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Topological Hole Detection

Date post: 17-Jan-2016
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Topological Hole Detection. Ritesh Maheshwari CSE 590. 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. Motivation. - PowerPoint PPT Presentation
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Topological Hole Detection Ritesh Maheshwari CSE 590
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Page 1: Topological Hole Detection

Topological Hole Detection

Ritesh Maheshwari

CSE 590

Page 2: Topological Hole Detection

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

Page 3: Topological Hole Detection

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

Page 4: Topological Hole Detection

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!


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