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    Green Frame Aggregation Scheme for IEEE 802.11n Networks

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    Thesis
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    Type
    Thesis
    Authors
    Alaslani, Maha S. cc
    Advisors
    Shihada, Basem cc
    Committee members
    Alouini, Mohamed-Slim cc
    Zhang, Xiangliang cc
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2015-04
    Permanent link to this record
    http://hdl.handle.net/10754/552098
    
    Metadata
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    Abstract
    Frame aggregation is one of the major MAC layer enhancements in the IEEE 802.11 family that boosts the network throughput performance. It aims to achieve higher throughput by transmitting huge amount of data in a single transmit oppor- tunity. With the increasing awareness of energy e ciency, it has become vital to rethink about the design of such frame aggregation protocol. Aggregation techniques help to reduce energy consumption over ideal channel conditions. However, in a noisy channel environment, a new energy-aware frame aggregation scheme is required. In this thesis, a novel Green Frame Aggregation (GFA) scheduling scheme has been proposed and evaluated. GFA optimizes the aggregate size based on channel quality in order to minimize the consumed energy. GFA selects the optimal sub-frame size that satisfies the loss constraint for real-time applications as well as the energy budget of the ideal channel situations. The design, the implementation, and evaluation of GFA using testbed deployment is done. The experimental analysis shows that GFA outperforms the conventional frame aggregation methodology in terms of energy e ciency by about 6⇥ in the presence of severe interference conditions. Moreover, GFA also outperforms the static frame sizing method in terms of network goodput and maintains almost the same end- to-end latency.
    Citation
    Alaslani, M. S. (2015). Green Frame Aggregation Scheme for IEEE 802.11n Networks. KAUST Research Repository. https://doi.org/10.25781/KAUST-09LXH
    DOI
    10.25781/KAUST-09LXH
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-09LXH
    Scopus Count
    Collections
    MS Theses; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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