Edge AIBench 2.0: A scalable autonomous vehicle benchmark for IoT–Edge–Cloud systems Article Swipe
Tianshu Hao
,
Wanling Gao
,
Chuanxin Lan
,
Fei Tang
,
Zihan Jiang
,
Jianfeng Zhan
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.tbench.2023.100086
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.tbench.2023.100086
Many emerging IoT–Edge–Cloud computing systems are not yet implemented or are too confidential to share the code or even tricky to replicate its execution environment, and hence their benchmarking is very challenging. This paper uses autonomous vehicles as a typical scenario to build the first benchmark for IoT–Edge–Cloud systems. We propose a set of distilling rules for replicating autonomous vehicle scenarios to extract critical tasks with intertwined interactions. The essential system-level and component-level characteristics are captured while the system complexity is reduced significantly so that users can quickly evaluate and pinpoint the system and component bottlenecks. Also, we implement a scalable architecture through which users can assess the systems with different sizes of workloads.We conduct several experiments to measure the performance. After testing two thousand autonomous vehicle task requests, we identify the bottleneck modules in autonomous vehicle scenarios and analyze their hotspot functions. The experiment results show that the lane-keeping task is the slowest execution module, with a tail latency of 77.49 ms for the 99th percentile latency. We hope this scenario benchmark will be helpful for Autonomous Vehicles and even IoT–edge–Cloud research. Now the open-source code is available from the official website https://www.benchcouncil.org/scenariobench/edgeaibench.html.
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- Language
- en
- Landing Page
- https://doi.org/10.1016/j.tbench.2023.100086
- OA Status
- diamond
- Cited By
- 2
- References
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- Related Works
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https://openalex.org/W4321033926Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.tbench.2023.100086Digital Object Identifier
- Title
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Edge AIBench 2.0: A scalable autonomous vehicle benchmark for IoT–Edge–Cloud systemsWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-01Full publication date if available
- Authors
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Tianshu Hao, Wanling Gao, Chuanxin Lan, Fei Tang, Zihan Jiang, Jianfeng ZhanList of authors in order
- Landing page
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https://doi.org/10.1016/j.tbench.2023.100086Publisher landing page
- Open access
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1016/j.tbench.2023.100086Direct OA link when available
- Concepts
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Computer science, Cloud computing, Bottleneck, Benchmarking, Scalability, Benchmark (surveying), Edge computing, Distributed computing, Enhanced Data Rates for GSM Evolution, Embedded system, Operating system, Artificial intelligence, Marketing, Geography, Geodesy, BusinessTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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