SatCom-TELMA/MA-DRL_Routing_Simulator
Multi-Agent Deep Reinforcement Learning (MA-DRL) Routing Simulator for satellite networks
This project helps satellite network operators or researchers simulate data transmissions through satellite constellations like Starlink, OneWeb, or Iridium_NEXT. You provide information about the satellite constellation, desired gateways (e.g., Malaga to Los Angeles), and routing methods (like shortest path or Q-Learning). It then generates detailed latency results and link rate data, which helps evaluate network performance and optimize routing strategies. This is ideal for those planning or analyzing the efficiency of satellite-based communication systems.
133 stars. No commits in the last 6 months.
Use this if you need to simulate data flow and assess latency and link efficiency within various satellite network configurations, especially when exploring different routing algorithms like Q-Learning.
Not ideal if you need a real-time network monitoring tool or an operational system for live satellite data management, as this is a simulation environment for planning and analysis.
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Last pushed
May 01, 2025
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