How to solve the problem of network congestion during video surveillance?

Network congestion during video surveillance can severely impact the performance of security systems, resulting in video loss, pixelation, and delayed feeds. This issue often arises due to the high bandwidth requirements of surveillance cameras, especially when transmitting high-definition video streams over shared networks. Here are several strategies to address and prevent network congestion in video surveillance systems.

1. Segment the Surveillance Network (VLANs)

Problem: Shared networks can become congested when surveillance video streams compete with regular network traffic.

Solution: Use Virtual LANs (VLANs) to segregate surveillance traffic from other data, ensuring that video streams do not interfere with critical business applications.

Implementation:

--- Set up a dedicated VLAN for all IP cameras and the video management system (VMS).

--- Assign high-priority Quality of Service (QoS) to this VLAN to ensure video traffic is prioritized over other data types.

Example configuration:

2. Implement Quality of Service (QoS)

Problem: Without prioritization, critical video traffic may experience delays due to other network activities such as file transfers or voice over IP (VoIP).

Solution: Implement QoS to prioritize video surveillance traffic over non-essential traffic, reducing delays and preventing congestion.

Implementation:

--- Use network devices (switches and routers) that support QoS policies to prioritize surveillance video traffic based on port, IP range, or protocol.

--- Classify video streams as high priority while deprioritizing less critical traffic (e.g., file transfers or web browsing).

Example Cisco QoS policy:

3. Use Network Video Recorders (NVRs) with Local Storage

Problem: Continuous streaming from multiple cameras to a centralized server can overload the network.

Solution: Use Network Video Recorders (NVRs) with local storage, reducing the need to send high-bandwidth streams constantly across the network.

Implementation:

--- Install NVRs at strategic locations to store video data locally and only transmit low-bandwidth metadata or footage when needed.

--- Centralize video monitoring while distributing storage across the network.

4. Implement Multicast Streaming

Problem: Unicast streaming, where each camera sends an individual stream to each viewing station, consumes excessive bandwidth when multiple devices view the same feed.

Solution: Use multicast streaming, which allows a single stream to be sent to multiple viewers without duplicating traffic for each recipient.

Implementation:

--- Configure multicast on switches and routers and enable it on IP cameras and the VMS.

--- Implement the Internet Group Management Protocol (IGMP) to manage the multicast group.

Example multicast command:

5. Optimize Camera Resolution and Frame Rate

Problem: High-resolution and high-frame-rate video streams consume significant bandwidth, leading to congestion, especially in large-scale deployments.

Solution: Adjust the camera settings to lower resolution and frame rate where full HD is not necessary.

Implementation:

--- Assess the environment and reduce resolution for areas that don’t require high-definition video.

--- Set cameras in low-traffic areas to lower frame rates (e.g., 15 FPS instead of 30 FPS) to decrease bandwidth usage without compromising video quality.

Example camera settings:

--- Resolution: 1080p to 720p for non-critical areas.

--- Frame Rate: Adjust from 30 FPS to 15 FPS where applicable.

6. Use Video Compression (H.265 or H.264+)

Problem: Raw or uncompressed video streams require large amounts of bandwidth.

Solution: Use modern video compression standards like H.265 (HEVC) or H.264+, which significantly reduce the bandwidth requirements while maintaining video quality.

Implementation:

--- Ensure that your cameras and NVRs support H.265 or H.264+, and switch to these codecs to reduce video size and bandwidth usage by 30-50%.

--- Configure video management systems to use the most efficient codecs.

7. Implement Edge Computing and Video Analytics

Problem: Streaming all video footage to a central server can cause unnecessary bandwidth usage, especially when most of the footage is not needed.

Solution: Use edge computing with cameras that have built-in video analytics, which analyze the footage locally and only transmit relevant video or alerts to the central system.

Implementation:

--- Deploy smart cameras with edge processing capabilities that analyze footage and transmit only important data or events (e.g., motion detection).

--- This reduces the amount of unnecessary data being transmitted across the network, freeing up bandwidth for critical traffic.

8. Set Up Redundant Links or Aggregated Links (LACP)

Problem: A single network link may not provide sufficient bandwidth for high-definition video streaming from multiple cameras.

Solution: Implement Link Aggregation Control Protocol (LACP) to combine multiple network interfaces into a single logical link, increasing bandwidth.

Implementation:

--- Use LACP to create aggregated links on switches and routers, effectively increasing the bandwidth available for video streams.

Example LACP configuration:

9. Deploy Dedicated Surveillance Switches

Problem: Sharing network resources with other services can lead to competition for bandwidth and eventual congestion.

Solution: Use dedicated switches for the surveillance network, ensuring that surveillance data does not compete with regular data traffic.

Implementation:

--- Install managed switches that handle only surveillance traffic.

--- These switches can be optimized specifically for video traffic, with features like QoS and IGMP snooping enabled by default.

10. Use Adaptive Bitrate Streaming

Problem: Fixed bitrate streams can overwhelm the network if conditions degrade or if the network is under heavy load.

Solution: Use adaptive bitrate streaming that adjusts video quality dynamically based on available network bandwidth.

Implementation:

--- Many VMS platforms and cameras support adaptive bitrate streaming, which lowers video quality when congestion is detected and raises it when bandwidth allows.

--- This feature can help maintain network stability without sacrificing too much video quality.

11. Monitor and Optimize Network Utilization

Problem: Without proper monitoring, network congestion may go undetected until it disrupts surveillance operations.

Solution: Use network monitoring tools like SolarWinds, PRTG, or Zabbix to continuously track bandwidth usage, identify congestion points, and optimize network performance.

Implementation:

--- Set up alerts for high network utilization or packet loss and adjust QoS policies or bandwidth allocation accordingly.

Conclusion

Solving network congestion during video surveillance requires a combination of strategic network design, equipment upgrades, and configuration optimization. Segregating surveillance traffic with VLANs, implementing QoS, using multicast streaming, and optimizing camera settings are critical steps in preventing congestion. Additionally, leveraging modern technologies like H.265 compression, edge computing, and adaptive bitrate streaming can help maintain network performance while supporting high-definition video streams. By carefully planning and monitoring your network, you can ensure efficient and reliable surveillance system operation.