Generic Analytical Model for Mobile Networks Management in IP-Based Networks Dipl.-Ing. Ali Diab Page 1 Generic Analytical Model for Mobile Networks Dr.-Ing. Ali Diab Generic Analytical

Integrated Communication Systems Groupwww.tu-ilmenau.de/ics

Mobility Management in IP-Based NetworksDipl.-Ing. Ali Diab

Page 1


Generic Analytical Model for Mobile NetworksDr.-Ing. Ali Diab

Page 1

Generic Analytical Model for Mobile Networks

Dr.-Ing. A. Diab



Page 2

Outline

• Introduction

• Case Study: Mobility Management– Overview– Generic Model– Evaluation Metrics– Example– Performance vs. Cost

• Conclusions

• References



Page 3

Introduction



Page 4

Motivation

• Future mobile communication networks– Heterogeneous networks– Wide deployment and large variety of new applications– Ubiquitous access to information, usage of services, etc.– More dynamic in terms of changing topologies, access technology, etc.

• Lots of challenges to overcome– Efficient mobility management– Guarantee of Quality of Service (QoS)– Securing of communication links and content– Service placement– ….

• New developed mechanisms/protocols should be evaluated, how?



Page 5

Which Evaluations Types Do We Have?

• Functional Evaluation– Prototypes to check if the scheme developed performs correctly as it

has to do– SDL, UML, FSM, etc.

• Performance Evaluation– Estimate how good/bad/expensive is your scheme– Mathematical models– Simulations– Real testbeds



Page 6

Performance Evaluation Steps

Mathematical analysis Simulation Implementation

• Developed fast

• Low development

cost and good

approximation of

the performance

• Model for each

protocol/Scheme

under study

• Takes long time

• High development

cost, but detailed

evaluation

• Detect errors in the

design before the

real implementation

• Longer time than

by simulation

• Very high

development cost,

but the most

detailed evaluation

• Test of real

applications

Try to develop a generic model to handle the issue you are studying



Page 7

How to Model in a Generic Way

• Define the main components (key stones) of the issue under study– Network topology– Mechanism/protocol– The dynamics– …

• Model each component alone– Generalize the characters of each component– Model it so that physically existing components can be mapped to the

modeled one

• Determine the evaluation metrics and calculate them



Page 8

Case Study: Mobility Management



Page 9

Access Router (AR)

AR

Corresponding Node (CN)IP-based network

Home Agent (HA)CN

Overview - Mobile IP Version 6 (MIPv6)

Periodic Router Advertisements (RAs)

Mobility support; use of two IP addresses (Home Address (HoA) & Care of Address (CoA))

AR



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AR

CNIP-based network

HACN


Binding Updates (BUs)/Binding Acknowledgments (BAs)

AR

During the handoff no communication is possible

AR • Listen to a RA message

• Configure a new CoA

• Duplicated address detection



Page 11

IP-based networkCN


CNHA

AR

AR AR

Route optimization

Triangular routing

Inadequate for real-time applications• Triangular routing• Encapsulation overhead• Long handoff latency



Page 12

Overview - Improvement Principles

IP-based network IP-based network

HA

IP-based network

Gateway Gateway

AR

Micro-mobility: local processing of mobility(intermediate node(s), hierarchical topology)

Local processing can be in • Gateway (HMIP)• Crossover router and/or old

AR (AFA, CIP, HAWAII)• Certain servers/proxies in the

domain (BCMP)



Page 13



HA

IP-based network

Gateway Gateway

AR

Macro (global) mobility (MIP)



Page 14



HA

IP-based network

Gateway Gateway

AR

Detection of a layer 2 trigger (FMIPv6) start the handoff in advance



Page 15

Generic Model – Main Components

• Main components– Network topology– Mobility model– Mobility management protocol

IP-based network



Page 16

Generic Model – Network Topology

IP-based network

Gateway (GW)

Mobility Router (MR)

Mobility Agent (MA)

HACN

Mapping of a given network topology to a generic one (which nodes are MAs, MRs, etc.?)

