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Public evaluation

OGS_Network_Simulation_Run

The evaluation will focus on the performance of the optimized OGS network (data throughput, resilience, latency), the robustness and scalability of the Metaflow workflows, and the effective integration of Ax and Command R+ for decision support and optimization.

Evaluation type
task based
Challenge
AI-Driven Optimal Optical Ground Station Placement for LEO Constellations
Difficulty
Advanced
Rigor
Unspecified
Open linked challenge

Evaluation overview

How the linked challenge is judged: tasks, benchmarks, and criteria count.

Tasks
2
Benchmarks
0
Criteria
0

Task templates

Inputs and expected outputs.

Task 1

OGS_Network_Simulation_Run

Run the OGS network simulation for a given optimized configuration over a 72-hour period.

Input format

{'num_ogs': int, 'ogs_locations': [{'lat': float, 'lon': float, 'alt': float}], 'constellation_definition': dict}

Output format

{'total_data_gb': float, 'avg_latency_ms': float, 'link_availability_pct': float}

Task 2

Metaflow_Workflow_Execution_Check

Verify that the Metaflow pipeline runs successfully and integrates Ax for optimization.

Input format

N/A

Output format

{'workflow_status': 'success'|'failure', 'optimization_iterations': int, 'best_config_found': dict}