When edge computing meets compact data structures

Zheng Li, Diego Seco, Jose Fuentes-Sepulveda

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

1 Citation (Scopus)

Abstract

Edge computing enables data processing and storage closer to where the data are created. Given the largely distributed compute environment and the significantly dispersed data distribution, there are increasing demands of data sharing and collaborative processing on the edge. Since data shuffling can dominate the overall execution time of collaborative processing jobs, considering the limited power supply and bandwidth resource in edge environments, it is crucial and valuable to reduce the communication overhead across edge devices. Compared with data compression, compact data structures (CDS) seem to be more suitable in this case, for the capability of allowing data to be queried, navigated, and manipulated directly in a compact form. However, the relevant work about applying CDS to edge computing generally focuses on the intuitive benefit from reduced data size, while few discussions about the challenges are given, not to mention empirical investigations into real-world edge use cases. This research highlights the challenges, opportunities, and potential scenarios of CDS implementation in edge computing. Driven by the use case of shuffling-intensive data analytics, we proposed a three-layer architecture for CDS-aided data processing and particularly studied the feasibility and efficiency of the CDS layer. We expect this research to foster conjoint research efforts on CDS-aided edge data analytics and to make wider practical impacts.

Original languageEnglish
Title of host publicationProceedings of the 2021 IEEE Cloud Summit
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages29-34
ISBN (Electronic)9781665425827
DOIs
Publication statusPublished - 29 Dec 2021
Externally publishedYes
Event2021 IEEE Cloud Summit - Hempstead, United States
Duration: 21 Oct 202122 Oct 2021
https://www.computer.org/csdl/proceedings/cloud-summit/2021/1zJmLY3bL4Q

Publication series

NameProceedings of the IEEE Cloud Summit
PublisherIEEE

Conference

Conference2021 IEEE Cloud Summit
Country/TerritoryUnited States
CityHempstead
Period21/10/202122/10/2021
Internet address

Keywords

  • Collaborative data analytics
  • Communication overhead
  • Compact data structure
  • Data shuffling
  • Edge computing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Optimization
  • Information Systems and Management

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