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With the advancement of technology and the increase in corporate surveillance needs, the scale of video surveillance systems continues to expand, and accessing a large number of devices has become a normalized challenge. To meet this challenge, the video convergence system LntonCVS video fusion platform, with its excellent high-concurrency processing capabilities, provides reliable load balancing service guarantees for enterprise video surveillance management systems.

The load balancing of the LntonCVS video fusion platform is different from the traditional random polling or CPU architecture-based design. Instead, it calculates the load based on multi-dimensional pressures such as traffic. It takes into account the differences in protocols and device capabilities, and loads the same devices and protocols to the nodes that have started the corresponding access protocols to ensure the optimal use of resources. If the optimal node cannot be found, the system will schedule the optimal idle node to start the access service to ensure the optimal use of resources.

In addition to automatic load balancing, manual load balancing is also very important. Administrators can redistribute device access pressure as needed to respond to changes in business needs or network conditions. Manual load balancing allows administrators to flexibly control access service allocation to ensure service reliability and performance.

Advantage

1. Integrated comprehensive management capabilities: LntonCVS video fusion platform realizes the collection, aggregation, encoding, management, storage and distribution of video data through efficient video capabilities, and supports functions such as connection, storage, management, control and intelligence. This helps to standardize the management of social video resources and improve the management capabilities of monitoring system construction for key units and key areas.

2. Strong video access compatibility: The platform supports access to video streams and devices of different brands, models, and types, including RTSP, RTMP, GB28181, ONVIF, etc., to solve technical compatibility issues and realize national standard conversion of heterogeneous video formats and signaling formats, thereby achieving data interconnection and sharing docking.

3. AI analysis and alarm reporting: The platform can receive special event alarms from front-end devices, including video signal loss, offline, lens occlusion, and dynamic detection alarms. Administrators can capture videos based on device alarm information and obtain video screenshots at the alarm moment to improve security monitoring effects.

4. High concurrent processing capability:

- Distributed architecture: The distributed architecture is used to divide the system into multiple independent modules, each module processes part of the data, effectively improving the concurrent processing capability of the system.

- Load Balancing: The built-in load balancing mechanism automatically distributes requests to multiple servers to avoid overloading a single server and make full use of system resources.

- Efficient data processing: Supports multiple video encoding formats and resolutions to ensure good video quality and processing effects in various scenarios.

5. Continuous and reliable service guarantee: The platform has real-time monitoring and alarm functions, which can monitor the system operation status and performance indicators, and issue an alarm notification immediately once an abnormal situation is found. Provide a complete after-sales service system, including technical support, training, maintenance and upgrades, to ensure that the system is always in the best condition.

With its powerful high-concurrency processing capabilities and reliable service guarantees, the LntonCVS video fusion platform has become an ideal choice for enterprises to cope with the challenge of connecting a large number of devices to the video surveillance system. In the future, as technology develops and the market expands, the platform will continue to provide more outstanding performance and services, and promote the development of the visual monitoring cloud platform.