Report From Centre

8/13/2019 Report From Centre

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TCP-Aware Channel Allocation in CDMA Networks

Synopsis

This project explores the use of rate adaptation in cellular networks to maximizethroughput of long-lied TCP sessions! Modern cellular networks incorporate "#

technolog$ that allows them to d$namicall$ ar$ the wireless channel rate in response to

user demands and channel conditions! %oweer& the set of data rates as well as the

scheduler's rate adaptation polic$ are t$picall$ chosen to maximize the throughput of

inelastic connections! (e focus on the pro)lem of maximizing the throughput of TCP

connections and propose a joint optimization of MAC and ph$sical la$er parameters with

respect to TCP sending rate! *n particular& we propose a simple TCP-aware channel

scheduler that adapts the wireless channel rate to changes in the TCP sending rate and

explore its performance for )oth single and multiple concurrent sessions! *n the case of a

single TCP session& we deelop a fluid model of its stead$-state )ehaior in such a

s$stem that adapts )etween two channel rates!

The accurac$ of the model& it's utilit$ in selecting optimal rates as well as the

performance of s$stems with up to three channel rates are explored with ns-+ simulations!

,ur results indicate that a two-rate scheme improes TCP throughput )$ . to +/ percent

oer a s$stem that does not exploit rate adaptation and that little additional )enefit

accrues from the addition of a third channel rate! #inall$& we extend the framework to

scenarios where )andwidth is shared )$ multiple TCP sessions! (e propose two channel

allocation algorithms& one rel$ing on detailed TCP state information& the other not& and

explore their performance through simulation! ,ur results indicate that TCP throughput is

relatiel$ insensitie to either channel allocation algorithm& and adaptie rate ariation is

the dominant factor in performance! This project is deeloped using N0 -+!


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INTRODUCT

ION


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INTRODUCTION

M,D1"N digital communication technologies com)ined with powerful mo)ile

processors now allow wireless channel schedulers in cellular networks to rapidl$ change

the allocated channel resources in response to channel conditions as well as user

demands! This is achieed )$ changing parameters 2and com)inations thereof3 such asthe coding rate& spreading factor& modulation scheme& and link-la$er retransmission rate!

#or ease of exposition& we shall refer to these jointl$ as "# control aria)les! These

aria)les essentiall$ trade off data rates for improed frame error rates 2#1"s3 and ice

ersa!

Cellular networks t$picall$ specif$ arious com)inations of the "# control

aria)les that result in a set of allowed data rates and corresponding #1"! The "#

scheduler d$namicall$ assigns rates from this allowed set )ased on its rate adaptation

polic$! #or example& in the CDMA+/// x"TT network& the scheduler can d$namicall$

transition )etween fie different data rates during a mo)ile's session in response to )uffer

content and channel conditions )$ ar$ing the spreading factor through the (alsh code

length!

A shorter (alsh code lowers the spreading factor which results in higher data

rates! %oweer& a shorter code results in lower 0ignal to *nterference and Noise "atio

20*N"3 and supports fewer users simultaneousl$! *n practice& the aforementioned

parameters as well as the scheduler's rate adaptation polic$ are chosen to optimize the

raw ph$sical la$er goodput of a user! The set of data rates is o)tained )$ choosing a

com)ination of the "# control aria)les that produces the highest channel data rate under

a particular channel condition+ for a target #1"! 0imilarl$& scheduling policies t$picall$

assign the highest possi)le data rate allowed 2for a gien channel condition3 from the set


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of gien data rates that can clear the )uffer )acklog4 2see 5+6 for a detailed

characterization of this )ehaior3! (hile ideal for inelastic constant rate applications& this

resource allocation methodolog$ can produce su)optimal performance of elastic

applications and protocols& in particular TCP& that adapt their rate in response to feed)ack

from the receier!

As is well known& TCP& )$ far the most dominant transport protocol& uses an

additie increase multiplicatie decrease 2A*MD3 algorithm that graduall$ increases its

transmission rate )ased on receier feed)ack and rapidl$ throttles )ack when it perceies

losses 2either due to congestion or channel errors3! 7ien this complex relation )etween

TCP throughput and the channel transmission and loss rate& the same trade-off in channel

capacit$ and #1" that works for inelastic traffic ma$ $ield data rates and #1"s that

degrade TCP throughput! 0imilarl$& a scheduler's rate adaptation polic$ that alwa$s aims

to clear )uffer )acklog can )e su)optimal for TCP! #or example& when the TCP source

has a small window and is ramping up its rate& it is er$ sensitie to losses )ut not to the

assigned channel rate!

*n such a state& if the "# scheduler allocates a high channel rate at the expense of

a high #1" 2perhaps due to a sudden accumulation of )uffer )acklog as a result of jitter

in the network3& the TCP source cannot full$ utilize the high rate and& in fact& ma$ drop

its window or time out due to channel errors! Conersel$& for large windows 2high TCP

sending rates3& it ma$ )e adisa)le to allocate high channel rates een at the expense of

high )it error rates& since a low channel rate will ineita)l$ result in packet loss due to

congestion! ,n a related note& a preious stud$ found that sharp )andwidth oscillations

induced )$ rate adaptation of the "# scheduler in CDMA networks that are agnostic to

TCP result in throughput degradation!

#inall$& as noted preiousl$& in current CDMA networks 2e!g!& CDMA+///

x"TT3& the high-rate channels are achieed )$ reducing the spreading factor of the

orthogonal (alsh codes! This essentiall$ implies that onl$ few users can simultaneousl$

share the high-rate channels at an$ gien time& simpl$ )ecause of the shorter code length!

