ncsim: A Lightweight Simulator for Networked Edge Computing with Wireless Interference Modeling
For researchers evaluating DAG task schedulers in wireless edge computing, this work provides a tool to avoid misleading conclusions from interference-free models.
Existing simulators for edge computing fail to model wireless interference, causing rank inversions where the best scheduler under interference-free models becomes the worst under realistic conditions. ncsim bridges this gap, revealing rank inversions in 27.8% of scenarios and up to 2.7x worse makespan for interference-free-optimal schedulers.
Evaluating DAG task schedulers for wireless edge computing requires jointly modeling compute placement and wireless interference, yet existing tools treat them in isolation. This gap leads to rank inversions: the scheduler that appears optimal under an interference-free model can be the worst choice under realistic wireless conditions. We present ncsim, a lightweight discrete-event simulator that bridges this gap by combining DAG workflow scheduling with physically-grounded IEEE 802.11 CSMA/CA interference modeling in a single Python package. A 108-run factorial experiment reveals rank inversions in 27.8% of scenarios, with the interference-free-optimal scheduler producing up to 2.7x worse makespan than a simple round-robin baseline; scaling to a 100-node random geometric graph raises the inversion rate to 50%. These rank inversions show that interference-free evaluation can select the wrong algorithm entirely, justifying the design and use of ncsim.