Studying the effect of human mobility onMANET topology and routing: friend or foe?

Authors:Adan G. Medrano-Chavez∗

Elizabeth Perez-CortesMiguel Lopez-Guerrero

Department of Electrical Engineering∗Graduate school of Science and Information Technologies

MOBIWac 2015 Cancun - Mexico, Nov 2–6

MANET context Research question Experimental methodology Results Conclusion

Presentation outline

1 MANET context

2 Research question

3 Experimental methodology

4 Results

5 Conclusion

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MANET context Research question Experimental methodology Results Conclusion

MANET paradigm

Collection of mobile terminals that establish a networkinfrastructure on-demand and in a self-organized manner

MANET features

There’s no fixedcommunicationinfrastructure

There’s no centralizedmanagement

Terminals act as hosts androuters

Support for distributedapplications

3/25

MANET context Research question Experimental methodology Results Conclusion

MANET paradigm

Collection of mobile terminals that establish a networkinfrastructure on-demand and in a self-organized manner

MANET features

There’s no fixedcommunicationinfrastructure

There’s no centralizedmanagement

Terminals act as hosts androuters

Support for distributedapplications

3/25

MANET context Research question Experimental methodology Results Conclusion

MANET paradigm

Collection of mobile terminals that establish a networkinfrastructure on-demand and in a self-organized manner

MANET features

There’s no fixedcommunicationinfrastructure

There’s no centralizedmanagement

Terminals act as hosts androuters

Support for distributedapplications

3/25

MANET context Research question Experimental methodology Results Conclusion

MANET paradigm

Collection of mobile terminals that establish a networkinfrastructure on-demand and in a self-organized manner

MANET features

There’s no fixedcommunicationinfrastructure

There’s no centralizedmanagement

Terminals act as hosts androuters

Support for distributedapplications

3/25

MANET context Research question Experimental methodology Results Conclusion

MANET paradigm

Collection of mobile terminals that establish a networkinfrastructure on-demand and in a self-organized manner

MANET features

There’s no fixedcommunicationinfrastructure

There’s no centralizedmanagement

Terminals act as hosts androuters

Support for distributedapplications

3/25

MANET context Research question Experimental methodology Results Conclusion

Why is the design of MANET protocols hard?

MANET challenges

Low per-node capacity

Dynamical topology Per

-no

de

cap

acit

yNetwork size

Θ(1/sqrt(n*log(n)))

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MANET context Research question Experimental methodology Results Conclusion

Why is the design of MANET protocols hard?

MANET challenges

Low per-node capacity

Dynamical topology

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MANET context Research question Experimental methodology Results Conclusion

Why is the design of MANET protocols hard?

MANET challenges

Low per-node capacity

Dynamical topology

4/25

MANET context Research question Experimental methodology Results Conclusion

What’s the problem with node motion?

It invalidates routes established by routing protocols

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MANET context Research question Experimental methodology Results Conclusion

How is node motion?

We know . . .

MANETs are integrated byportable devices

Humans carry such devices

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MANET context Research question Experimental methodology Results Conclusion

How is node motion?

We know . . .

MANETs are integrated byportable devices

Humans carry such devices

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MANET context Research question Experimental methodology Results Conclusion

How is human motion?

Features

1 Humans mainly move withinconfined areas1

2 Humans are attracted to popularareas2

3 Pause time is well-modeled byheavy-tailed distributions3

4 Flight lengths are also modeled byheavy-tailed distributions4

5 Speed is normally distributed5

1Gonzalez, et al. “Understanding individual human mobility patterns”, Nature, 20082Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 20123Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20114Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20115Chandra, et al. “Speed Distribution Curves for Pedestrians During Walking and Crossing”, Procedia, 2013

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MANET context Research question Experimental methodology Results Conclusion

How is human motion?

