topological hole detection ritesh maheshwari cse 590
TRANSCRIPT
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Topological Hole Detection
Ritesh Maheshwari
CSE 590
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Paper
S. Funke, “Topological Hole Detection and its Applications”, DIALM-POMC, 2005.
Basically, aim is to identify which nodes form the boundary, outer or inner (of holes), in a wireless sensor network
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Motivation
Imagine a remote nature preserveLong summer drought, resulting inWildfires!Airplanes dropping thousands of cheap
sensor nodes, so that the sensor network: Organizes itself, routes messages Identifies current firefront Answers Queries efficiently
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Motivation
Imagine a remote nature preserveLong summer drought, resulting inWildfires!Airplanes dropping thousands of cheap
sensor nodes, so that the sensor network Organizes itself, routes messages Identifies current firefront => Hole Detection! Answers Queries efficiently
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Other Uses
Provide topology information to Location unaware protocols like GLIDER
Help in Landmark selection for GLIDER
Better Virtual coordinates in absence of Location Information
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Assumptions
Region REvery point in R is covered for sensing by
atleast one sensor Usually comm range larger than sensing range
Unit Disk GraphNo location informationOnly connectivity information available
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The continuous case
A beacon pointConstruct contours of
Euclidean distance from beacon
Observation: contours usually break at boundary
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Discrete Case
No ‘points’ – only sensor nodes
No ‘distance’ measurement – only hop-count
Connected Components of same hop-count from beacon form contours
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Discrete Case
Beacon – node pdp(v) is hop-count from p to node v
I(k) = { v : dp(v) = k} is isoset of level k
I(k) may be disconnected, so resulting connected components are called C1(k), C2(k), C3(k)…..
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Discrete Case
Boundary nodes are now the end nodes of the Connected Components - C1(k), C2(k) etc
Pick random node r in Ci(k) and find nodes in Ci(k) with highest hop-count from r
Usually, one beacon is not enough. They use 4
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Algorithms
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Beacon Selection
The 4 beacons should be as far away as possible
Choose 1st beacon randomlyOther 3 chosen on the basis of their
distance from the 1st beacon
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Distributed Implementation
Topology exploration done only rarely
Thus naïve implementation suits
Can be done by Flooding a constant number of times
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Application: Landmark Selection in GLIDER
Landmarks divide the network into tiles using Voronoi diagrams
Local coordinate system constructed within each tile
When p in tilep wants to send packet to q in tileq, Inter-tile: Packet is routed to a neighboring tile which is
nearer to tileq than tilep and so on
Intra-tile: When reaching tileq, local coordinate system used to route to q
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Problems of unaware Landmark-Selection
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Problems of unaware Landmark-Selection
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Solution: First Attempt
Observation: If 2 landmarks are on same hole boundary, then the hole cannot be totally inside one tile
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Solution: Second Attempt
Hole Repulsion and Pruning
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More Applications
To find Virtual Coordinates in presence of holes
Medial-Axis-Based Routing
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Evaluation: UDG - random
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Evaluation: UDG - grid
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Evaluation: Non-UDG
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Conclusion
Simple protocolOnly Connectivity info requiredHole detection => Event detection
But useful only for dense networksNot that bad, as they assume cheap
sensors
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Thank You!