contact-based mobility metrics for delay-tolerant ad hoc networking

Universität Stuttgart

Institute of Parallel and Distributed Systems (IPVS)

Universitätsstraße 38D-70569 Stuttgart

Contact-Based Mobility Metrics for Delay-Tolerant Ad Hoc Networking

A. Khelil, P.J. Marrón, K. Rothermel

MASCOTS, Sept 29 2005


IPVS

Research Group

“Distributed Systems” 2

Outline

• Motivation

• Related Work

• Contact-Based Mobility (CBM) Metrics

• Statistical and Theoretical Analysis for Random Waypoint

• Uses of CBM Metrics

• Conclusion


IPVS

Research Group


dest-2

Motivation

• Mobile ad hoc network (MANET)

• In MANETs mobility can be exploited

◦ to increase the capacity of the network *)

◦ to overcome network partitioning

• New class of protocols and applications

◦ Physical transport of messages (mobility-aided)

◦ Tolerate higher E2E transmission delays (delay-tolerant)

• Delay-tolerant protocols and appl. act on a large time-scale

Investigation of mobility on a large time-scale is crucial

*) M. Grossglauser et al. “Mobility Increases the Capacity of Ad Hoc Networks” Trans. on Netw., 2002.

src

dest-1


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Research Group


Related Work

• Existing mobility metrics

◦ Velocity-based: e.g. speed, relative speed

◦ Link-based: e.g. link change rate, link duration *)

◦ Route-based: e.g. route change rate, route duration **)

• Metrics defined for (non-delay-tolerant) ad hoc routing

• Metrics model mobility instantaneously and do not support detection of mobility patterns a large time-scale

**) N. Sadagopan et al. “Paths: Analysis of Path Duration Distributions in MANET and their Impact on Routing Protocols” Mobihoc, 2003.

*) J. Boleng et al. “Metrics to Enable Adaptive Protocols for Mobile Ad Hoc Networks” ICWN, 2002.


IPVS

Research Group


Outline

• Motivation

• Related Work


◦ Methodology and Terminology

◦ Metrics Definition



• Conclusion


IPVS

Research Group


Methodology and Terminology (1)

• Observation: Epidemiology uses contacts to model mobility of individuals

• We use “contacts” between nodes to quantify the mobility on a large time-scale

AB

• Assumption: Nodes are uniquely identified (e.g. MAC addr.)

• Definitions

◦ Encounter between nodes n and m occurs if distance(n,m) <= com. range

enm={n, m, tstart, duration}

◦ Contact:

cnm={enm} AB1st E

2nd E

3rd E


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Research Group


Methodology and Terminology (2)

• Node manages a contact table for the “time of interest T”

• Cn={cnm}:

set of contacts of node n in T

• En={enm}:

set of encounters of node n in T

5

13

9

14

6

con

tact

ee

-ID

0 10 20 30 t

{0, 20}

{7.5, 7.5} {22.5, 12.5}

{22.5, 7.5}

{25, 12.5}

{32.5, 5}

{10, 7.5}

time duration

time (sec)

Contact Table (Node 1)

contact

encounter

time of interest T


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Research Group


Def. of Contact-Based Mobility (CBM) Metrics

• Node-centric vs. network-wide

• Metrics

◦ Avg. Encounter Frequency = ( = 1.4)

◦ Encounter Rate = (= 7/40 encounters/s)

◦ Contact Rate = (= 5/40 contacts/s)

◦ Avg. Encounter Duration =

◦ Avg. Contact Duration =

T

Cn

T

En

n

Ee nm

C

durennm

.n

Ee nm

E

durennm

.

n

n

C

E

5

13

9

14

6

con

tact

ee

-ID

0 10 20 30 T=40s

{0, 20}

{7.5, 7.5} {22.5, 12.5}

{22.5, 7.5}

{25, 15}

{32.5, 7.5}

{10, 7.5}

time duration

time (sec)

Contact Table (Node 1)

