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    Lifenet: a flexible ad hoc networking solution for transient environments

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    mehendale_hrushikesh_sanjay_201112_MS.pdf (1.186Mb)
    Date
    2011-11-18
    Author
    Mehendale, Hrushikesh Sanjay
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    Abstract
    In the wake of major disasters, the failure of existing communications infrastructure and the subsequent lack of an effective communication solution results in increased risks, inefficiencies, damage and casualties. Currently available options such as satellite communication are expensive and have limited functionality. A robust communication solution should be affordable, easy to deploy, require little infrastructure, consume little power and facilitate Internet access. Researchers have long proposed the use of ad hoc wireless networks for such scenarios. However such networks have so far failed to create any impact, primarily because they are unable to handle network transience and have usability constraints such as static topologies and dependence on specific platforms. LifeNet is a WiFi-based ad hoc data communication solution designed for use in highly transient environments. After presenting the motivation, design principles and key insights from prior literature, the dissertation introduces a new routing metric called Reachability and a new routing protocol based on it, called Flexible Routing. Roughly speaking, reachability measures the end-to-end multi-path probability that a packet transmitted by a source reaches its final destination. Using experimental results, it is shown that even with high transience, the reachability metric - (1) accurately captures the effects of transience (2) provides a compact and eventually consistent global network view at individual nodes, (3) is easy to calculate and maintain and (4) captures availability. Flexible Routing trades throughput for availability and fault-tolerance and ensures successful packet delivery under varying degrees of transience. With the intent of deploying LifeNet on field we have been continuously interacting with field partners, one of which is Tata Institute of Social Sciences India. We have refined LifeNet iteratively refined base on their feedback. I conclude the thesis with lessons learned from our field trips so far and deployment plans for the near future.
    URI
    http://hdl.handle.net/1853/42781
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    • College of Computing Theses and Dissertations [1156]
    • Georgia Tech Theses and Dissertations [23403]

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