An information-theoretic view of cloud workloads

Lav R. Varshney, Krishna C. Ratakonda

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

Abstract

Analytics-as-a-service is emerging as a key offering for cloud systems, however in the petascale regime, data transfer bottlenecks are a limiting factor. Often information has to be transmitted to the cloud by physical transportation. Efficient information representations that leverage the functional purpose of data for the analytics service to be offered can serve to ameliorate many of these information flow bottlenecks. In this paper, we provide an information-theoretic view on optimal information representations for big data analytics in the cloud. We also provide some structural design principles for building a petascale analytics appliance.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages466-471
Number of pages6
ISBN (Electronic)9781479937660
DOIs
StatePublished - Sep 18 2014
Externally publishedYes
Event2nd IEEE International Conference on Cloud Engineering, IC2E 2014 - Boston, United States
Duration: Mar 10 2014Mar 14 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Cloud Engineering, IC2E 2014

Other

Other2nd IEEE International Conference on Cloud Engineering, IC2E 2014
Country/TerritoryUnited States
CityBoston
Period3/10/143/14/14

Keywords

  • Analytics-as-a-service
  • cloud computing
  • data compression
  • data transfer bottlenecks
  • information theory

ASJC Scopus subject areas

  • Software

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