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    Location-Aware, Context-Driven QoS for IoT Applications

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    Type
    Article
    Authors
    Ahmad, Enas M.
    Alaslani, Maha S. cc
    Dogar, Fahad R.
    Shihada, Basem cc
    KAUST Department
    Computer Science
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2019-02-12
    Online Publication Date
    2019-02-12
    Print Publication Date
    2020-03
    Permanent link to this record
    http://hdl.handle.net/10754/655920
    
    Metadata
    Show full item record
    Abstract
    In this paper, we identify the unique quality of service (QoS) needs of emerging IoT applications and propose SDN-based Application-aware Dynamic Internet of things Quality of service (SADIQ), a software-defined network (SDN) framework that addresses these needs. SADIQ provides location-aware, context-driven QoS for IoT applications by allowing applications to express their requirements using a location-based abstraction and a high-level SQL-like policy language, and the network to support these requirements through recent advances in SDNs. We implement SADIQ using commodity OpenFlow-enabled switches and an open-source SDN controller and evaluate its effectiveness using traces from two real IoT applications. Our results show that SADIQ improves the percentage of regions with error in their reported temperature for the Weather Signal application up to 45x, and improves the percentage of incorrect parking statuses for regions with high occupancy for the Smart Parking application up to 30x, under the same network conditions and drop rates.
    Citation
    Ahmad, E., Alaslani, M., Dogar, F. R., & Shihada, B. (2020). Location-Aware, Context-Driven QoS for IoT Applications. IEEE Systems Journal, 14(1), 232–243. doi:10.1109/jsyst.2019.2893913
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Systems Journal
    DOI
    10.1109/JSYST.2019.2893913
    Additional Links
    https://ieeexplore.ieee.org/document/8640087/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8640087
    ae974a485f413a2113503eed53cd6c53
    10.1109/JSYST.2019.2893913
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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