Networking
The network architecture will provide reliable, high-performance connectivity between cameras, compute units, and integration endpoints while maintaining security and quality of service standards. This infrastructure will ensure consistent data flow and system responsiveness across all competition environments.
We propose a network architecture optimized for routing high-bandwidth GigE Vision camera data (industrial camera network protocol) to edge computing nodes while maintaining the low-latency characteristics essential for real-time judging applications.
Core Infrastructure Design
The proposed network will implement a hierarchical topology (layered network design) designed specifically for machine vision applications. At the network core, high-capacity switches will provide the backbone for routing camera data streams to distributed edge computing nodes. This design will minimize the distance between cameras and their assigned processing systems, reducing latency and improving overall system responsiveness.
Distribution switches at strategic locations will aggregate multiple camera connections, creating efficient data collection points that simplify cabling and reduce infrastructure complexity. The entire system will operate as an isolated competition network, ensuring predictable performance and eliminating external network dependencies during events.
GigE Vision Data Routing Strategy
The network routing strategy will ensure efficient data flow from capture devices to processing systems while maintaining performance guarantees.
Camera-to-Edge Computer Mapping will prioritize efficient routing of GigE Vision streams from cameras to assigned edge computing nodes through optimized network paths. Each camera will connect to the nearest distribution switch, which will route video streams to appropriate edge computers based on pre-configured assignments.
Minimized Network Hops (data transfer steps) will reduce latency and eliminate potential bandwidth bottlenecks that could impact real-time processing requirements.
Bandwidth Management will accommodate the substantial data volumes generated by GigE Vision cameras, which typically produce 50-100 Mbps (megabits per second) per camera at 1080p60 resolution. Large venue deployments could reach aggregate bandwidth demands of several gigabits per second during peak operation.
10 Gigabit Ethernet Backbone will provide sufficient capacity for peak load scenarios while maintaining the low-latency characteristics essential for real-time judging applications.
Edge Computing Integration
Edge computing nodes will be strategically positioned throughout the venue to minimize the distance between cameras and processing systems. This distributed approach will reduce network load on the backbone infrastructure and improve system responsiveness. Each edge computer will handle processing for a cluster of nearby cameras, with the network facilitating both the inbound video streams and outbound processing results.
The network will also support coordination traffic between edge nodes, enabling the system to maintain consistency across multiple processing nodes and provide seamless handoffs when athletes move between coverage areas.
Power and Infrastructure Considerations
Efficient power distribution and infrastructure management will reduce deployment complexity while ensuring reliable operation throughout competition events. Integrated power solutions will minimize cable runs and simplify field setup procedures.
Power over Ethernet Integration
Power over Ethernet technology (PoE - single cable for data and power) will simplify camera deployment by delivering both data connectivity and electrical power through a single cable. This approach will eliminate the need for separate power infrastructure at each camera location, significantly reducing installation complexity and improving system reliability.
The proposed network switches will incorporate PoE+ capabilities (enhanced Power over Ethernet) to support the power requirements of machine vision cameras, while higher-power PoE++ ports could accommodate edge computing devices that require additional power for processing operations. Power budget planning will ensure that all critical system components receive adequate power allocation even during peak demand scenarios.
Network Performance and Reliability
Network performance and reliability standards will ensure consistent data flow and system responsiveness throughout competition events. Advanced quality of service mechanisms (traffic prioritization) will prioritize critical traffic while maintaining overall network stability.
Quality of Service Framework
The network will implement quality of service mechanisms (QoS - traffic priority management) to ensure that time-sensitive video data receives priority treatment throughout the infrastructure. GigE Vision streams will be marked for expedited forwarding, guaranteeing minimal latency and jitter (timing variations) even during periods of high network use.
Traffic prioritization will ensure that camera data streams maintain consistent performance characteristics, while lower-priority traffic such as system monitoring and administrative functions will be managed to prevent interference with critical judging operations.
Security and Access Control
The proposed network will implement comprehensive security measures appropriate for a competition environment. Access control mechanisms will prevent unauthorized device connections, while physical security measures will protect network infrastructure components.
Network isolation will ensure that the judging system operates independently of external networks, reducing potential security vulnerabilities and eliminating dependencies on venue networking infrastructure that might be shared with other systems or public access.
Deployment and Management Considerations
Deployment and management strategies will prioritize operational efficiency and system reliability while minimizing the technical complexity of field operations. These considerations will ensure consistent performance across diverse venue environments.
System Monitoring and Maintenance
The network infrastructure will include comprehensive monitoring capabilities to ensure optimal performance throughout competition events. Network health monitoring will track key performance indicators including bandwidth use, latency measurements, and error rates.
Remote management capabilities will enable system administrators to monitor and configure network components without requiring physical access to equipment, supporting efficient operation during competition events when access to infrastructure areas may be limited.
Scalability and Flexibility
The proposed network architecture will accommodate varying venue sizes and camera deployment patterns. Modular design principles will allow the system to scale from smaller venue installations with fewer cameras to large-scale deployments supporting extensive camera coverage areas.
Flexible routing capabilities will enable dynamic reconfiguration of camera-to-processor assignments, supporting different competition formats or venue layouts without requiring significant infrastructure changes. This adaptability will be particularly valuable for HYROX's diverse global venue portfolio, where network requirements may vary significantly between locations.