Distributed Intellisense Controller

Abstract

The invention relates to an intelligent perception controller, which belongs to the technical field of big data processing, in particular to a distributed intelligent perception controller. Including: several groups of computing units with independent storage, at least 2 Ethernet data exchange modules, among which, the computing units are physically independent of each other, and the switching modules are divided into external network data exchange and internal network data exchange. Therefore, the present invention has the following advantages: (1) Simultaneously improve the data preprocessing capability of multiple computing units; (2) Support scalable functions, and a single computing unit can be compatible with system performance and capacity upgrades. With the improvement of the system's computing power and data volume, the hardware can replace high-performance computing modules and switching modules to meet the system's capabilities; (3) maintenance and after-sales are more convenient. When a single computing unit is damaged, it can be quickly replaced without the need for a complete system. machine replacement, shortening operation and maintenance time and costs.

Description

[0001] The invention relates to an intelligent perception controller, which belongs to the technical field of big data processing, in particular to a distributed intelligent perception controller. Background technique [0002] The monitoring of equipment and service status in the subway industry is related to the safety and stability of the entire subway operation, and has high requirements for high reliability, high availability and security of data. [0003] At present, there are the following problems in equipment and service status monitoring: [0004] (1) Deploying monitoring services on a single server is prone to equipment single point failure problems. [0005] (2) The monitoring service is deployed on multiple nodes and multiple servers, which greatly increases the cost and wastes resources. [0006] (3) The monitoring service is deployed in the business cluster, and the server resources are easily occupied by the main business, which leads to the performance degrada...

AI Technical Summary

Problems solved by technology

[0004] (1) A single server deploys monitoring services, which is prone to equipment single point failure problems

[0005] (2) Multi-node and multiple servers deploy monitoring services, which greatly increases the cost and wastes resources

[0006] (3) The monitoring service is deployed in the business cluster, and the server resources are easily occupied by the main business, which leads to the performance degradation of the monitoring system, and problems such as freezing or even crashing

[0007] (4) The types of failures of equipment and services require human judgment, and are not intelligently combined with operation and maintenance strategies, making operation and maintenance difficult and costly

Such an architecture cannot meet the particularity of high reliability and high availability in the rail transit industry

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