qijianpeng/awesome-edge-computing

A curated list of awesome edge computing, including Frameworks, Simulators, Tools, etc.

What it solves

Edge computing spans many overlapping technologies—simulators, frameworks, network emulators, AI toolkits, benchmark datasets, and academic groups—with no single source of truth to compare them. This project curates those resources into one alphabetized directory, saving researchers and engineers the time spent hunting across GitHub, academic papers, and project wikis to find the right tool for a given task. It also addresses the need for standardized comparison by linking to a companion paper and an interactive web interface that break down platforms, inheritance relationships, and programming languages.

How it works

Everything is organized as an "awesome list"—a structured Markdown document where every entry is a named tool or resource with a short description and a link. The categories are: Simulators, Frameworks (split into Engine and Networks), Test (data and benchmarks), Tools, Applications, Edge-AI frameworks, Academic institutions, and Other awesome lists. All artifacts are arranged in alphabetical order. The README points to an arXiv paper (2505.09995) for detailed cross-platform comparisons and to an interactive web page that presents the same content in a more explorable format. The list itself is the primary deliverable: a written, human-readable index rather than a software package.

Who it's for

Researchers and practitioners working in edge computing, fog computing, cloud-edge hybrid systems, and related fields like vehicular networks (V2X), IoT, and edge AI. It suits anyone who needs to survey the landscape, choose a simulator for experiments, or find an existing framework before building their own. The alphabetized, category-based structure makes it useful both as a quick lookup reference and as a starting point for a broader literature or tool survey.

Highlights

  • Covers a broad spectrum: simulators, emulators, frameworks, benchmarks, tools, applications, edge-AI frameworks, and academic institutions in one place.
  • Every entry includes a one-paragraph description and a direct link, with everything sorted alphabetically for consistent navigation.
  • Links to an arXiv paper (2505.09995) that provides detailed comparisons across platforms, inheritance relationships, and programming languages—added depth beyond the list itself.
  • An interactive web version (qijianpeng.github.io/repositories/edge-computing/) offers a more dynamic way to browse the same repository contents.

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