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A genetic algorithm-based solution for efficient in-network sensor data annotation in virtualized Wireless Sensor Networks

  • Imran Khan
  • , Jagruti Sahoo
  • , Son Han
  • , Roch Glitho
  • , Noël Crespi
  • CNRS SAMOVAR UMR 5157
  • Concordia Institute for Information Systems Engineering

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

13 Citations (Scopus)

Abstract

Sharing a deployed Wireless Sensor Network Infrastructure (WSNI), (using virtualization), among multiple, concurrent applications can help realize the true potential of Internet-of-Things (IoT). Virtualized WSNs can be used by multiple applications and services concurrently including semantic applications to help end-users to understand the context of the events and make informed decisions. This paper proposes a heuristic-based genetic algorithm to select capable nodes to perform efficient in-network sensor data annotation in virtualized WSNs. We also present early simulations results.

Original languageEnglish
Title of host publication2016 13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages321-322
Number of pages2
ISBN (Electronic)9781467392921
DOIs
Publication statusPublished - 30 Mar 2016
Externally publishedYes
Event13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016 - Las Vegas, United States
Duration: 6 Jan 201613 Jan 2016

Publication series

Name2016 13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016

Conference

Conference13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016
Country/TerritoryUnited States
CityLas Vegas
Period6/01/1613/01/16

Keywords

  • Genetic Algorithm
  • Internet of Things (IoT)
  • Semantic Web
  • WSN Virtualization
  • Wireless Sensor Networks

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