In the railway industry, high-definition surveillance systems bring not only clearer images and improved monitoring results, but also significantly higher demands on system performance, long-distance transmission bandwidth, and storage capacity. The question arises: what kind of high-definition system can effectively support the multi-level access, long-distance transmission, and large-scale monitoring characteristics of the railway sector?
Traditionally, the video surveillance architecture in railways centers around a streaming media server, commonly used in station-level monitoring systems. Front-end encoders or IP cameras (IPC) send unicast streams over the network to distribution and storage servers, which then convert these into multicast for on-demand delivery and storage. While this setup works well for standard definition (SD) systems, it faces serious limitations when applied to high-definition (HD) solutions.
Firstly, the number of servers required increases proportionally with the number of monitoring points. HD IPCs typically output 6–8 Mbps streams, three to four times that of SD, leading to a massive increase in the number of servers needed. This creates performance bottlenecks and requires frequent hardware upgrades, increasing costs and complexity.
Secondly, the system has multiple local failure points. If a distribution/storage server fails, it affects all the video channels it manages, compromising reliability—something critical in the transportation sector. Although redundancy could help, it's rarely implemented due to cost concerns.
Thirdly, front-end IPCs output unicast streams, causing both real-time and storage streams to share the same bandwidth. This puts immense pressure on disk arrays and drives up costs. To reduce storage costs, compression ratios are increased, which severely degrades image quality.
Lastly, the large number of servers and their racks occupy significant space, violate green environmental standards, and increase system unreliability by creating more failure points. During emergencies or traffic surges, the entire server farm may become overwhelmed.
To address these challenges, a more advanced solution is needed. It leverages the mature softswitch architecture from the telecom industry—NGN (Next Generation Network). In this model, the management server handles device control, signaling, and session setup but does not process real-time video streams. Both storage and real-time streams are directly transmitted to the disk array, decoder, or client through the network, bypassing the server bottleneck.
When multiple users access the same real-time video stream, the system supports multicast, as shown in Figure 2. The front-end IPC sends a multicast stream, allowing network switches to replicate the stream efficiently, reducing bandwidth usage and improving scalability. This approach is especially beneficial for HD systems, offering better performance and cost efficiency.
Key advantages include:
1. No direct correlation between the number of monitoring points and server count. A single video management server can handle thousands of channels.
2. High reliability: failure of the management server doesn’t interrupt real-time monitoring or storage.
3. Dual-stream output from the front-end allows independent configuration of storage and real-time streams, optimizing clarity and reducing storage costs.
4. Efficient handling of large-scale traffic bursts via multicast, ensuring reliable operation during emergencies.
While this solution works well within stations, it must also support remote access by higher-level dispatch centers. Traditional streaming media architectures naturally support multi-tier monitoring, but the NGN-based approach faces challenges in wide-area networks (WAN) with limited bandwidth.
To overcome this, a media forwarding server can be added at the station level, as shown in Figure 4. The station platform must support both unicast and multicast modes, automatically switching based on access needs. This ensures compatibility with future HD deployments and maintains system efficiency and reliability.
As high-definition monitoring becomes more widespread in the railway industry, adapting existing systems to meet new demands will be crucial. It’s time for the industry to rethink its infrastructure and embrace smarter, more scalable solutions.
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