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    Bio-inspired energy and channel management in distributed wireless multi-radio networks

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    Date
    2014-06
    Author
    Mekuira, F
    Masonta, M T
    Olwal, T O
    Type
    Article; en
    Language
    en
    Metadata
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    Abstract
    In the recent past, research in the next generation wireless heterogeneous broadband networks has favoured the design of multi-radio interface over the single radio interface architectures in order to support desirable features such as a self-organisation, self-configuration, reliability and robustness of network operations in a resource-constrained environment. However, such autonomous network behaviours have been seen to cause an inefficient consumption of energy and frequency channel resources, impacting negatively on the economy and environment. In order to address the inefficient energy and frequency channel utilisation problems, this paper proposes a biological behaviour-based network resource management method. The research is inspired by such a well-established optimal foraging theory whereby a solitary biological forager in a random ecosystem makes optimal decisions that maximise its own nutrients consumption, survival probability and lifetime, while minimising possible risks associated with its own behaviour. The paper has applied this natural principle and developed a Bio-inspired Energy and Channel (BEACH) management method. The BEACH method is aimed at achieving both efficient communication energy and frequency channel utilisation in the considered distributed wireless multi-radio network. The efficacy of the developed BEACH method has been extensively validated through computer simulations and shown to yield improved energy-efficiency and throughput performance.
    URI
    http://hdl.handle.net/11295/77320
    Citation
    Olwal, T.O, Masonta, M.T and Mekuira, F. 2014. Bio-inspired energy and channel management in distributed wireless multi-radio networks. IET Science, Measurement & Technology, pp 1-10
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    • Faculty of Engineering, Built Environment & Design (FEng / FBD) [1465]

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