Distributed Deep Learning on FogBus and Aneka - A tutorial. Implement, deploy and test a distributed deep learning software on a Fog Computing setup using FogBus. In this repo we have deployed an object detection YOLO software on multiple edge devices (raspberry pis) and cloud VMs (using Azure).
@article{tuli2019edgelens,
title={{Edgelens: Deep learning based object detection in integrated iot, fog and cloud computing environments}},
author={Tuli, Shreshth and Basumatary, Nipam and Buyya, Rajkumar},
journal={arXiv preprint arXiv:1906.11056},
year={2019}
}
- Shreshth Tuli, Redowan Mahmud, Shikhar Tuli, and Rajkumar Buyya, FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing. Journal of Systems and Software (JSS), Volume 154, Pages: 22-36, ISSN: 0164-1212, Elsevier Press, Amsterdam, The Netherlands, August 2019.
- Shreshth Tuli, Nipam Basumatary, Sukhpal Singh Gill, Mohsen Kahani, Rajesh Chand Arya, Gurpreet Singh Wander, and Rajkumar Buyya, HealthFog: An Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments, Future Generation Computer Systems (FGCS), Volume 104, Pages: 187-200, ISSN: 0167-739X, Elsevier Press, Amsterdam, The Netherlands, March 2020.
- Shreshth Tuli, Nipam Basumatary, and Rajkumar Buyya, EdgeLens: Deep Learning based Object Detection in Integrated IoT, Fog and Cloud Computing Environments, Proceedings of the 4th IEEE International Conference on Information Systems and Computer Networks (ISCON 2019, IEEE Press, USA), Mathura, India, November 21-22, 2019.
