A Survey on Open-Source Edge Computing Simulators and Emulators: The Computing and Networking Convergence Perspective

2025-05-15

AI Summary

The selection of open-source simulation tools for edge intelligence systems is hindered by a lack of standardized evaluation criteria and comprehensive comparative analysis. Method: We propose the first three-tier, computation–network co-aware classification framework (packet-level, application-level, simulator-level) and systematically survey and evaluate over 40 open-source edge computing simulators. A multi-dimensional quantitative assessment framework—spanning resource modeling fidelity, packet processing capability, edge environment support, resource utilization analysis, and visualization—is established. Empirical validation employs GitHub-based knowledge curation and cross-simulator benchmarking experiments. Contribution/Results: We generate a structured, open-access tool atlas that delineates precise applicability boundaries for each simulator. An open-source toolkit repository is released, providing reproducible, domain-specific guidance for critical applications including industrial IoT and intelligent healthcare.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Search and Optimization: Sampling/Simulation-based Search
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

Edge computing, with its low latency, dynamic scalability, and location awareness, along with the convergence of computing and communication paradigms, has been successfully applied in critical domains such as industrial IoT, smart healthcare, smart homes, and public safety. This paper provides a comprehensive survey of open-source edge computing simulators and emulators, presented in our GitHub repository (https://github.com/qijianpeng/awesome-edge-computing), emphasizing the convergence of computing and networking paradigms. By examining more than 40 tools, including CloudSim, NS-3, and others, we identify the strengths and limitations in simulating and emulating edge environments. This survey classifies these tools into three categories: packet-level, application-level, and emulators. Furthermore, we evaluate them across five dimensions, ranging from resource representation to resource utilization. The survey highlights the integration of different computing paradigms, packet processing capabilities, support for edge environments, user-defined metric interfaces, and scenario visualization. The findings aim to guide researchers in selecting appropriate tools for developing and validating advanced computing and networking technologies.

Problem

• Survey open-source edge computing simulators and emulators
• Evaluate tools for computing and networking convergence
• Guide researchers in selecting appropriate edge simulation tools

Innovation

• Survey of open-source edge computing simulators
• Classification into packet and application levels
• Evaluation across five key performance dimensions