BearLoc: A composable distributed framework for indoor localization systems

Kaifei Chen, Siyuan He, Beidi Chen, John Kolb, Randy H. Katz, David E. Culler

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

2 Scopus citations

Abstract

Many indoor localization algorithms have been proposed to enable location-based applications in indoor environments. However, these systems are monolithic and not component-based. We present BearLoc, a distributed modular framework for indoor localization systems that provides (1) natural development abstractions for sensor, algorithm, and application components, and (2) easy and exible component composition. We demonstrate the merits of BearLoc with an example use case. Our evaluation shows we can reduce developer lines of code by 60% while introducing acceptable network delay overhead.

Original languageEnglish (US)
Title of host publicationIoT-Sys 2015 - Proceedings of the 2015 Workshop on IoT Challenges in Mobile and Industrial Systems
PublisherAssociation for Computing Machinery, Inc
Pages7-12
Number of pages6
ISBN (Electronic)9781450335027
DOIs
StatePublished - May 18 2015
Externally publishedYes
Event1st Workshop on IoT Challenges in Mobile and Industrial Systems, IoT-Sys 2015 - Florence, Italy
Duration: May 18 2015 → …

Publication series

NameIoT-Sys 2015 - Proceedings of the 2015 Workshop on IoT Challenges in Mobile and Industrial Systems

Conference

Conference1st Workshop on IoT Challenges in Mobile and Industrial Systems, IoT-Sys 2015
Country/TerritoryItaly
CityFlorence
Period5/18/15 → …

Bibliographical note

Publisher Copyright:
© 2015 ACM.

Keywords

  • Composability
  • Framework
  • Localization

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