Features

1 Humans mainly move withinconfined areas1

2 Humans are attracted to popularareas2

3 Pause time is well-modeled byheavy-tailed distributions3

4 Flight lengths are also modeled byheavy-tailed distributions4

5 Speed is normally distributed5

1Gonzalez, et al. “Understanding individual human mobility patterns”, Nature, 20082Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 20123Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20114Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20115Chandra, et al. “Speed Distribution Curves for Pedestrians During Walking and Crossing”, Procedia, 2013

7/25

MANET context Research question Experimental methodology Results Conclusion

How is human motion?

Features

1 Humans mainly move withinconfined areas1

2 Humans are attracted to popularareas2

3 Pause time is well-modeled byheavy-tailed distributions3

4 Flight lengths are also modeled byheavy-tailed distributions4

5 Speed is normally distributed5

1Gonzalez, et al. “Understanding individual human mobility patterns”, Nature, 20082Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 20123Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20114Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20115Chandra, et al. “Speed Distribution Curves for Pedestrians During Walking and Crossing”, Procedia, 2013

7/25

MANET context Research question Experimental methodology Results Conclusion

How is human motion?

Features

1 Humans mainly move withinconfined areas1

2 Humans are attracted to popularareas2

3 Pause time is well-modeled byheavy-tailed distributions3

4 Flight lengths are also modeled byheavy-tailed distributions4

5 Speed is normally distributed5

1Gonzalez, et al. “Understanding individual human mobility patterns”, Nature, 20082Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 20123Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20114Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20115Chandra, et al. “Speed Distribution Curves for Pedestrians During Walking and Crossing”, Procedia, 2013

7/25

MANET context Research question Experimental methodology Results Conclusion

How is human motion?

Features

1 Humans mainly move withinconfined areas1

2 Humans are attracted to popularareas2

3 Pause time is well-modeled byheavy-tailed distributions3

4 Flight lengths are also modeled byheavy-tailed distributions4

5 Speed is normally distributed5

1Gonzalez, et al. “Understanding individual human mobility patterns”, Nature, 20082Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 20123Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20114Rhee, et al. “On the Levy-Walk Nature of Human Mobility”, TON, 20115Chandra, et al. “Speed Distribution Curves for Pedestrians During Walking and Crossing”, Procedia, 2013

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MANET context Research question Experimental methodology Results Conclusion

Presentation outline

1 MANET context

2 Research question

3 Experimental methodology

4 Results

5 Conclusion

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MANET context Research question Experimental methodology Results Conclusion

Research question

How does human motion affect the performance of MANETprotocols?

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MANET context Research question Experimental methodology Results Conclusion

Presentation outline

1 MANET context

2 Research question

3 Experimental methodology

4 Results

5 Conclusion

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MANET context Research question Experimental methodology Results Conclusion

Scenario of study

A MANET where nodes roam according to . . .

Mobility models

Random Waypoint6

Self-similar least-actionwalk7

0

200

400

600

800

1000

0 200 400 600 800 1000

Y [m

]

X [m]

6Broch, et al. “A Performance Comparison of Multi-hop Wireless Ad Hoc Network Routing Protocols”,Mobicom 98, 1998

7Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 2012

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MANET context Research question Experimental methodology Results Conclusion

Scenario of study

A MANET where nodes roam according to . . .

Mobility models

Random Waypoint6

Self-similar least-actionwalk7

0

200

400

600

800

1000

0 200 400 600 800 1000

Y [m

]

X [m]

6Broch, et al. “A Performance Comparison of Multi-hop Wireless Ad Hoc Network Routing Protocols”,Mobicom 98, 1998

7Lee, et al. “SLAW: Self-similar least-action human walk”, TON, 2012

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E1: Analysis of MANET topology

Purpose: To investigate the connectivity features of the d-hopneighborhood of every node

Procedure

1 Compute the d-hop neighborhoodof a node

2 Count the size of the d-hopneighborhood

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E1: Analysis of MANET topology

Purpose: To investigate the connectivity features of the d-hopneighborhood of every node

Procedure

1 Compute the d-hop neighborhoodof a node

2 Count the size of the d-hopneighborhood

blue node’s 2-hop neighborhood

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E1: Analysis of MANET topology

Purpose: To investigate the connectivity features of the d-hopneighborhood of every node

