• Login
    View Item 
    •   Home
    • Research
    • Conference Papers
    • View Item
    •   Home
    • Research
    • Conference Papers
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of KAUSTCommunitiesIssue DateSubmit DateThis CollectionIssue DateSubmit Date

    My Account

    Login

    Quick Links

    Open Access PolicyORCID LibguideTheses and Dissertations LibguideSubmit an Item

    Statistics

    Display statistics

    gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Type
    Conference Paper
    Authors
    Al-Halafi, Abdullah cc
    Sboui, Lokman cc
    Naous, Rawan cc
    Shihada, Basem cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2016-09-08
    Online Publication Date
    2016-09-08
    Print Publication Date
    2016-04
    Permanent link to this record
    http://hdl.handle.net/10754/622554
    
    Metadata
    Show full item record
    Abstract
    Wireless sensor networks (WSN) are widely used to sense and measure physical conditions for different purposes and within different regions. However due to the limited lifetime of the sensor's energy source, many efforts are made to design energy efficient WSN. As a result, many techniques were presented in the literature such as power adaptation, sleep and wake-up, and scheduling in order to enhance WSN lifetime. These techniques where presented separately and shown to achieve some gain in terms of energy efficiency. In this paper, we present an energy efficient cross layer design for WSN that we named 'green Task-Based Sensing' (gTBS) scheme. The gTBS design is a task based sensing scheme that not only prevents wasting power in unnecessary signaling, but also utilizes several techniques for achieving reliable and energy efficient WSN. The proposed gTBS combines the power adaptation with a sleep and wake-up technique that allows inactive nodes to sleep. Also, it adopts a gradient-oriented unicast approach to overcome the synchronization problem, minimize network traffic hurdles, and significantly reduce the overall power consumption of the network. We implement the gTBS on a testbed and we show that it reduces the power consumption by a factor of 20%-55% compared to traditional TBS. It also reduces the delay by 54%-145% and improves the delivery ratio by 24%-73%. © 2016 IEEE.
    Citation
    Alhalafi A, Sboui L, Naous R, Shihada B (2016) gTBS: A green Task-Based Sensing for energy efficient Wireless Sensor Networks. 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). Available: http://dx.doi.org/10.1109/INFCOMW.2016.7562060.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
    Conference/Event name
    35th IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2016
    DOI
    10.1109/INFCOMW.2016.7562060
    Additional Links
    http://ieeexplore.ieee.org/document/7562060/
    ae974a485f413a2113503eed53cd6c53
    10.1109/INFCOMW.2016.7562060
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

    entitlement

     
    DSpace software copyright © 2002-2023  DuraSpace
    Quick Guide | Contact Us | KAUST University Library
    Open Repository is a service hosted by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items. For anonymous users the allowed maximum amount is 50 search results.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.