1C1E = 5= 7


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Research Group


Outline

• Motivation

• Related Work




• Conclusion


IPVS

Research Group


Simulation Parameters

Area 1000m x 1000m

Number of nodes N

Communication range R = 100 m

Mobility Model Random waypoint

N ∈ [30,300]

Simulation time T = 1800 s

uniform in [0, Vmax ]Vmax ∈ [3,30] m/s

- pause uniform in [0,2] s

+

+

+

+

+

+

+

+

R

Area

+

+

- speed

+

Population closed


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Research Group


Average Encounter Frequency

• AEF is independent from node density

• AEF increases with Vmax


IPVS

Research Group


Average Encounter Rate | Average Contact Rate

• Linear increase with node density

• Non linear increase with Vmax

• Linear increase with node density

• linear increase with Vmax

AER / ACR ≈ AEF


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Research Group


Avg. Contact Duration | Avg. Encounter Duration

• Independent from node density

• Decreases with Vmax

• Independent from node density

• Decreases with Vmax

ACD / AED ≈ AEF


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Research Group


Analytical Model for Random Waypoint

AA

avgSpeed * time

2R

areadensityencounters *#

= avgSpeed * time * 2R

= Vmax / 2RVdensity

time

encounterserRateavgEncount

**

#

max


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Research Group


Comparison Analytical & Simulation Results

• Results are very comparable

• Differences are due to

- Spatial node distribution is not exactly uniform, since nodes are more likely to locate in the middle of movement area [Bettstetter]

- Average nodal speed decreases over time [Yoon]


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Research Group


Outline

• Motivation

• Related Work




◦ CBM Metrics in Network Simulator ns-2

• Conclusion


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Research Group


Uses of CBM Metrics

• Design and adaptation of delay-tolerant mobility-aided protocols

◦ Detect large time-scale mobility patterns, examples:

▪Node src encounters dest-1 periodically

▪Nodes src and x move in a group

◦ At run-time: HELLO beaconing

Dest-1

X

Contact table of src

src

dest-1

x

• Performance analysis of delay-tolerant mobility-aided protocols

◦ Classification of mobility scenario

◦ Performance evaluation and comparison


IPVS

Research Group


The Network Simulator ns-2

• Ns-2: discrete event simulator for wired & wireless networks

• General Operations Director (GOD): central instance

◦ Stores global state information:

▪#nodes

▪node position

▪number of hops between 2 nodes

▪partitioning information

• GOD simplifies (global view) evaluation of wireless protocols


IPVS

Research Group


CBM Metrics in ns-2

Annotation ToolAnnotation Tool

GeneralGeneralOperationsOperations

DirectorDirector(GOD)(GOD)

Delay- Delay- TolerantTolerantProtocolProtocol

EvaluationEvaluation

Query()

CBM metrics

ns-2ns-2

Simulation Simulation tracetrace

Arbitrary ns-2 Arbitrary ns-2 movement tracemovement trace

Before Before simulationsimulation

During During simulationsimulation

Movement trace annotated with Movement trace annotated with CBM informationCBM information

Basic communication Basic communication modelmodel

http://canu.informatik.uni-stuttgart.de/cbmhttp://canu.informatik.uni-stuttgart.de/cbm

A and B communicate if

distance(A,B) <= comm_range


IPVS

Research Group


Conclusion

• We introduced novel metrics to quantify mobility on a large time- scale

◦ Based on contacts between nodes

◦ Important for evaluation of mobility-aided delay-tolerant networking

• Detailed statistical analysis for random waypoint

• First steps towards an analytical model for random waypoint

• We provide implementation for ns-2


Institute of Parallel and Distributed Systems (IPVS)

Universitätsstraße 38D-70569 Stuttgart

Thank you for your attention!

http://canu.informatik.uni-stuttgart.de/cbmhttp://canu.informatik.uni-stuttgart.de/cbm

{khelil,marron,rothermel}@informatik.uni-stuttgart.de

contact-based mobility metrics for delay-tolerant ad hoc networking

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