The Role of Controlled Mobility in Wireless Networksmorse.colorado.edu/~timxb/0803China.pdf · – Environmental Engineering – Interdisciplinary Telecommunications ... – Wireless

1

The Role of Controlled Mobility The Role of Controlled Mobility

in Wireless Networksin Wireless Networks

Timothy X Brown

Interdisciplinary Telecommunications

Electrical and Computer Engineering

Pervasive Communications Lab

Research and Engineering Center in Unmanned Vehicles

University of Colorado, Boulder

March 5, 2008

5/3/2008 http://http://ece.colorado.edu/~timxbece.colorado.edu/~timxb 2

• Three Nobel Prize winners in the past five

years, Four in total

• Ranked as World’s No. 11th best public

university, 34th overall by The Economists

and SJTU

• National Academy of Engineering’s top

educational honor, Gordon Prize, 2004 and

2008.

• 21 members of the National Academy of

Sciences; 12 members of the National

Academy of Engineering (4 in ECE)

• CU is one of the 17 participating universities of the program by China Scholarship Council, accepting exchange students

• College of Engineering

– Aerospace Engineering

– Chemical and Biological Engineering

– Civil Engineering

– Computer Science

– Electrical and Computer Engineering:

– Environmental Engineering

– Interdisciplinary Telecommunications Program

– Mechanical Engineering

University of Colorado, BoulderUniversity of Colorado, Boulder

2

5/3/2008 http://http://ece.colorado.edu/~timxbece.colorado.edu/~timxb 3

• Chair: Prof. Michael Lightner,

IEEE President

• $6M Annual Research

Expenditures

• 3 in 4 Graduate Students have Aide

• Research Areas:

– Biomedical Engineering

– Computer Engineering

– Communications and Signal Processing

– Dynamics, Robotics, and Controls

– Electromagnetics, RF, and Antennas

– Optics & Photonics

– Power Electronics and Renewable

Energy

– Solid State Materials and Devices

– VLSI/CAD

Department of Electrical and Department of Electrical and

Computer Computer EngnieeringEngnieering

5/3/2008 http://http://ece.colorado.edu/~timxbece.colorado.edu/~timxb

• Masters Program that integrates all aspects of networking

– technical

– policy

– business

• Students work closely with industry and public policy experts.

• State-of-the art network laboratory

• 100% of students find jobs within 6 months of graduating

• Multilayer study of– Internet

– Telephony

– Wireless Networking

– Network security

Interdisciplinary Telecommunications Interdisciplinary Telecommunications

ProgramProgram

3

The Role of Controlled Mobility The Role of Controlled Mobility

in Wireless Networksin Wireless Networks


Thanks to Thanks to

• Dan Henkel

• Cory Dixon

• Andrew Jenkins

• Yikun Zhang

• Eric Frew

• Brian Argrow

4


Basic InsightBasic Insight

A problem in:

Cellular

Ad hoc networks

Exploited in:

Epidemic routing

Ad hoc capacity

Mobility is

Mobility separate

from network

Delay

sensitive

traffic

Delay

tolerant

traffic

Mobility controlled

by network

How can we

control mobility?

What are the delay

and throughput tradeoffs?

What are the limits?


OutlineOutline

• Motivating problem

• Communication Modes

• Extensions

• Practical Issues

• Conclusions

5


AUGNetAUGNet

241cm

Ad hoc UAV Ground Network

Group 1

Group 2

16cm

Delay sensitive traffic.


Sensor Data CollectionSensor Data Collection

Sparsely distributed sensors

Limited radio range, power

Sensor-1

Sensor-2

Sensor-3

SMS-1

Delay tolerant traffic.

6


Research GoalResearch Goal

GS1

UAV1

UAV3

UAV2

GS2

Using node mobility control to enhancenetwork performance

DirectRelayFerrying


Problem CharacteristicsProblem Characteristics

• Focused on a single link:

• Interaction between– Separation, d

– Required rate, R

– Limit on delay, T

• Store and Forward– No cooperative relaying

– No network coding

• Task vs. Helper nodes

A Bd

R, T

7


Communication ModesCommunication Modes

A B Direct

A B Relay

A B Ferry

What determines the mode?


Rate vs. Distance FunctionRate vs. Distance Function

• Shannon Capacity

W = channel BW

α = radio parameters

ε = pathloss exponent

≈ reality

Rate vs. RangeRate vs. Range

Distance

Ra

te R

D(d

)

Disc

802.11g

Shannon C

apacity

( )

+⋅=

ε

α

dWdRD 1log2

8


Throughput and DelayThroughput and Delay

Delay, T

(for length L packet)Data Rate, RRD(d)= W log2(1 + K/dε)

2b/(RD(d/2) + vb/d)≈ ½(RD(d/2) + vb/d)Ferry

2 L /RD(d/2)½ RD(d/2)Relay

L/ RD(d)RD(d)Direct

A B

A B

A B

W = bandwidth

K = communication constant

ε = pathloss exponent

d

d

d

v = ferry velocity

b = ferry buffer size


What Determines the Mode?What Determines the Mode?

• Take 1:

– Choose mode with lowest delay that meets data rate

requirement

distance[m]

da

ta r

ate

[b

ps]

101

102

103

104

105

106

100

102

104

106

108

Direct Ferry

Unachievable

Relay

9


What Determines the Mode?What Determines the Mode?

• Take 2:

The “simplest”

mode that

achieves the

desired

throughput-

delay

requirement


ExtensionsExtensions

• Point to multipoint

• Multiple Relays

10


PointPoint--toto--multipointmultipoint

• Ferry can form virtual access point.

How often should ferry visit each node?

