stochastic characterization of mobile ad-hoc networks

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Stochastic Characterization of Mobile Ad-hoc Networks

John P. Mullen and Timothy I. MatisCenter for Stochastic ModelingDepartment of Industrial EngineeringNew Mexico State University

INFORMS 2004

2

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

What Are MANETS ?

A MANET is a mobile ad-hoc wireless communication network that is capable of autonomous operation Each node is capable of transmitting, receiving, and routing packets of

information. The network has no fixed backbone The nodes are able to enter, leave, and move around the network

independently and randomly

3

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Mobile Ad Hoc Path Search

Y

XAB

I

G

EF

C

D

H

4

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Same MANET After a While

Y

XAB

I

G

EF

C

D

HH

X

I

G

FE

D

B

A

C

Y

5

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

NutshellMANET field performance differs greatly from simulation’s

Field & testbed performance is much poorer Developing MANET protocols in the field is very difficult Improving simulation fidelity increases the value of simulation in design. Higher fidelity earlier in the design process leads to better designs

Research focus: Significantly improve the fidelity of MANET simulations Without significantly increasing

Simulation run time or Modeling effort.

Research results Up to an order of magnitude improvement in fidelity Runtime increases are often insignificant, but generally less than 100% Very little added modeling effort

6

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Overview

Multipath Fading and its impact on mobile ad hoc netsThe Stochastic Model

Objectives Implementation Validation

Demonstrations of the Model Small Models

Impact of Short Retry Limit (SRL) Comparing AODV and DSR

Large Models AODV vs. DSR AODV vs. DSR using GPS data Impact of SRL on DSR

Summary, Conclusions and Further Work

7

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Shadowing and Fading

Shadowing Is caused by objects absorbing part of the signal Can be estimated by looking at the Line of Sight (LOS) path Causes a random reduction in signal strength.

Fading Is the result of the algebraic sum of signals from many paths Because movement of any object in the vicinity can change the sum

Multipath fading is extremely difficult to model and predict Would be very time consuming to simulate exactly And would have little predictive value.

This phenomena causes: Very rapid large-scale fluctuations in signal strength Can cause the signal to be significantly lesser or greater than expected.

8

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Main causes of signal variation

R

T

Shadowing

Multipath

9

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Measured Received Signal Strength(from Neskovic 2000)

10

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Stochastic Variation Model

The Model Given mp(d), the expectation of power at distance d Rayleigh fading model of the instantaneous power, P(d)

Pr {P(d) ≤ p} = 1 – exp{-[p/mp(d)]} Inverse transform of the Rayleigh fading model

P(d) = -mp(d)ln(1-r)

11

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Simulated vs. Real Power

Actual Measurements Simulated Values

12

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Validation

Simulated reported field tests and compared results K.-W. Chin, J. Judge, A. Williams, and R. Kermode, "Implementation

experience with MANET routing protocols," ACM SIGCOMM Computer Communications Review, vol. 32, pp. 49 - 59, 2002.

I. D. Chakeres and E. M. Belding-Royer, "The Utility of Hello messages for determining link connectivity," Wireless Personal Multimedia Communications, vol. 2, pp. 504 - 508, 2003.

D. S. J. D. Couto, D. Aguayo, J. Bicket, and R. Morris, "A High Throughput Path Metric for MultiHop Wireless Routing," presented at MobiCom '03, San Diego, California, USA, 2003.

S. Desilva and S. Das, "Experimental evaluation of a wireless ad hoc network," 2000.

Simulations with Standard non-fading model were exceedingly optimistic Proposed fading model were very much more realistic.

13

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Impact of Multipath Fading on MANETsHow does it affect MANETs?

Unnecessary route searches Selection of false routes

14

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Impact of Multipath Fading On MANETs

NominalRange

(r0)

OK

StubCellular

DroppedPackets

Fadingmargin

FalseRoutesOK

15

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Impact of Multiple Retries on MANETs

16

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

The MANET fading Trade-off

Protocol

ImproveReliability

OnGood Routes

IncreaseRisk of

SelectingBad Routes

MANET:Nominal range is amatter of balance.

Most Wireless:Nominal range is amatter of design.

17

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Demonstrations

Small Models (validations of field tests) Scenario 1 – Performance vs. distance.

Used for the two cases above Scenario 2 – Routing Test Focus mainly on fading effects Models:

Fading vs. nonfading simulations of AODV DSR vs. AODV with fading model

Large models (exploration) Scenario 3 – 24 nodes. Also consider other effects, such as interference Models: Fading and non-fading versions of

AODV vs. DSR AODV vs. DSR using GPS data Impact of SRL on DSR

18

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Scenario 2: Routing test(from Chin et. al., 2002)

10 pps

0.5 m/s

r0 = 39m

19

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Sc 2: Fading vs. Nonfading: AODV

Notes: Default values for AODV SRL = 7

20

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Sc 2: AODV vs. DSR

Notes: Default protocol values SRL = 7

Nonfading model shows no difference

21

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Scenario 3: Larger Scale Test

Features:•More nodes (24)•Random r-t pairs•Interference•Higher loads

22

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Mean Throughput: AODV vs. DSR

Notes:•Default protocol values•SRL = 7

23

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Mean Delay: AODV vs. DSR

Notes:•Default protocol values•SRL = 7

24

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Using GPS data

3

2

1 B

Ar0

Use GPS to block unreliable routes

25

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Impact of GPSWithout GPS With GPS

26

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Mean Throughput: Impact of SRL on DSR

Notes:•Default protocol values

27

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Mean Delay: Impact of SRL on DSR

Notes:•Default protocol values

28

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Execution Time in Scenario 3 (Virtually no differences in Scenarios 1 & 2)

29

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Summary

Non fading modelOverestimates field performance Is very insensitive to all the contrasts shown here and more.

Fading modelProvides more realistic estimatesBetter predicts impacts of protocol and parameter changesShows promise of new techniques.Requires little or no additional modelingHas little impact on execution time

(Alternative is a testbed or a field trial)

30

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Conclusions

Multipath Fading has a great impact on mobile ad hoc nets

Including its effects in simulation greatly improves fidelity

Stochastic Modeling of Multipath Fading Is a practical way to include the impact of fading

Minor modifications to code (in OPNET, at least)Without great increases in

Modeling effort orExecution time

31

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Future Work

More Fading ModelsRayleigh Ricean Nakagami

Other significant RF effects e.g. exponential decay factor

Better user interface Allow selection of models & parameters without need to recompile.

ValidationReplicating published studies Set up own testbed and field trials

Better modeling of fading impacts Hello vs. control vs. data packet results Other significant measurable elements.

32

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Acknowledgements

OPNET TechnologiesSoftware license research grantTechnical assistance

Center for Stochastic ModelingTechnical resources

Klipsch School of Electrical and Computer EngineeringDr. Steve HoranDr. Hong Huang (also CSM member)

33

INFORMS 2004

Primary Author: J.P. Mullen, Presented by: T.I. Matis, 10/26/2004

Final Questions?