ncsim: A Lightweight Simulator for Networked Edge Computing with Wireless Interference Modeling

TL;DR

ncsim is a Python-based discrete-event simulator that models wireless interference and DAG task scheduling for edge computing, revealing that interference-aware evaluation is crucial for accurate scheduler selection.

Contribution

It introduces ncsim, the first tool to jointly simulate DAG scheduling and IEEE 802.11 interference, exposing significant rank inversions in scheduler performance evaluations.

Findings

Interference-free models can mislead scheduler selection, causing up to 2.7x worse makespan.

Rank inversions occur in 27.8% of small scenarios and 50% in larger networks.

Interference-aware simulation is essential for accurate edge computing scheduler assessment.

Abstract

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.