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When Service-Oriented Computing Meets the IoT: A Use Case in the Context of Urban Mobile Crowdsensing

Invited Paper
  • Valérie IssarnyEmail author
  • Georgios Bouloukakis
  • Nikolaos Georgantas
  • Françoise Sailhan
  • Géraldine Texier
Conference paper
  • 460 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11116)

Abstract

The possibilities of new mobile distributed systems have reached unprecedented levels. Such systems are dynamically composed of networked resources in the environment, which may span from the immediate neighborhood of the users - as advocated by pervasive computing - up to the entire globe - as envisioned by the Future Internet and one of its major constituents, the Internet of Things. This paper more specifically concentrates on urban participatory mobile distributed systems where people get involved in producing new knowledge about the urban environment. Service-oriented and cloud computing are evident baseline technologies for the target mobile distributed systems. Service orientation provides the abstraction to deal with the assembly of the relevant heterogeneous component systems. The cloud provides the infrastructure to deal with the gathering and analyses of the observations coming from the sensing infrastructure, including from people. However, cloud-based centralized solutions come at a price, regarding both resource consumption and privacy risk. Further, the high heterogeneity of the participating nodes results in diverse levels of sensing accuracy. This paper provides an overview of our past and ongoing research to overcome the challenges facing urban participatory mobile distributed systems, which leverages mobile collaborative sensing, networking and computing. The experience with the Ambiciti platform and associated mobile app for monitoring the individual and collective exposure to environmental pollution serves as an illustrative use case.

Keywords

IoT Interoperability Middleware Mobile crowdsensing Urban sensing systems Multiparty calibration 

Notes

Acknowledgments

The authors would like to thank the support of: the Inria@SiliconValley International Lab, CityLab@Inria Project lab, and the EIT Digital innovation activity Env&You. They also gratefully acknowledge the major contribution of their Inria colleagues, Vivien Mallet, Pierre-Guillaume Raverdy and Kinh Nguyen, to the development of the Ambiciti system solution.

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  • Valérie Issarny
    • 1
    Email author
  • Georgios Bouloukakis
    • 1
  • Nikolaos Georgantas
    • 1
  • Françoise Sailhan
    • 2
  • Géraldine Texier
    • 3
  1. 1.InriaParisFrance
  2. 2.CNAMParisFrance
  3. 3.IMT Atlantique/IRISA/UBLRennesFrance

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