Presenters: Puneet Gupta Sol Lederer

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Mobile Assisted Localization in Wireless Sensor Networks N.B. Priyantha, H. Balakrishnan, E.D. Demaine, S. Teller MIT Computer Science Presenters: Puneet Gupta Sol Lederer

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Mobile Assisted Localization in Wireless Sensor Networks N.B. Priyantha, H. Balakrishnan, E.D. Demaine, S. Teller MIT Computer Science. Presenters: Puneet Gupta Sol Lederer. Case for Mobile Assisted Localization. Obstructions, especially in indoor environments Sparse node deployments - PowerPoint PPT Presentation

Transcript of Presenters: Puneet Gupta Sol Lederer

Page 1: Presenters: Puneet Gupta Sol Lederer

Mobile Assisted Localization in Wireless Sensor Networks

N.B. Priyantha, H. Balakrishnan, E.D. Demaine, S. TellerMIT Computer Science

Presenters:

Puneet Gupta

Sol Lederer

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Case for Mobile Assisted Localization

Obstructions, especially in indoor environments

Sparse node deployments Geometric dilution of precision (GDOP)

Hence, finding 4 reference points for each node for localization is difficult

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Overview of scheme

Initially no nodes know their location Mobile node finds cluster of nearby

nodes Explores “visibility region” and

measures distance # of measurements required is linear

in the # of nodes Virtual nodes are discarded

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Theorem 1

A graph is globally rigid if it is formed by starting from a clique of 4 non-coplanar nodes and repeatedly adding a node connected to at least 4 nodes.

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MAL: Distance Measurement

First case: Two nodes, n0 and n1 , single unknown ||n0 - n1||

Adding mobile node, m, introduces 3 unknowns (mx, my, mz), making problem more difficult

Necessary condition: # deg of freedom (unknowns – knowns) ≤ 0.

Solution: Use three mobile locations along the same line in a plane containing n0 and n1

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Case of 2 nodes solved 6 constraints from

measurements of ||ni – mj|| for I = 0,1 and j = 0,1,2

Extra constraint obtained from colinearity of mobile points

unknowns – knowns = 0 Solve system of

polynomial equations

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Case of 3 nodes

Three nodes, n0 n1 n2, three unknowns, ||n0 - n1|| ||n1 - n2|| ||n0 - n2||

Each mobile position gives #unknowns (mx, my, mz) = 3 #constraints (||m – ni||, i = 0,1,2) = 3

Three additional constraints needed

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Case of 3 nodes Solution

Restriction: All mobile positions lie in a common plane k mobile locations k-3 additional co-

planarity constraints Solution: k = 6, geometry of n0, n1, n2

above the plane containing 6 coplanar points m0, m1, m2, m3, m4, m5 no three of which are collinear, determined by the distances ||mi - nj||, i = 0…5 & j = 0...2

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Case of 4 or More

Number of nodes = j ≥ 4 Initially: Number of unknowns = (3j – 5)

3 coordinates per node Minus 3 deg of translational motion Minus 2 deg of rotational motion

Each mobile node adds (j – 3) deg of freedom (j distances – 3 coordinates of mobile position)

j – 3 >= 1

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Case of 4 or more Solution

Require at least (3j – 5)/(j – 3) mobile positions

E.g. for j = 4, required mobile positions to uniquely determine the geometry = 7

But, no 4 of the 11 nodes (4 + 7) may be coplanar

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MAL: Movement Strategy

Initialize: Find 4 nodes that can all be seen from a common

location Move the mobile to 7 nearby locations & measure

distances Compute pair-wise distances

Loop: Pick a localized stationary node (not yet considered by

this loop) Move mobile in perimeter of this node, searching for

positions to hear a non-localized node Localize this node

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AFL: Anchor-free localization

Elect five nodes as shown

Get crude coordinates based on hop count to anchors

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AFL

Use non-linear optimization algorithm to minimize sum-squared energy E

Coordinate assignments satisfy all 1-hop node distances when E = 0

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Graph from running AFL—using RF connectivity information

Graph obtained by MAL

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Performance

Layout of nodes in test scenario

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Estimate error

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Critique

Pros: Innovative stategy

Cons: In a cumbersome terrain (e.g. forest) it

may not be feasible to deploy a roving node.

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The End