IDEAS home Printed from https://ideas.repec.org/a/wly/intnem/v29y2019i2ne2062.html
   My bibliography  Save this article

An approach for provisioning virtual sensors in sensor clouds

Author

Listed:
  • Marcus Lemos
  • Ricardo Rabelo
  • Douglas Mendes
  • Carlos Carvalho
  • Raimir Holanda

Abstract

In sensor clouds environments, the provisioning process is a crucial task since it is responsible for selecting physical sensors that will be used to create virtual sensors. However, most works consider the allocation of all sensors within the region of interest, causing serious problems such as the wasting of energy consumption. The objective of this paper is to present ACxSIM, an automatic approach to the provisioning of virtual sensors. ACxSIM includes two algorithms: adaptive clustering algorithm based on similarity (ACASIM) and ant colony optimization for sensor selection based on similarity (ACOSIM). ACASIM first clusters the sensor nodes based on the similarity of its measurements (exploiting the temporal and spatial correlations between them), which may create clusters with nodes not physically close to each other. Therefore, in ACASIM, a cluster represents different geographical areas whose nodes have correlated measurements (according to a defined error threshold). Later, ACOSIM, based on ant colony optimization algorithm, creates virtual sensors by selecting only a subset of nodes from each cluster. In this way, the overall energy consumption of sensor nodes is reduced, prolonging the lifetime of the sensor cloud. Results from experiments in Intel Lab dataset show that the ACxSIM reduces energy consumption by 73.97%, providing a solution to be considered in sensor cloud scenarios.

Suggested Citation

  • Marcus Lemos & Ricardo Rabelo & Douglas Mendes & Carlos Carvalho & Raimir Holanda, 2019. "An approach for provisioning virtual sensors in sensor clouds," International Journal of Network Management, John Wiley & Sons, vol. 29(2), March.
  • Handle: RePEc:wly:intnem:v:29:y:2019:i:2:n:e2062
    DOI: 10.1002/nem.2062
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nem.2062
    Download Restriction: no

    File URL: https://libkey.io/10.1002/nem.2062?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:intnem:v:29:y:2019:i:2:n:e2062. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1099-1190 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.