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MobiWAC'15 Presentation
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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
2/25
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
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)))
4/25
MANET context Research question Experimental methodology Results Conclusion
Why is the design of MANET protocols hard?
MANET challenges
Low per-node capacity
Dynamical topology
4/25
MANET context Research question Experimental methodology Results Conclusion
Why is the design of MANET protocols hard?
MANET challenges
Low per-node capacity
Dynamical topology
4/25
MANET context Research question Experimental methodology Results Conclusion
What’s the problem with node motion?
It invalidates routes established by routing protocols
5/25
MANET context Research question Experimental methodology Results Conclusion
How is node motion?
We know . . .
MANETs are integrated byportable devices
Humans carry such devices
6/25
MANET context Research question Experimental methodology Results Conclusion
How is node motion?
We know . . .
MANETs are integrated byportable devices
Humans carry such devices
6/25
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
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
Presentation outline
1 MANET context
2 Research question
3 Experimental methodology
4 Results
5 Conclusion
8/25
MANET context Research question Experimental methodology Results Conclusion
Research question
How does human motion affect the performance of MANETprotocols?
9/25
MANET context Research question Experimental methodology Results Conclusion
Presentation outline
1 MANET context
2 Research question
3 Experimental methodology
4 Results
5 Conclusion
10/25
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
11/25
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
11/25
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
12/25
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
12/25
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
12/25
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
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
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
13/25
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
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
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
13/25
MANET context Research question Experimental methodology Results Conclusion
Simulation settings
Components
Simulation area
Mobile terminals
Reachability application
Lookup application
University campus 1000× 1000 m2
14/25
MANET context Research question Experimental methodology Results Conclusion
Simulation settings
Components
Simulation area
Mobile terminals
Reachability application
Lookup application
Radius = 50 m
14/25
MANET context Research question Experimental methodology Results Conclusion
Simulation settings
Components
Simulation area
Mobile terminals
Reachability application
Lookup application
Routing protocol AODV
14/25
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
14/25
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)
14/25
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
15/25
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
15/25
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
15/25
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
15/25
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
15/25
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)
15/25
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)
15/25
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)
16/25
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)
16/25
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)
16/25
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)
16/25
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
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
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
18/25
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
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
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
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
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
20/25
MANET context Research question Experimental methodology Results Conclusion
E2: Routing performance evaluation
Successful lookup ratio
]replied queries
]sent queries
21/25
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
21/25
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
21/25
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
22/25
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
22/25
MANET context Research question Experimental methodology Results Conclusion
E2: Routing performance evaluation
Route lifetime
The duration of a path between a pair 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 = 25 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
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
Presentation outline
1 MANET context
2 Research question
3 Experimental methodology
4 Results
5 Conclusion
24/25
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
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!
25/25
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