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I will implement ns3 network with a python rl agent via ns3gym
Dagmawit Tenaye
Level 1
About this gig
I am an expert in NS3-Gym integration and reinforcement learning for network simulation. Using the official NS3-Gym framework, I design and implement custom RL agents (DQN, PPO, TGN) to optimize 5G, IoT, VANET, and SDN networks.
My services help you reduce congestion, improve routing efficiency, optimize dynamic resource allocation, and achieve high-performance network simulations for research papers, theses, or industrial projects. All solutions include fully commented source code, reproducible results, and detailed performance analysis.
Packages:
- Proof-of-Concept: Full NS3-Gym setup with a working baseline RL agent.
- Custom Agent Implementation: Advanced Python RL agent to optimize network metrics for throughput, delay, jitter, PDR, and QoS.
- Advanced Solutions: Multi-objective optimization, complex NS-3 module integration, AI-based network control, and publication-ready performance analysis.
Get to know Dagmawit Tenaye
Dagmawit Tenaye
Expert NS3 and 5G Network Simulation IoT VANET and AI Integration
Level 1
- FromEthiopia
- Member sinceJun 2022
- Last delivery2 months
Languages
English, Amharic
I am a Network Simulation and NS3 expert with extensive experience designing implementing and analyzing 5G IoT VANET SDN and AI integrated network simulations. I deliver custom simulations for research and industry with performance analysis including throughput delay jitter PDR and QoS. I integrate AI and ML models and provide detailed source code graphs and reproducible reports. I help researchers and professionals achieve accurate reliable results and research ready simulations.
My Portfolio
FAQ
Which NS3 versions do you support for the NS3-Gym integration?
I primarily work with NS3 version 3.30 or newer, as these are most compatible with the latest NS3-Gym releases. Please specify your exact NS3 version before ordering.
Can you help me choose the right RL algorithm (e.g., DQN, PPO)?
Absolutely. The best algorithm depends on your network optimization goal. I can implement and compare DQN (Deep Q-Networks) for discrete actions or PPO (Proximal Policy Optimization) for complex, continuous control tasks.
What kind of NS3 components can the RL agent control?
My RL agent can control any element exposed through the Gym interface, including congestion control parameters, routing decisions, power management, and scheduler settings for precise network optimization
