Demo Abstract: Decomposing Data Analytics in Fog Networks

Ta Cheng Chang, Chege Gitau, Liang Zheng, Ching-Yao Huang, Maria Gorlatova, Mung Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Fog computing, the distribution of computing resources closer to the end devices along the cloud-to-things continuum, is recently emerging as an architecture for scaling of the Internet of Things (IoT) sensor networking applications. Fog computing requires novel computing program decompositions for heterogeneous hierarchical settings. To evaluate these new decompositions, we designed, developed, and instrumented a fog computing testbed that includes cloud computing and computing gateway execution points collaborating to finish complex data analytics operations. In this interactive demonstration we present one fog-specific algorithmic decomposition we recently examined and adapted for fog computing: a multi-execution point linear regression decomposition that jointly optimizes operation latency, quality, and costs. The demonstration highlights the role fog computing can play in future sensor networking architectures, and highlights some of the challenges of creating computing program decompositions for these architectures. An annotated video of the demonstration is available at [5].

Original languageEnglish
Title of host publicationSenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
EditorsRasit Eskicioglu
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450354592
DOIs
StatePublished - 6 Nov 2017
Event15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017 - Delft, Netherlands
Duration: 6 Nov 20178 Nov 2017

Publication series

NameSenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
Volume2017-January

Conference

Conference15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017
CountryNetherlands
CityDelft
Period6/11/178/11/17

Keywords

  • Data analytics
  • Distributed systems
  • Edge computing
  • Fog computing
  • Heterogeneous architectures
  • Internet of Things

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