Coded Computation Against Straggling Decoders for Network Function Virtualization

Malihe Aliasgari, Jorg Kliewer, Osvaldo Simeone

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

8 Scopus citations

Abstract

The uplink of a cloud radio access network architecture is studied in which decoding at the cloud takes place via network function virtualization (NFV) on commercial off-the-shelf (COTS) servers. In order to mitigate the impact of straggling decoders in the cloud computing platform, a novel coding strategy is proposed, whereby the cloud re-encodes the received frames via a linear code before distributing them to the decoding processors. Upper bounds on the resulting frame unavailability probability (FUP) as a function of the decoding latency are derived by assuming a binary symmetric channel for uplink communications. The bounds leverage large deviation results for correlated variables, and depend on the properties of both the uplink linear channel code adopted at the user and the NFV linear code applied at the cloud. Numerical examples demonstrate that the bounds are useful tools for code design, and that coding is instrumental in obtaining a desirable tradeoff between FUP and decoding latency.

Original languageEnglish (US)
Title of host publication2018 IEEE International Symposium on Information Theory, ISIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages711-715
Number of pages5
ISBN (Print)9781538647806
DOIs
StatePublished - Aug 15 2018
Event2018 IEEE International Symposium on Information Theory, ISIT 2018 - Vail, United States
Duration: Jun 17 2018Jun 22 2018

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2018-June
ISSN (Print)2157-8095

Other

Other2018 IEEE International Symposium on Information Theory, ISIT 2018
Country/TerritoryUnited States
CityVail
Period6/17/186/22/18

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Keywords

  • C-RAN
  • Coded computation
  • Large deviation
  • Network function virtualization

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