# Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking

arXiv: https://arxiv.org/abs/1908.01924 · HTML: https://mlsanity.com/paper/1908.01924/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Aug 2019.

## Built on by (most cited first, 6 of 6)

- [Towards Personalized Federated Learning](https://mlsanity.com/paper/2103.00710/) (2021)
- [Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey](https://mlsanity.com/paper/2505.01821/) (2025)
- [A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things](https://mlsanity.com/paper/2104.10501/) (2021)
- [Optimizing Performance of Federated Person Re-identification: Benchmarking and Analysis](https://mlsanity.com/paper/2205.12144/) (2022)
- [CAROL: Confidence-Aware Resilience Model for Edge Federations](https://mlsanity.com/paper/2203.07140/) (2022)
- [DRAGON: Decentralized Fault Tolerance in Edge Federations](https://mlsanity.com/paper/2208.07658/) (2022)

## Abstract (arXiv)

In edge computing scenarios, the distribution of data and collaboration of workloads on different layers are serious concerns for performance, privacy, and security issues. So for edge computing benchmarking, we must take an end-to-end view, considering all three layers: client-side devices, edge computing layer, and cloud servers. Unfortunately, the previous work ignores this most important point. This paper presents the BenchCouncil's coordinated e ort on edge AI benchmarks, named Edge AIBench. In total, Edge AIBench models four typical application scenarios: ICU Patient Monitor, Surveillance Camera, Smart Home, and Autonomous Vehicle with the focus on data distribution and workload collaboration on three layers. Edge AIBench is a part of the open-source AIBench project, publicly available from http://www.benchcouncil.org/AIBench/index.html. We also build an edge computing testbed with a federated learning framework to resolve performance, privacy, and security issues.