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    Cognitive Diversity Routing in Wireless Sensor Networks

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    COGNITIVE_DIVERSITY_ROUTING.pdf (5.186Mb)
    Date
    2010-08-25
    Author
    El-Jabi, Zouheir,
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    Abstract
    Energy efficiency and network lifetime are key factors in characterizing wireless sensor networks due to the nodes having a finite and exhaustible source of energy. Due to the nodes limited energy, it is vital to have the node functioning for as long as possible otherwise it will render the technology futile. Transmission is the most energy consuming activity a node undertakes, therefore by decreasing the number of unnecessary transmissions, the energy consumption in the nodes decreases significantly. In order to reduce unnecessary transmissions, energy-efficient data dissemination techniques have been developed to deliver the data using the minimum number of necessary transmissions. The topic of this thesis is to develop a routing protocol that will extend the network lifetime by introducing cognition to routing. Cognitive routing is an approach to make nodes more intelligent by utilizing information from the lower layers and network in order to make more informant decisions. Data from the physical layer can relay important information about the state of the node, its neighbors, and the surrounding environment hence enabling the node to make energy-efficient and aware decisions. The routing protocol formulates an energy profile, a channel profile and a traffic profile in order to make adapted and intelligent decisions. Diversity routing is used to increase the reliability of transmissions in the network to reduce unnecessary transmissions as communication is the primary reason for energy consumption in wireless sensor networks. Combining these two approaches in one protocol allows for cognitive routing to operate based on energy constraints obtained from the lower levels hence optimizing the process yielding a longer network lifetime.
    URI for this record
    http://hdl.handle.net/1974/5988
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    • Queen's Graduate Theses and Dissertations
    • Department of Electrical and Computer Engineering Graduate Theses
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