– Function of traffic flow fi and distance, di

– minimize weighted delay if ∝ √fi/di

A

C

B

H


TSP routing finds an optimal “tour” between nodes

Visits each node in tour in turn

In 3-node linear layout, only one tour

Our approach visits nodes based on f and d

PointPoint--toto--point vs. point vs. ““TSP routingTSP routing””

0 0.2 0.4 0.6 0.8 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

hub separation from A as fraction of total distance A−B [%]

op

tim

al d

ela

y a

s f

ractio

n o

f n

aiv

e d

ela

y [

%]

fA=1 fB

fA=3 fB

fA=10 fB

fA=30 fB

fA=100 fB

A BH

Example where

TSP is 100x

worse

11


Ferry Path Planning ResultsFerry Path Planning Results

• TSP = Traveling Salesman solution

• RL = Reinforcement Learning

Reinforcement learning solution beats competing methods.

I II III IV

rela

tive g

ain

[%

]

A

C

B AC

B

AC

B

A

C

B

D

E

D

0

40

50

20

D

TSP

RL

RR

STO 37

46

23

TSP

RL

RR

STO 23

33

7

8 packets/sec1 packet/sec

RL

STO 17

34

TSPRR 1

RL

RR

STO 13

2422TSP

RL

TSP

10

30

ACB. ADCB. ADCB. ACEDB.

A.B.B.CB. EDB.EDB.EDB._BC.A.BC.A.CB.A._ A.CB.A.DCB.

CB.DA.

:

:

EDB.ECA.

• RR = Round Robin (naive)

• STO = Stochastic Modeling


Multiple RelaysMultiple Relays

S D

d

dk

End-to-end data rate: RR

Packet delay: τ = L/RR

Direct transmission(zero relays)

Relay transmission

12


““Single Single TxTx”” Relay ModelRelay Model

a.k.a., the noise-limited case

++=

11

1

k

dR

kR DRS

+

+=

1

)1(

k

dR

Lk

D

RSτ

S Ddk

t=0


““Parallel Parallel TxTx”” Relay ModelRelay Model

a.k.a., the interference limited case> Optimal distance between transmissions?

{ }

+= ),,(

,1min

1max ρ

ρρkdR

kR IRP

)1(log2

NI

SI

PP

PWR

++=∑

−+

+

+=

i

Iiid

kP

εε

ε

ρρβ

)1(

1

)1(

1)

1(

S Dρ

t=0 t=0 t=0

13


Performance AnalysisPerformance Analysis

100

101

102

103

1

2

3

4

5x 10

6

# of relays

Th

rou

gh

pu

t [b

ps]

100

101

102

103

1

2

3

4

5x 10

6

# of relays

Th

rou

gh

pu

t [b

ps]

100

101

102

103

1

2

3

4

5x 10

6

# of relays

Th

rou

gh

pu

t [b

ps]

100

101

102

103

1

2

3

4

5x 10

6

# of relays

Th

rou

gh

pu

t [b

ps]

Parallel Tx

Single Tx

Direct Tx

d=2km d=4km d=8km d=16km

2km 4km 8km 16km

ε = 5 PN/α = 10-15W


Optimizing Optimizing ““Single Single TxTx””

• Optimal # of relays:

⇒ optimal relay distance

=

),( εαopt

optd

dk

Throughput vs. # of relays

14


RRRPRP for Small Path Lossfor Small Path Loss


Data Rate and Path LossData Rate and Path Loss

kopt finite kopt = ∞

15


εε -- d Phase Transitiond Phase Transition

kopt finite

kopt = ∞


Optimal Reuse Factor Optimal Reuse Factor ρρ

d=10km PN/α = 4.14·10-15 (based on 802.11)

k+1ρopt

5555565422

5555555423

5555544324

5554332225

5543222226

∞256128643216842ε

ρopt ≈ min{k+1, 5}

16


RateRate--Distance Phase PlotDistance Phase Plot


Core ConceptCore Concept

• Fundamentally, we are talking about a new

shared media.

– Very long distances

– Long delays

– Familiar metrics (delay, rate, …)

17


Practical IssuesPractical Issues

• How do helpers find the relay point?

• What network protocols are needed to support

ferrying?


Finding the relay point Finding the relay point

MaximizeMaximize--Minimum SNRMinimum SNR

• Re-cast Control Problem– Control motion of an orbit center point

– Autopilot system tracks orbit point

• Gradient Estimates for Each Link

• Feedback ForceMove the point mass by generating forces

based on link gradient.

• Scaling Parameter Ki

])[][(][ kxkSkgGorbitkorbitk

ii

vvv∆⋅∆== ∑∑

∈∈

m

vCFa o

vvr −

=

iii GKfvv

⋅= ∑∈

=linksi

ifFvv

=

=else0

)min(arg if1 ii

SiK

a=F/m

Pos

Ad Hoc Network

R

R R

R

RR

R

R

F(Si)

Orbit Point

sensorF +

18


Two Helpers with NoiseTwo Helpers with Noise


New ProtocolsNew Protocols

• Application:

– Disruption Tolerant File Transfer

• Network:

– Service discovery

– Routing

• Link:

– Reliable Packet Forwarding

• MAC

– Rate discovery protocols

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ConclusionsConclusions

• Controlled mobility improves network performance

• Enables a new kind of shared media

• Spurs new thinking on communication

• Demonstration on Colorado Test Bed

The EndThe End

[email protected]

http://recuv.colorado.edu/

Documents

The Role of Controlled Mobility in Wireless Networksmorse.colorado.edu/~timxb/0803China.pdf · – Environmental Engineering – Interdisciplinary Telecommunications ... – Wireless