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Analysis of a Cone-Based Distributed Topology Control Algorithm for Wireless Multi-hop Networks
L. Li, J. Y. Halpern Cornell University P. Bahl, Y. M. Wang, and R. Wattenhofer Microsoft Research, Redmond Presented by Lu-chuan Kung For CS598hou Sp2006 University of Illinois at Urbana-Champaign
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Outline Motivation Bigger Picture and Related Work
Basic Cone-Based Algorithm Summary of Two Main Results Properties of the Basic Algorithm Optimizations Properties of Asymmetric Edge Removal Performance Evaluation
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Motivation for Topology Control
Example of No Topology Control with maximum transmission radius R (maximum connected node set) High energy consumption High interference Low throughput
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Example of No Topology Control with Smaller Transmission Radius
Network may partition
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Example of Topology Control
Global connectivity Low energy consumption Low interference High throughput
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Basic Cone-Based Algorithm
Assumption: receiver can determine the direction of sender Directional antenna community: Angle of Arrival problem Each node u broadcasts “Hello” with increasing power (radius) Each discovered neighbor v replies with “Ack”. Each node u increases power until each cone of degree αcontains a node, or u transmits with maximum power Who should be my neighbor in the graph? What is my transmission power?
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Notation E = { (u,v) V x V: v is a discovered neighbor by node u}
G = (V, E) E may not be symmetric (B,A) in E but (A,B) not in E
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Notation: Two Symmetric Sets
E+ = { (u,v): (u,v) E or (v,u) E } Symmetric closure of E G+ = (V, E+ ) E- = { (u,v): (u,v) E and (v,u) E } Asymmetric edge removal G- = (V, E- )
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Summary of Two Main Results
Let GR = (V, ER), ER = { (u,v): d(u,v) R } Connectivity Theorem If 150, then G+ preserves the connectivity of GR and the bound is tight. Asymmetric Edge Theorem If 120, then G- preserves the connectivity of GR and the bound is tight.
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Properties of the Basic Algorithm
Counter-example for =
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Counter-example for = 150 +
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Counter-example for = 150 +
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Connectivity Lemma For 150 ( 5/6 ) if d(A,B) = d R and (A,B) E+, there must be a pair of nodes W,Y, one red and one green, with distance d(W,Y) less than d(A,B).
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Connectivity Lemma Sketch of Proof
B A z z is in Nα(B) with minimal Angle(z,B,A) Case 1: Angle(z,B,A) < 60° Then d(A,z) < d(A,B), therefore the Lemma holds ( W=A, Y=z )
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B A z y w x Case 2: Angle(z,B,A) > 60° Must exist y such that Angle(z,B,y) <= α Similarly there exists w and x st Angle(w,A,x) <= α Then either d(w,z) < d(A,B) or d(x,y) < d(A,B) Q.E.D
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Connectivity Theorem Order the edges in ER by length and induction on the rank in the ordering For every edge in ER, there’s a corresponding path in G+ . If 150, then G+ preserves the connectivity of GR and the bound is tight.
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Optimizations Shrink-back operation Asymmetric edge removal
“Boundary nodes” can shrink radius as long as not reducing cone coverage Asymmetric edge removal If 120, remove all asymmetric edges Pairwise edge removal If < 60, remove longer edge e2 B e1 A e2 C
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Properties of Asymmetric Edge Removal
Counterexample for =
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For 120 ( 2/3 ) Asymmetric Edge Lemma
if d(A,B) R and (A,B) E, there must be a pair of nodes, W or X and node B, with distance less than d(A,B).
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Asymmetric Edge Theorem
Two-step inductions on ER and then on E For every edge in ER , if it becomes an asymmetric edge in G , then there’s a corresponding path consisting of only symmetric edges. If 120, then G- preserves the connectivity of GR and the bound is tight.
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Performance Evaluation
Simulation Setup 100 nodes randomly placed on a 1500m-by-1500m grid. Each node has a maximum transmission radius 500m. Performance Metrics Average Radius Average Node Degree
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Average Radius
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Average Node Degree
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Comparison with Other TC
SMECN: small minimum-energy communication network (requires location information)
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Reconfiguration In response to mobility, failures, and node additions
Based on Neighbor Discovery Protocol (NDP) beacons Joinu(v) event: may allow shrink-back Leaveu(v) event: may resume “Hello” protocol AngleChangeu(v) event: may allow shrink-back or resume “Hello” protocol Careful selection of beacon power
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Summary Distributed cone-based topology control algorithm that achieves maximum connected node set If we treat all edges as bi-directional 150-degree tight upper bound If we remove all unidirectional edges 120-degree tight upper bound Simulation results show that average radius and node degree can be significantly reduced
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Comments The requirement to measure angle-of-arrival is not practical
CBTC doesn’t work better than distance-based topology control
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The Aladdin Home Networking System
Phoneline Ethernet LAN Powerline Network Home Gateway Wireless Sensor Network Alert Router IM
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Bigger Picture and Related Work
Routing Topology Control Selective Node Shutdown [Hu 1993] [Ramanathan & Rosales-Hain 2000] [Rodoplu & Meng 1999] [Wattenhofer et al. 2001] [GAF] [Span] MAC / Power-controlled MAC [MBH 01] [WTS 00] Relative Neighborhood Graphs, Gabriel graphs, Sphere-of-Influence graphs, -graphs, etc. Computational Geometry
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The Why-150 Lemma 150 =
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