Procedure

1 Compute the d-hop neighborhoodof a node

2 Count the size of the d-hopneighborhood

8 1

7

65 4

3

2

2-hop neighborhood size equals 8 nodes

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E2: Routing performance evaluation

Purpose: To analyze the performance of the routing protocolAODV

Source’s procedure

1 Select a reachable destination at dhops away randomly

2 Send a query to the destination

3 If a reply is received, send a queryto the destination again after t s

4 Else, select a new reachabledestination at random

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E2: Routing performance evaluation

Purpose: To analyze the performance of the routing protocolAODV

Source’s procedure

1 Select a reachable destination at dhops away randomly

2 Send a query to the destination

3 If a reply is received, send a queryto the destination again after t s

4 Else, select a new reachabledestination at random

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E2: Routing performance evaluation

Purpose: To analyze the performance of the routing protocolAODV

Source’s procedure

1 Select a reachable destination at dhops away randomly

2 Send a query to the destination

3 If a reply is received, send a queryto the destination again after t s

4 Else, select a new reachabledestination at random

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E2: Routing performance evaluation

Purpose: To analyze the performance of the routing protocolAODV

Destination’s procedure

If a query is received, send a reply to thesender

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MANET context Research question Experimental methodology Results Conclusion

Experiments

E2: Routing performance evaluation

Purpose: To analyze the performance of the routing protocolAODV

Source’s procedure

1 Select a reachable destination at dhops away randomly

2 Send a query to the destination

3 If a reply is received, send a queryto the destination again after t s

4 Else, select a new reachabledestination at random

13/25

MANET context Research question Experimental methodology Results Conclusion

Experiments

E2: Routing performance evaluation

Purpose: To analyze the performance of the routing protocolAODV

Source’s procedure

1 Select a reachable destination at dhops away randomly

2 Send a query to the destination

3 If a reply is received, send a queryto the destination again after t s

4 Else, select a new reachabledestination at random

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MANET context Research question Experimental methodology Results Conclusion

Simulation settings

Components

Simulation area

Mobile terminals

Reachability application

Lookup application

University campus 1000× 1000 m2

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MANET context Research question Experimental methodology Results Conclusion

Simulation settings

Components

Simulation area

Mobile terminals

Reachability application

Lookup application

Radius = 50 m

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MANET context Research question Experimental methodology Results Conclusion

Simulation settings

Components

Simulation area

Mobile terminals

Reachability application

Lookup application

Routing protocol AODV

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MANET context Research question Experimental methodology Results Conclusion

Simulation settings

Components

Simulation area

Mobile terminals

Reachability application

Lookup application

8 1

7

65 4

3

2

Time between observations t = 60 s

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MANET context Research question Experimental methodology Results Conclusion

Simulation settings

Components

Simulation area

Mobile terminals

Reachability application

Lookup application

Time between queries t = N (60, 36)

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

0

200

400

600

800

1000

0 200 400 600 800 1000

Y [m

]

X [m]

2000 waypoints

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

0

200

400

600

800

1000

0 200 400 600 800 1000

Y [m

]

X [m]

H = 0.75

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

0

200

400

600

800

1000

0 200 400 600 800 1000

Y [m

]

X [m]

area 1

radius equals 40 m

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

0

200

400

600

800

1000

0 200 400 600 800 1000

Y [m

]

X [m]

area 1area 5area 7

U(3, 5) areas per walker

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

100

120

140

160

180

200

500 520 540 560 580 600

Y [m

]

X [m]

trip

planning degree equals 3

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

0

0.2

0.4

0.6

0.8

1

0 0.5 1 1.5 2 2.5P

(S ≤

s)

Speed (s) [m/s]

N(1.36,0.0361)

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MANET context Research question Experimental methodology Results Conclusion

SLAW settings

Parameters

Number of waypoints

Hurst parameter

Confined area radius

Areas per walker

Planning degree

Node speed

Pause time

0

0.2

0.4

0.6

0.8

1

100 1000P

(T >

t)

Time (t) [s]

Paretob(1.36;30,9504)

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MANET context Research question Experimental methodology Results Conclusion

