ASWP – Ad-hoc Routing with Interference Consideration June 28, 2005.
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Transcript of ASWP – Ad-hoc Routing with Interference Consideration June 28, 2005.
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ASWP – Ad-hoc Routing with Interference Consideration
June 28, 2005
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Scenarios Deploy troops into field Goals
QoS Traffic classes, flow requirements
Scalable Difficulty
Interference
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Outline Problem description
Interference model Possible solutions
Ad-hoc shortest widest path ASWP problem Proposed algorithm
Simulations Conclusion
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Interference is critical Wired networks
Independent links Ad-hoc networks
Neighbor links interfere Interference range >
Transmission range For simulations
Tx range = 500 m Ix range = 1 km
InterferenceRange
TransmissionRange
Node A
Node D
Node C
Node B
Link 2
Link 1
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Interference Model Conflict graph
G(X,A ) CG(A,I ) Undirected graph
Violate Bellman’s Principle of Optimality
Clique Constraint • Node 13: path A (c)• Node 15: path A-D-E (c/3)
path B-C-D-E (c/2)
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Routing solutions CG-based methods
Ideal solution Clique constraint Row constraint
Two-hops interference model AQOR
MAC scheduling SEEDEX, TDM/CDM
Connectivity only DSR, AODV
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Outline Problem description
Interference model Possible solutions
Ad-hoc shortest widest path ASWP problem Proposed algorithm
Simulations Conclusion
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Ad-Hoc Shortest Widest Path Path metrics
Width Length
Shortest widest path between (s,d ) Want to find the widest path; If more than one, take the shortest.
NP-complete
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ASWP Design Separate scheduling and routing
Finding the widest path Distributed algorithm
Clique computation Path computation
Minimize overhead Localized cliques
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ASWP Heuristic Bellman approach Key step
Compute path width for one-hop extension Bottleneck clique
Unchanged A maximal clique that the extending link belongs
to Can be done locally
K-shortest-path approach
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Outline Problem description
Interference model Possible solutions
Ad-hoc shortest widest path ASWP problem Proposed algorithm
Simulations Conclusion
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Simulations – path width
50-node network Distant s/d pair
7 hops away X axis: load =
average clique utilization
Y axis: path width
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Simulations – path width
50-node network Load = 0.32 All pairs performance X axis: distance
between s/d pair Y axis (upper): ratio
of improved s/d pair Y axis (lower):
average improvement
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Simulations – admission ratio
50-node network Dynamic simulation 5 s/d pairs
Randomly chosen Given distance
Traffic model Flow requests: 4Kb/s, 10,000 flow requests Incoming rate: 0.32 flows per second Duration: uniform distribution between 400 and 2800
seconds Load = 0.32(400+2800)/24 = 2048 Kb/s = 2 Mb/s
Results: admission ratio (%)
distance
SP ASWP 2ASWP
4ASWP
2 hops 99.4 100 100 100
4 hops 47.9 54.8 54.8 54.7
7 hops 31.8 44.1 43.4 43.9
Mixed 66.5 71.4 71.0 70.9
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More on ASWP Optimal path = shortest widest path Complexity
Polynomial, but … Running time (sec):
Optimal SWP necessary? Wide path = long path Long term behavior: bad
SP ASWP 2ASWP
4ASWP
5.3 27.9 50.4 80.0
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Outline Problem description
Interference model Possible solutions
Ad-hoc shortest widest path ASWP problem Proposed algorithm
Simulations Conclusion
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Conclusion Overall goals
Bandwidth guaranteed path Long-term admission ratio
Interference model Conflict constraints
ASWP solution Find shortest widest path Distributed algorithm
Bellman-Ford architecture + k-shortest-path approach
A small k value is the good trade-off