Routing With Node Mobility in Wireless Networks
Introduction
Mobile wireless networks help us produce and consume information
anytime and anywhere. In ad hoc mobile wireless networks, due to the
lack of communication infrastructure, the problem of information
delivery becomes harder. In this project, we try to understand the
properties and performance limits of mobile ad hoc networks. We also
leverage stable properties of these mobile networks to design
efficient information delivery algorithms.
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Understanding the Performance of Mobile Networks
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We try to estimate the maximum achievable performance of a mobile
wirelss network. Analysis of mobile networks is challenging because
such analysis must take into account the link volatility caused by
network dynamics as well as node mobility. Although a network is
partitioned at a given time instant, the routing might still be
feasible if we consider a time interval. We build on prior work on
time-expanded graphs and apply it to the analysis of mobile ad hoc
networks. We also reduce the number of nodes in the time expanded
graph, and hence space complexity of the analysis, by pruning the
nodes that remain static over multiple intervals. We were able to
scale the performance analysis to hundreds of nodes.
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Predictive Routing to Mobile Sinks
If the mobility of the mobile sink has some structure to it or is
predictable to some extent, we can exploit the knowledge about the
trajectory to perform predictive routing. We can route data, not to
the sink directly, but to the relay nodes along the predicted path of
the mobile node. The data remain stashed on those nodes until the
mobile node passes by and picks up the data. We use linear programming
to find the choice of stashing nodes that minimizes the communication
overhead while guaranteeing robustness against link and node failures,
as well as trajectory uncertainty. We found that this technique
achieves data delivery efficiency comparable to what is possible with
perfect knowledge about future trajectory of the mobile node.
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Hierarchical Routing Robust to Sink Mobility
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To make information delivery to mobile sinks efficient, our strategy
is to select, in a distributed manner, a set of well-placed nodes
(warehouses) to act as intermediaries between the information sources
and clusters of nearby users. Warehouses are selected via the
distributed construction of hierarchical well-separated trees (HSTs),
which are sparse structures that induce a natural spatial clustering
of the network. These trees are agnostic to the number and position of
sources as well as to the mobility patterns of users. Our sparse and
flexible infrastructure is precomputed and efficiently reused by
sources and users, its cost amortized over time. Our algorithm ensures
with high probability a guaranteed stretch bound for the information
delivery path, and is robust to lossy links and node failure by
providing alternative HST-induced routes. Nearby users are clustered
and their requests aggregated, further reducing communication
overhead.
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Publications
Arik Motskin, Ian Downes, Branislav Kusy, Omprakash Gnawali, and
Leonidas Guibas, Network Warehouses: Efficient Information
Distribution to Mobile Users, To appear in proceedings of the 30th
IEEE International Conference on Computer Communications (INFOCOM
2011), April 2011. Acceptance Rate - 291/1823 (15.9%) |
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Ian Downes, Branislav Kusy, Omprakash Gnawali, and
Leonidas Guibas, Interactive Analysis
and Simulation of VANETs Using MOWINE, To appear in
proceedings of the IEEE Vehicular Networking Conference (VNC 2010),
December 2010. |
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HyungJune Lee, Martin Wicke, Branislav Kusy, Omprakash
Gnawali, and Leonidas
Guibas, Data
Stashing: Energy-efficient Information Delivery to Mobile Sinks
through Trajectory Prediction, In Proceedings of the ACM/IEEE
International Conference on Information Processing in Sensor Networks
(IPSN 2010), Stockholm, Sweden, April 12-16, 2010. Acceptance Rate -
20/117 (17.1%) |
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