Distributed Active Learning Strategies on Edge Computing

Jia Qian, Sarada Prasad Gochhayat, Lars Kai Hansen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Fog platform brings the computing power from the remote cloud-side closer to the edge devices to reduce latency, as the unprecedented generation of data causes ineligible latency to process the data in a centralized fashion at the Cloud. In this new setting, edge devices with distributed computing capability, such as sensors, surveillance camera, can communicate with fog nodes with less latency. Furthermore, local computing (at edge side) may improve privacy and trust. In this paper, we present a new method, in which, we decompose the data processing, by dividing them between edge devices and fog nodes, intelligently. We apply active learning on edge devices; and federated learning on the fog node which significantly reduces the data samples to train the model as well as the communication cost. To show the effectiveness of the proposed method, we implemented and evaluated its performance on a benchmark images data set.

Original languageEnglish
Title of host publicationProceedings of 6th IEEE International Conference on Cyber Security and Cloud Computing and 5th IEEE International Conference on Edge Computing and Scalable Cloud
EditorsMeikang Qiu
PublisherIEEE
Publication date1 Jun 2019
Pages221-226
Article number8854053
ISBN (Electronic)9781728116600
DOIs
Publication statusPublished - 1 Jun 2019
Event6th IEEE International Conference on Cyber Security and Cloud Computing and 5th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud/EdgeCom 2019 - Paris, France
Duration: 21 Jun 201923 Jun 2019

Conference

Conference6th IEEE International Conference on Cyber Security and Cloud Computing and 5th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud/EdgeCom 2019
CountryFrance
CityParis
Period21/06/201923/06/2019
SponsorIEEE, IEEE, IEEE, IEEE, Columbia University

Keywords

  • Active Learning
  • Bayesian Neural Network
  • Edge Computing
  • Federated Learning
  • Fog Computing

Cite this

Qian, J., Gochhayat, S. P., & Hansen, L. K. (2019). Distributed Active Learning Strategies on Edge Computing. In M. Qiu (Ed.), Proceedings of 6th IEEE International Conference on Cyber Security and Cloud Computing and 5th IEEE International Conference on Edge Computing and Scalable Cloud (pp. 221-226). [8854053] IEEE. https://doi.org/10.1109/CSCloud/EdgeCom.2019.00029