D MA,MR

D MR,GW

D GW,CN

D HA,CN



Page 17

Generic Model – Mobility Model

IP-based network

Gateway (GW)

Mobility Router (MR)

Mobility Agent (MA)

HACN

1PMR nPMR

PGW∑=n

nPMRR

PGWG =



Page 18


MA1

MA4 MA3

MA8

MA5

MA7 MA6

MA9

5,1P

1,5P

2,1P

1,2P

9,1P 4,1P9,2P2,9P 5,3P

4,9P 3,4P

8,9P6,4P

4,6P7,9P9,7P

8,7P

7,8P

3q

4q9q

6q8q

7q

1q

5q2qMA2

iq Probability that the MN switches in the range of iMA

Transition probabilities

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡

=

zzzz

z

PPP

PPP

P

,2,1,

,12,11,1

....................

...

]...[21

0Z

qqqQ =



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PQQ nn *1 =+

]...[lim21 Z

n

nPPPQQ ==

∞→

The probability that the MNwill stay in the range of eachMA at the steady state of thesystem

∑∑ ≠∈=j

njjii

njiandMRIjiwherePPMRP )(,*)( ,

∑=

=ϑ

1

)(n

nMRPR

The probability that thecrossover router is

nMR

RG −=1



Page 20

Generic Model – Protocol Operation

IP-based network

GW

MR

MA

HACN

Anchor Point (AP) New MAOld MA

Binding Update node (BUnode)

• Mapping of a given mobility protocol to a generic one

• Calculate evaluation metrics for the generic protocol



Page 21

Generic Model – Protocol Operation

][ANPGWMAMRMAHAGWMR

JJJJJJB−−

=

The probability that the MNupdates its binding at the GW

the probability that the MNupdates its binding at the oldor new MA when thecrossover router is the GW

]0000[ GRB= The protocol updates is binding at the MRand GW (e.g. HMIP)

]00000[ GRB += The protocol updates is binding at the HA(e.g. MIP)



Page 22

Generic Model – Evaluation Metrics

• Performance Evaluation– Average handoff latency– Average expected number of dropped packets

• Cost Estimation– Location update cost– Packets delivery cost– Total cost

• Take into account that they have to be computed for eachBUnode



Page 23


• Calculation of the handoff latency– Handoff latency vector

– Average handoff latency

][ANPGWMAMRMAHAGWMR

TTTTTTT−−

=

The handoff latency when theBUnode is a MR

The handoff latency when theBUnode is an ANP

1* −= TBTavr



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Movementdetection time

Number of messagesexchanged on thewireless link

How many times theMA processeshandoff controlmessages

Delay on the link(between the current MAand the BUnode)

Processing timerequired to processa control messagein the MA

Number of IntermediateNodes (InNode)

InNode is a node thatsupports mobility anddifferent from the MA,MR, GW, HA and ANP

Protocol-epecificextra latency



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][ APGWMAMRMAHAGWMR JJJJJJB −−= Probability per BUnode

][ APGWMAMRMAHAGWMR TTTTTTT −−= HO latency per BUnode

1* −= TBTavr Average handoff latency



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• Calculation of the average number of dropped packets– Packet dropping vector

– Expected average number of dropped packets per handoff

][ANPGWMAMRMAHAGWMR

LPLPLPLPLPLPLP−−

=

Expected Number of droppedpackets when the BUnode isthe GW

1* −= LPBLPavr



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• Expected number of dropped packets on downlink

• Expected number of dropped packets on uplink

λ*00

))T(t)t((tLPlinkBUnodeBUnode

−−+=

The time, atwhich thehandoff starts

The time, at whichthe BUnode isinformed

Delay betweenthe old MA andthe BUnode

Packetsarrival rate

λ*BUnodeBUnode

TLP =



Page 28


Tanik

akaktktkttS

itimer

SInNode

BUnodeMABUnodecurrentMA,MAMNBUnode

∑=

−+++

++++Δ=

2

)2(''6

'5

'44,3

*2**

****

γ

Number of messagesexchanged on thewireless link (requiredto notify the BUnode)

Number of messages exchangedbetween the current MA and theBunode (required to notify theBUnode)

How many times, theBUnode processescontrol messages inorder to get notified

Protocol-epecificextra latencyduring the Bunodenotifying procedure

To consider dropping of control messages

S: number of times, the message istransmitted (> 1)

: Time to wait before retransmission T

timer



Page 29

Generic Model – Example

Current AR

AR

CN

IP-based network

HACN

Layer3-Frequent HandoffRegion (L3-FHR)

MN’s specific data (soft states)

• Mobile IP FastAuthentication protocol(MIFA)



Page 30


CN

IP-based network

HACN

Layer3-Frequent HandoffRegion (L3-FHR)

MN’s specific data (soft states)

Old AR

New AR

• Mobile IP FastAuthentication protocol(MIFA)



