Model transition planning in participatory sensing cold start

Fatemeh Saremi, Tarek Abdelzaher

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

Abstract

"Cold Start" in participatory sensing applications refers to the initial stage in service deployment, during which service adoption remains sparse and, hence, the collected data does not offer adequate coverage. Predictive models, learned from data, offer a way to generalize from sparse observations, but the models themselves need to be statistically reliable to offer a reliable service. To achieve service reliability, this paper offers a modeling approach, where simpler models are used initially, gradually transitioning to more elaborate models, when enough data is collected. A key challenge and contribution of the work is to time model transitions correctly to provide theoretical guarantees on modeling error. Our technique takes a holistic approach in bounding modeling error as opposed to prior statistical approaches that bound the error of a single model component at a time. This technique is tested in the context of a vehicular participatory sensing application.

Original languageEnglish (US)
Title of host publicationProceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages99-101
Number of pages3
ISBN (Electronic)9781509014590
DOIs
StatePublished - Aug 8 2016
Event12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016 - Washington, United States
Duration: May 26 2016May 28 2016

Publication series

NameProceedings - 12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016

Other

Other12th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2016
CountryUnited States
CityWashington
Period5/26/165/28/16

Keywords

  • Modeling
  • Participatory sensing
  • Reliability

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems and Management

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