invention

[0006] The technical problem solved by the present invention: The present invention provides a building information model collaborative cluster method based on load balancing to solve the problem that the existing building information model design using the modeling software Revit may cause server overload and affect the design.

[0007] The technical solution adopted by the present invention to solve the above technical problems: A building information model collaborative cluster method based on load balancing, which is applied to a building information model collaborative cluster system. The building information model collaborative cluster system deploys multiple Revit Server servers, a load balancer, and multiple Revit clients. The method includes the following steps:

[0008] S1. The load balancer calculates the score of each Revit Server server based on the performance metrics of each Revit Server server;

[0009] S2. The user sends a request to the load balancer through the Revit client;

[0010] S3. When the load balancer receives the request, it sends the IP address of the Revit Server server with the highest score to the Revit client;

[0011] S4. The Revit client receives the IP address and connects to the Revit Server server with the highest score through the IP address.

[0012] Further, the formula for calculating the score of each Revit Server server based on the real-time performance metrics of each Revit Server server is: P = AK1 + BK2 + CK3, where P represents the score of the Revit Server server, K1 represents the CPU score of the Revit Server server, A represents the weight of the CPU score, K2 represents the memory score of the Revit Server server, B represents the weight of the memory score, K3 represents the hard disk score of the Revit Server server, and C represents the weight of the hard disk score.

[0013] Further, the calculation formula for the CPU score of the Revit Server server is: K1 = A1k 11 +A2k 12 , where k 11 represents the CPU core number score, S represents the CPU core number, S MAX represents the maximum CPU core number of all Revit Server servers, and A1 represents the weight of the CPU core number score.

[0014] Further, the calculation formula for the memory score of the Revit Server server is: K2 = 1 - k 21 , where k 21 represents the memory usage rate.

[0015] Further, the calculation formula for the hard disk score of the Revit Server is: K3 = 1 - k 31 , where k 31 represents the hard disk utilization rate.

[0016] Further, in S1, the load balancer calculates the score of each Revit Server at regular intervals.

[0017] Beneficial effects of the present invention: The present invention provides a building information model collaborative cluster method based on load balancing. The load balancer calculates the score of each Revit Server according to the performance indicators of each Revit Server. When a user sends a request to the load balancer through the Revit client, when the load balancer receives the request, it assigns the IP address of the Revit Server with the highest score to the request. The Revit client connects to the Revit Server with the highest score through the IP address, thereby completing the connection between the Revit client and the Revit Server, avoiding excessive users connecting to the same Revit Server at the same time, and solving the problem that the existing building information model design using the modeling software Revit may cause server overload and affect the design. Description of the Drawings

[0018] Figure 1 is a schematic flowchart of a building information model collaborative cluster method based on load balancing provided by the present invention. Detailed Embodiments

[0019] Aiming at the problem that the existing building information model design using the modeling software Revit may cause server overload and affect the design, the present invention provides a building information model collaborative cluster method based on load balancing, which is applied to a building information model collaborative cluster system. The building information model collaborative cluster system deploys multiple Revit Servers, a load balancer, and multiple Revit clients. The method is as follows Figure 1 shown, including the following steps:

[0020] S1. The load balancer calculates the score of each Revit Server according to the performance indicators of each Revit Server.

[0021] Specifically, the formula for calculating the score of each Revit Server based on its real-time performance metrics is: P = AK1 + BK2 + CK3, where P represents the score of the Revit Server, K1 represents the CPU score of the Revit Server, A represents the weight of the CPU score, K2 represents the memory score of the Revit Server, B represents the weight of the memory score, K3 represents the hard disk score of the Revit Server, and C represents the weight of the hard disk score. In one embodiment, A is 0.4, B is 0.3, and C is 0.3.

[0022] The formula for calculating the CPU score of the Revit Server is: K1 = A1k 11 + A2k 12 where k 11 represents the CPU core count score, S represents the number of CPU cores, S MAX represents the maximum number of CPU cores of all Revit Servers, and A1 represents the weight of the CPU core count score. The formula for calculating the memory score of the Revit Server is: K2 = 1 - k 21 where k 21 represents the memory usage rate. The formula for calculating the hard disk score of the Revit Server is: K3 = 1 - k 31 where k 31 represents the hard disk usage rate.

[0023] To reduce the burden on the load balancer, the load balancer calculates the score of each Revit Server at regular intervals, for example, once every five minutes.

[0024] S2. The user sends a request to the load balancer through the Revit client.

[0025] S3. When the load balancer receives the request, it sends the IP address of the Revit Server with the highest score to the Revit client.

[0026] Specifically, for the Revit client, it always obtains the IP address of the Revit Server with the highest score during the current time period, that is, the Revit Server with the optimal performance, ensuring that the Revit client used by the user connects to the Revit Server with the optimal performance.

[0027] S4. The Revit client receives the IP address and connects to the Revit Server with the highest score through the IP address.

[0028] Specifically, through secondary development of the Revit API in the Revit client, the IP address of the Revit Server with the highest score is set in the access of the Revit client to the Revit Server.

Claims

1. A building information model collaborative cluster method based on load balancing, characterized in that, Applied to a building information model collaborative cluster system, where multiple Revit Server servers, a load balancer, and multiple Revit clients are deployed in the building information model collaborative cluster system. The method includes the following steps: S1. The load balancer calculates the score of each Revit Server server based on the performance metrics of each Revit Server server; S2. The user sends a request to the load balancer through the Revit client; S3. When the load balancer receives the request, it sends the IP address of the Revit Server server with the highest score to the Revit client; S4. The Revit client receives the IP address and connects to the Revit Server server with the highest score through the IP address.

2. The method for collaborative clustering of building information models based on load balancing according to claim 1, wherein, The formula used to calculate the score of each Revit Server server based on the real-time performance metrics of each Revit Server server is: P = AK1 + BK2 + CK3, where P represents the score of the Revit Server server, K1 represents the CPU score of the Revit Server server, A represents the weight of the CPU score, K2 represents the memory score of the Revit Server server, B represents the weight of the memory score, K3 represents the hard disk score of the Revit Server server, and C represents the weight of the hard disk score.

3. The method for collaborative clustering of building information models based on load balancing according to claim 2, wherein, The calculation formula for the CPU score of the Revit Server is: K1 = A1k 11 + A2k 12 , where k 11 represents the CPU core count score, S represents the CPU core count, and S MAX represents the maximum CPU core count of all Revit Server servers, and A1 represents the weight of the CPU core count score.

4. The method for collaborative clustering of building information models based on load balancing according to claim 2, wherein The calculation formula for the memory score of the RevitServer server is: K2 = 1 - k 21 , where k 21 represents the memory usage rate.

5. The method for collaborative clustering of building information models based on load balancing according to claim 2, wherein The calculation formula for the hard disk score of the RevitServer server is: K3 = 1 - k 31 , where k 31 represents the hard disk usage rate.

6. The method for collaborative clustering of building information models based on load balancing according to any one of claims 1-5, characterized in that, In S1, the load balancer calculates the score of each Revit Server server at regular intervals.

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