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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/11342
Title: Opportunistic Vehicular Assisted Ferrying in Energy Efficient Wireless Mesh Networks
Authors: Rezaei, Moghadam Keyvan
Advisor: Todd, Terence D.
Zhao, Dongmei
Department: Electrical and Computer Engineering
Keywords: Wireless Mesh Networks (WMNs);Delay Tolerant Networks (DTNs);Routing;Energy efficiency;Mobility;WSNs;Electrical and Electronics;Electrical and Electronics
Publication Date: Oct-2011
Abstract: <p>Wireless mesh networks are widely used for various communication purposes and are often deployed in a broad range of outdoor applications. In cases where the deployment area is outside the reach of fixed infrastructure, energy efficient operation of the mesh nodes is very important. Many approaches have been explored to find energy efficient network solutions for these types of scenarios. This thesisproposes power saving mechanisms where the mesh network nodes opportunistically access coexistent vehicular networks. This is referred to as Opportunistic Vehicle Assisted Ferrying (OVAF). The history of using moving particles for message carrying can be found in research on intermittently connected networks. However, this approachhas never been considered with fully connected networks. Two different models are presented to model the OVAFmechanism: \textbf{a}. \emph{A flow based model}, and \textbf{b}. \emph{Apacket based model}. For each model an analytic lower bound isobtained by formulating a linear integer optimization with differentcost functions. Heuristics, which simplify the complexity of theproblem, are then developed for eachmodel. Arriving vehicles and generated packets are also modeled asrandom processes under various scenarios using different parameters.Results are presented which demonstrate the superiority of the OVAFrouting method compared to conventional multihop forwarding (Up to $60\%$increase in energy saving).</p>
URI: http://hdl.handle.net/11375/11342
Identifier: opendissertations/6316
7364
2262195
Appears in Collections:Open Access Dissertations and Theses

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