RWP settings

Configurations

Pure random

speedpause time

Human RWP

speedpause time

0

0.2

0.4

0.6

0.8

1

2 4 6 8 10 12 14 16 18 20

Speed (s) [m/s]

U(0.1,20)

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MANET context Research question Experimental methodology Results Conclusion

RWP settings

Configurations

Pure random

speedpause time

Human RWP

speedpause time

0

0.2

0.4

0.6

0.8

1

0 5 10 15 20

Pausetime (π) [s]

U(0,20)

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MANET context Research question Experimental methodology Results Conclusion

RWP settings

Configurations

Pure random

speedpause time

Human RWP

speedpause time 0

0.2

0.4

0.6

0.8

1

0 0.5 1 1.5 2 2.5P

(S ≤

s)

Speed (s) [m/s]

N(1.36,0.0361)

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MANET context Research question Experimental methodology Results Conclusion

RWP settings

Configurations

Pure random

speedpause time

Human RWP

speedpause time 0

0.2

0.4

0.6

0.8

1

100 1000P

(T >

t)

Time (t) [s]

Paretob(1.36;30,9504)

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MANET context Research question Experimental methodology Results Conclusion

Presentation outline

1 MANET context

2 Research question

3 Experimental methodology

4 Results

5 Conclusion

17/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Connectivity ratio

]times a node has neighbors

]observations

18/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

The network shows a similarperformance w/RWPconfigurations

One-hop connectivity of RWP issimilar to the two-hop connectivityof SLAW

RWP connectivity ratio is higherthan SLAW’s when routes arelarger than five hops

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7

Co

nn

ecti

vity

rat

ioRoute lenght [hops]

RWPHRWPSLAW

Network size = 300 nodes

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MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

The network shows a similarperformance w/RWPconfigurations

One-hop connectivity of RWP issimilar to the two-hop connectivityof SLAW

RWP connectivity ratio is higherthan SLAW’s when routes arelarger than five hops

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7

Co

nn

ecti

vity

rat

ioRoute lenght [hops]

RWPHRWPSLAW

Network size = 300 nodes

18/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

The network shows a similarperformance w/RWPconfigurations

One-hop connectivity of RWP issimilar to the two-hop connectivityof SLAW

RWP connectivity ratio is higherthan SLAW’s when routes arelarger than five hops

0

0.2

0.4

0.6

0.8

1

0 1 2 3 4 5 6 7

Co

nn

ecti

vity

rat

ioRoute lenght [hops]

RWPHRWPSLAW

Network size = 300 nodes

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MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Isolation ratio

]times a node is isolated

]observations

19/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

With SLAW, the network exhibitsthe lowest isolation ratio

When using a RWP configuration,the network needs 150 nodes toreach the isolation ratio that isexhibited by SLAW with only 25nodes

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200 250 300 350

Iso

lati

on

rat

ioNetwork size

RWPHRWPSLAW

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MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

With SLAW, the network exhibitsthe lowest isolation ratio

When using a RWP configuration,the network needs 150 nodes toreach the isolation ratio that isexhibited by SLAW with only 25nodes

0

0.2

0.4

0.6

0.8

1

0 50 100 150 200 250 300 350

Iso

lati

on

rat

ioNetwork size

RWPHRWPSLAW

19/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Number of neighbors

The number of neighbors a node has at d-hops away

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MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

Nodes have the largest number ofneighbors w/SLAW

The number of neighbors is almostconstant w/RWP

The number of neighbors increaseswhen distance increases for theRWP configurations 0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7M

ean

nu

mb

er o

f n

eig

hb

ors

Route length [hops]

RWPHRWPSLAW

Network size = 25 nodes

20/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

Nodes have the largest number ofneighbors w/SLAW

The number of neighbors is almostconstant w/RWP

The number of neighbors increaseswhen distance increases for theRWP configurations 0

0.5

1

1.5

2

2.5

0 1 2 3 4 5 6 7M

ean

nu

mb

er o

f n

eig

hb

ors

Route length [hops]

