Dynamic Satellite Capacity Orchestration with Network Controller

Network Capacity Controller leverages AI and machine learning to efficiently manage fleet-wide satellite capacity, ensuring optimal performance and quality of experience (QoE) by reallocating resources as needed. Satellite capacity allocated to ships, aircraft, or remote sites is typically fixed, leading to inefficiencies when demand fluctuates across the fleet.

Traditional methods rely on complex modeling and forecasting to prevent underutilization and congestion, but predicting optimal usage becomes challenging with variables like geography, weather, passenger numbers, and application requirements. Network Capacity Controller addresses these challenges by dynamically reallocating satellite capacity in near real-time without manual intervention.

For instance, during adverse weather conditions impacting Ship A's internet connectivity, the Controller can automatically shift capacity from Ship B to ensure uninterrupted service. It intelligently prioritizes bandwidth types that perform better in specific conditions, such as C-Band in rainy weather. Similarly, when one vessel requires additional capacity for a live-streamed event, the system can redistribute idle capacity from another vessel to meet the demand.

Neuron's founder and CEO, Benny Retnamony, highlights the significance of Network Capacity Controller in efficiently managing connectivity resources across a fleet of moving assets. By eliminating the need for individual endpoint-based decisions, the system ensures precise capacity management to meet demand dynamically.

Network Capacity Controller is powered by Neuron Grid, an AI-driven network management system that seamlessly blends connectivity from various providers, orbits, and networks. The intelligent decision engine of Grid orchestrates traffic every 50 milliseconds, optimizing bandwidth usage for the highest QoE across ships, planes, or remote sites.

Grid's continuous analysis of traffic patterns enables proactive management of capacity allocation. When imbalances are detected between endpoints, the Controller directs resources to vessels with the highest demand, ensuring efficient utilization of satellite throughput. Moreover, the system can manage consumption pools like LEO, MEO, or GEO, providing customers with optimized QoE and cost management.

Prateek Dahale, director of engineering at Neuron, emphasizes the system's ability to make data-driven decisions in real-time, ensuring optimal orchestration of capacity pools and network optimization. Network Capacity Controller's adaptive algorithm continually learns and evolves, guaranteeing smarter decisions and improved results over time.

For more information, visit www.getneuron.com.