Network-Aware Optimization of Distributed Learning for Fog Computing

Yuwei Tu, Yichen Ruan, Satyavrat Wagle, Christopher G. Brinton, Carlee Joe-Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

43 Scopus citations


Fog computing promises to enable machine learning tasks to scale to large amounts of data by distributing processing across connected devices. Two key challenges to achieving this are (i) heterogeneity in devices' compute resources and (ii) topology constraints on which devices can communicate. We are the first to address these challenges by developing a network-aware distributed learning optimization methodology where devices process data for a task locally and send their learnt parameters to a server for aggregation at certain time intervals. Unlike traditional federated learning frameworks, our method enables devices to offload their data processing tasks, with these decisions determined through a convex data transfer optimization problem that trades off costs associated with devices processing, offloading, and discarding data points. We analytically characterize the optimal data transfer solution for different fog network topologies, showing for example that the value of a device offloading is approximately linear in the range of computing costs in the network. Our subsequent experiments on both synthetic and real-world datasets we collect confirm that our algorithms are able to improve network resource utilization substantially without sacrificing the accuracy of the learned model.

Original languageEnglish (US)
Title of host publicationINFOCOM 2020 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781728164120
StatePublished - Jul 2020
Externally publishedYes
Event38th IEEE Conference on Computer Communications, INFOCOM 2020 - Toronto, Canada
Duration: Jul 6 2020Jul 9 2020

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference38th IEEE Conference on Computer Communications, INFOCOM 2020

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Electrical and Electronic Engineering


  • federated learning
  • fog computing
  • offloading


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