RWPHRWPSLAW

Network size = 25 nodes

20/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

Nodes have the largest number ofneighbors w/SLAW

The number of neighbors is almostconstant w/RWP

The number of neighbors increaseswhen distance increases for theRWP configurations

0

2

4

6

8

10

12

14

16

18

0 1 2 3 4 5 6 7

Mea

n n

um

ber

of

nei

gh

bo

rsRoute length [hops]

RWPHRWPSLAW

Network size = 300 nodes

20/25

MANET context Research question Experimental methodology Results Conclusion

E1: Analysis of MANET topology

Results

Nodes have the largest number ofneighbors w/SLAW

The number of neighbors is almostconstant w/RWP

The number of neighbors increaseswhen distance increases for theRWP configurations

6-hop neighborhood of node 299

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Successful lookup ratio

]replied queries

]sent queries

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

One hop paths have a probabilityof success close to one

HRWP and SLAW exhibit a similarSLR

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7SL

RRoute length [hops]

RWPHRWPSLAW

Network size = 300 nodes

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

One hop paths have a probabilityof success close to one

HRWP and SLAW exhibit a similarSLR

0.5

0.6

0.7

0.8

0.9

1

0 1 2 3 4 5 6 7SL

RRoute length [hops]

RWPHRWPSLAW

Network size = 300 nodes

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Round-trip time

The time interval measured from the instant a query is sent to anode to the instant in which the corresponding reply is received

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

The mobility model does not createsignificant differences

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7R

TT [s

]Route length [hops]

RWPHRWPSLAW

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Route lifetime

The duration of a path between a pair nodes

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

Path lifetime exhibits the highestperformance with SLAW

Path lifetime is almost constantwith RWP configurations

Path lifetime decreases almostexponentially with SLAW

In the worst case, lifetime underSLAW is three times greater thanRWP’s

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7Li

feti

me

[s]

Route length [hops]

RWPHRWPSLAW

Network size = 25 nodes

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MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

Path lifetime exhibits the highestperformance with SLAW

Path lifetime is almost constantwith RWP configurations

Path lifetime decreases almostexponentially with SLAW

In the worst case, lifetime underSLAW is three times greater thanRWP’s

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7Li

feti

me

[s]

Route length [hops]

RWPHRWPSLAW

Network size = 300 nodes

23/25

MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

Path lifetime exhibits the highestperformance with SLAW

Path lifetime is almost constantwith RWP configurations

Path lifetime decreases almostexponentially with SLAW

In the worst case, lifetime underSLAW is three times greater thanRWP’s

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7Li

feti

me

[s]

Route length [hops]

RWPHRWPSLAW

Network size = 300 nodes

23/25

MANET context Research question Experimental methodology Results Conclusion

E2: Routing performance evaluation

Results

Path lifetime exhibits the highestperformance with SLAW

Path lifetime is almost constantwith RWP configurations

Path lifetime decreases almostexponentially with SLAW

In the worst case, lifetime underSLAW is three times greater thanRWP’s

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7Li

feti

me

[s]

Route length [hops]

RWPHRWPSLAW

Network size = 300 nodes

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MANET context Research question Experimental methodology Results Conclusion

Presentation outline

1 MANET context

2 Research question

3 Experimental methodology

4 Results

5 Conclusion

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MANET context Research question Experimental methodology Results Conclusion

Final remarks

When human motion is considered . . .

MANETs show a high connectivity level

Node motion is not so harsh to network routing

Route lifetime suggests that building overlays is possible

25/25

MANET context Research question Experimental methodology Results Conclusion

Final remarks

When human motion is considered . . .

MANETs show a high connectivity level

Node motion is not so harsh to network routing

Route lifetime suggests that building overlays is possible

25/25

MANET context Research question Experimental methodology Results Conclusion

Final remarks

When human motion is considered . . .

MANETs show a high connectivity level

Node motion is not so harsh to network routing

Route lifetime suggests that building overlays is possible

25/25

MANET context Research question Experimental methodology Results Conclusion

Final remarks

Conclusion

Human motion could be afriend!

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