Island Hopping:
Efficient Mobility-Assisted Forwarding
in Partitioned Networks
Natasa Sarafijanovic-Djukic
Michal Piorkowski
Matthias Grossglauser
EPFL, LCA
Mobility with Concentration Points
Our main assumptions:
heterogeneous spatial distribution
concentration points (CPs): node density
much higher than average
stable over time
Our main goal:
exploit CPs to help ad-hoc networking
routing in mobile partitioned networks
Justification of our assumptions:
real-life mobility traces
Michal Piorkowski – LCA, EPFL
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Exploiting Stable Concentration Points
Mobile partitioned networks
routing
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If it is possible for nodes:
to assign unique and stable
labels to CPs
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to know this labeled CP graph
to know at which vertex the
destination is
Then:
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routing could be done more
efficient
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Components of Our Routing Scheme
the set of
neighbors
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1.Collaborative Graph Discovery
CP graph
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2. Last Encounter Locating
destination location
3. Island Hopping
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routing decisions
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1. Collaborative Graph Discovery
(COGRAD)
Each node knows only the set of
neighbors:
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has no external information (such
as GPS, or fixed beacons)
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does not know if it moves or not
Labeling:
assign unique labels to CPs
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maintain the labels stable as long
as possible
Edge Discovery:
discover the labeled edges of the
CP graph
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Our Contributions
Mobility model with CPs
validation: taxi mobility traces
Routing scheme for mobile partitioned networks
COGRAD: discovering the CP graph
by observing only the set of the neighbors
Last Encounter Routing: locating nodes
Island Hopping: mobility-assisted forwarding that exploits knowledge of
CP graph
destination location
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