DeFog: Fog Computing Benchmarks
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Abstract (arXiv)
Fog computing envisions that deploying services of an application across resources in the cloud and those located at the edge of the network may improve the overall performance of the application when compared to running the application on the cloud. However, there are currently no benchmarks that can directly compare the performance of the application across the cloud-only, edge-only and cloud-edge deployment platform to obtain any insight on performance improvement. This paper proposes DeFog, a first Fog benchmarking suite to: (i) alleviate the burden of Fog benchmarking by using a standard methodology, and (ii) facilitate the understanding of the target platform by collecting a catalogue of relevant metrics for a set of benchmarks. The current portfolio of DeFog benchmarks comprises six relevant applications conducive to using the edge. Experimental studies are carried out on multiple target platforms to demonstrate the use of DeFog for collecting metrics related to application latencies (communication and computation), for understanding the impact of stress and concurrent users on application latencies, and for understanding the performance of deploying different combination of services of an application across the cloud and edge. DeFog is available for public download (https://github.com/qub-blesson/DeFog).
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Jul 2019.
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Citing papers per year: 2021: 4; 2022: 3.
7 papers.
- 2021PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computingcited by 8
- 2021HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computingcited by 6
- 2021Generative Optimization Networks for Memory Efficient Data Generationcited by 5
- 2021GOSH: Task Scheduling Using Deep Surrogate Models in Fog Computing Environmentscited by 5
- 2022CAROL: Confidence-Aware Resilience Model for Edge Federationscited by 3
- 2022DRAGON: Decentralized Fault Tolerance in Edge Federationscited by 2
- 2022DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Modelcited by 2
- 2022DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Model2 Dec 2022
- 2022DRAGON: Decentralized Fault Tolerance in Edge Federations16 Aug 2022
- 2022CAROL: Confidence-Aware Resilience Model for Edge Federations14 Mar 2022
- 2021GOSH: Task Scheduling Using Deep Surrogate Models in Fog Computing Environments16 Dec 2021
- 2021PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computing4 Dec 2021
- 2021HUNTER: AI based Holistic Resource Management for Sustainable Cloud Computing11 Oct 2021
- 2021Generative Optimization Networks for Memory Efficient Data Generation6 Oct 2021