Page 31


CN

IP-based network

HACN

Old AR

New AR

BU/BA

UL

DL

BU: Binding UpdateBA: Binding Acknowledgement Hn_Not: Handoff Notification Hn_Ack: Handoff Acknowledgement M_P_Not: Movement Probability Notification



Page 32


CN

IP-based network

HACN

Old AR

New AR

BU/BA

UL

DL

BU: Binding UpdateBA: Binding Acknowledgement Hn_Not: Handoff Notification Hn_Ack: Handoff Acknowledgement M_P_Not: Movement Probability Notification



Page 33


IP-based network

GW

HA

CN

MR

MA

2 Hops

2 Hops

5 Hops

3 Hops

4 Hops

5 ms

• Delay on wireless links: 2 ms

• Layer 2 handoff: 50 ms



Page 34


MA1

MA4 MA3

MA8

MA5

MA7 MA6

MA9

25.0

1

25.0

5.0

25.025.05.025.0 1

25.0 5.0

25.0 5.0

125.05.0

5.0

1

MA2

• R = 0.75• G = 0.25



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Assumed topology

CN

IP-based network

HA

CN

Old MA

New MA

UL

BU

BA

• Handoff latency on uplink

BUnode is the new MA

]00000[ GRB +=

]00000[MRMA

TT−

=

Two messages areexchanged on thewireless link

is 21κ

The new MA mustprocess the BUmessage

is 1'1κ



Page 36


Assumed topology

CN

IP-based network

HA

CN

Old MA

New MA

BU

• Handoff latency ondownlink

BUnode is the old MA

]00000[MRMA

TT−

=

One messages areexchanged on thewireless link

is 21κ

Two messages areprocessed

is 2'1κ

two messages areexchanged on thewired link

is 22κ

]00000[ GRB +=



Page 37

Generic Model – Performance vs. Cost

• Separate evaluation of performance and cost• Most cases

– Performance gain through increase in cost• Better

– Consider all performance and cost metrics• Question

– Which gain for which cost?• Mostly:

– From the provider’s point of view. However,– From user’s point of view is possible



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[ ]hPer fxfxfxMx ...21=Performance matrix:

Number of performancemetrics

Protocol

[ ]hPer gpgpgpG ...21=Performance gain matrix:

100*)(100i

ii fb

fagp −=

[ ]hPer fwfwfwF ...21=Importance matrix:

1* −= PerperPer GFGainPerformance gain (A compared to B):

Performance metric for x



Page 39


Cost matrix:

Number of cost metricsProtocol

Cost gain matrix:

Importance matrix:

Cost gain (A compared to B):

[ ]gCost CxCxCxMx ...21=

[ ]gCost gcgcgcG ...21=

100*)(100i

ii Cb

Cagc −=

[ ]gCost cwcwcwF ...21=

1* −= CostCostCost GFGain

Cost metric for x



Page 40

Generic Model – Performance vs. CostC

ost g

ain

Maximumperformance andminimum cost

Network provider upgrades from MIPv6 to MIFAv6



Page 41

Conclusions



Page 42

Conclusions

• Development of generic mathematical models is significantlyencouraged

• Define the main components you need, model them and model theevaluation metrics

• Consider the relation between performance and cost• A certain protocol may be

– faster, better, etc.– …– The upgrade to this protocol may not be good for the network provider

or even for the user (the existing network topology for example notadequate for the protocol)



Page 43

References



Page 44

References

• A. Diab, „Mobility Management in IP-Based Networks: Analysis, Design, Programming andComputer-Based Learning Modules“, Doctoral thesis, Ilmenau University of Technology, 2010.

• A. Diab, F. Liers, A. Mitschele-Thiel, “Performance Analysis of Mobility Management ProtocolsUsing a Generic Mathematical Model”, in the proceeding of the 10th ACM/IEEE InternationalSymposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM’07),Greece, October 2007.

• D. Johnson, C. Perkins, J. Arkko, “Mobility Support in IPv6”, RFC 3775, June 2004.

• H. Soliman, C. Castelluccia, K. El-Malki, L. Bellier, “Hierarchical Mobile IPv6 Mobility Management(HMIPv6)”, RFC 4140, August 2005.

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Generic Analytical Model for Mobile Networks Management in IP-Based Networks Dipl.-Ing. Ali Diab Page 1 Generic Analytical Model for Mobile Networks Dr.-Ing. Ali Diab Generic Analytical