Lagrange Coded Computing with Sparsity Constraints

Mohammad Fahim, Viveck R. Cadambe

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

Abstract

In this paper, we propose a distributed coding scheme that allows for lower computation cost per computing node than the standard Lagrange Coded Computing scheme. The proposed coding scheme is useful for cases where the elements of the input data set are of large dimensions and the computing nodes have limited computation power. This coding scheme provides a trade-off between the computation cost per worker and the recovery threshold in a distributed coded computing framework. The proposed scheme is also extended to provide data privacy against at most t colluding worker nodes in the system.

Original languageEnglish (US)
Title of host publication2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages284-289
Number of pages6
ISBN (Electronic)9781728131511
DOIs
StatePublished - Sep 2019
Event57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019 - Monticello, United States
Duration: Sep 24 2019Sep 27 2019

Publication series

Name2019 57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019

Conference

Conference57th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2019
CountryUnited States
CityMonticello
Period9/24/199/27/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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