An Early Resource Characterisation of Wi-Fi Sensing on Residential Gateways

Chulhong Min, Mohammed Alloulah, Fahim Kawsar

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

Recent research has successfully shown brand new models with Wi- Fi signals explaining space dynamics, assessing social environments, and even tracking people's posture, gesture and emotion. However, these models are seldom used in real execution and operating environments, i.e., on residential gateways with networking tasks. In this paper, we present the first, albeit preliminary, measurement study of common Wi-Fi sensing models on a residential gateway. This investigation aims to understand the performance characteristics, resource requirements, and execution bottlenecks for Wi-Fi sensing when being used in parallel with communication tasks. Based on our findings, we propose two optimisation techniques - i) dynamic sampling and ii) dynamic planning of inference execution - for optimum Wi-Fi sensing performance without compromising the quality of communication service. The results and insights lay an empirical foundation for the development of optimisation methods and execution environments that enable sensing models to be more readily integrated into next-generation residential gateways.

Original languageEnglish
Title of host publicationBuildSys'18
Subtitle of host publicationProceedings of the 5th Conference on Systems for Built Environments
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages140-143
Number of pages4
ISBN (Print)978-145035951-1
DOIs
Publication statusPublished - 2018
Event5th ACM International Conference on Systems for Built Environments, BuildSys 2018 - Shenzen, China
Duration: 7 Nov 20188 Nov 2018

Conference

Conference5th ACM International Conference on Systems for Built Environments, BuildSys 2018
CountryChina
CityShenzen
Period7/11/188/11/18

Keywords

  • Residential Gateways
  • Runtime Adaptation
  • Wi-Fi Sensing

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