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

2026-05-01

AI Summary

Existing evaluation tools for wireless edge computing task scheduling typically model computation placement and wireless interference in isolation, leading to significant performance degradation—and even rank reversals—of schedulers deemed optimal in interference-free settings when deployed in real-world scenarios. To address this limitation, this work proposes ncsim, the first lightweight discrete-event simulator implemented in Python that jointly models DAG-based task scheduling and physical-layer-aware IEEE 802.11 CSMA/CA interference within a unified framework. Experimental results demonstrate that rank reversals occur in 27.8% of 108 test cases, rising to 50% in random topologies with 100 nodes. Moreover, schedulers selected as “optimal” under interference-agnostic assumptions can exhibit worst-case makespans up to 2.7× that of a simple round-robin baseline, underscoring the critical necessity of joint modeling.

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.

Problem

• DAG task scheduling
• wireless edge computing
• wireless interference
• scheduler evaluation
• compute placement

Innovation

• edge computing
• wireless interference
• DAG scheduling
• discrete-event simulation
• CSMA/CA