*n particular& the higher the channel rate& the fewer the num)er of concurrent users that

can )e supported! Thus& selection as well as allocation of high-rate channels must )e

made in a judicious fashion that not onl$ accounts for TCP )ehaior )ut is also fair across


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users! The a)oe discussion clearl$ motiates the case for TCP-aware d$namic rate

allocation as a means to increase throughput of TCP sessions oer wireless channels!8 *n

order to achiee this o)jectie& such a scheduler should )e a)le to 3 choose control

aria)les such as coding rate that $ield the optimal set of data rates 2and corresponding

#1"s3 from the perspectie of TCP throughput and +3 set channel rates in a manner that

is cognizant of TCP d$namics! The proposal of a simple scheduler that captures the

aforementioned properties and its anal$sis form the main o)jectie of this project!

0pecificall$& we propose a wireless channel scheduler that allocates different

channel rates from a set of optimized rates to TCP sessions in response to their sending

rates! *n the context of a single TCP session& we deelop a model to compute its long-

term throughput under such a scheduler and use it for joint optimization of control

aria)les& e!g!& spreading factor& to compute the set of optimal channel rates that are used

)$ the scheduler! (e extend the rate allocation framework to incorporate the presence of

multiple TCP sessions! *n particular& gien a set of channel rates that are computed )$ the

single flow model& we stud$ different mechanisms for allocating these channel rates to

different TCP flows in order to improe the throughput capacit$ of the s$stem


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ABOUT THE PROJECT

This project present the s$stem model and assumptions utilized in our work that capture

the arious aspects of a

CDMA s$stem mentioned a)oe9

! #or simplicit$& we focus on a two-rate s$stem to explain our rate allocation framework!

1xtensions of the s$stem model to three or more rates are straightforward! Denote )$ C/

and C the low-rate 2also called fundamental3 channel rate and high-rate 2also called

supplemental3 channel rate& respectiel$! Clearl$& C/2C3! At each point in time& the

scheduler decides which of the two channels& the low-rate channel 2rate C/3 or the high-

rate channel 2rate C3& are to )e assigned to a TCP session! 1ach actie user can alwa$s

)e assigned a low-rate channel: howeer& allocation of high-rate channels is ar)itrated )$

the channel scheduler )ecause there are onl$ a few highrate channels!+! The packet error pro)a)ilit$ is implicitl$ assumed to )e a function of the assigned rate

and denoted )$ p2p3 when the assigned channel rate is C/2C3! This is an important

feature representatie of current wireless s$stems where an increase in channel rate

t$picall$ comes at the cost of increased packet error pro)a)ilit$! #or simplicit$& we shall

refer to2pi& Ci3 together as a state or mode!

4! (e assume the presence of power control to primaril$ com)at fast fading and

interference effects! This is true in current s$stems where fast closed-loop power control

tracks a specified target 0*N" 2or e;uialentl$ target #1"3!

8! (e assume no 2or a er$ small3 )uffer at the )ase station! %ence& TCP experiences

congestion if its sending rate exceeds the maximum assigned channel rate!

.! #inall$& in the context of multiple TCP sessions& we assume a fixed population of N

sessions! 1ach session can )e assigned a low-rate channel: howeer& onl$ < = N sessions


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can )e assigned a high-rate channel concurrentl$! This captures issues such as increased

interference in high-rate channels and also allows us to stud$ statistical multiplexing gain

)$ ar$ing

#inall$& we emphasize that at this stage& no specific assumptions hae )een made

regarding how the channel rates are achieed nor how the$ result in the specific channel

error pro)a)ilities! *ndeed& the specific relation is not re;uired in our TCP model and onl$

the actual aria)les >pi: Ci? are re;uired! The channel rates and packet error pro)a)ilities

are a function of the underl$ing technolog$ that is used& e!g!& adaptie modulation and

spreading!


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TECHNICAL REQUIREMENT

HARDWARE SPECIFICATION

0$stem9 Pentium *@ and a)oe

"am 9 .+ M

%ard disk 9 B/ 7

Monitor 9 8 0@7A color Monitor

SOFTWARE SPECIFICATION

,perating s$stem 9 inux

anguage 9 N0 +


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LITERATURE


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LITERATURE SURVEY

LITERATURE SURVEY

Numerous approaches hae )een proposed in the literature to optimize TCP performance

in wireless networks! These approaches can )e )roadl$ categorized as either TCP

enhancement approaches or link-la$er optimization approaches! The framework

presented in this a link-la$er optimization approach that& rather than modif$ TCP to

adapt to "# d$namics 2as with TCP enhancement mechanisms3& adapts the "# la$er to

TCP d$namics! *n this iew& our work is closer in philosoph$ to preious literature that

optimizes link-la$er parameters like #orward 1rror Correction 2#1C3& Automatic "epeat

re;uest 2A"E3& and "# scheduling to improe TCP throughput!

A model which anal$zed the trade-off )etween TCP throughput and the amount of

#1C added )$ the link la$er! The$ showed that there exists a coding rate that maximizes

TCP throughput though the$ onl$ considered channel error losses! 1arlier cases it

conducted a similar stud$ )ut included the impact of signal power and A"E as well! An

anal$tical model of TCP that includes the impact of congestion losses due to a finite

capacit$ channel! The$ used this model to stud$ the impact of )oth coding rate and

processing gain on TCP throughput! All these preious studies& howeer& considered a

static scenario with onl$ a single coding rate! Adaptie coding on the fl$ has )een studied

ia simulations! *n )oth cases& howeer& the scheduler )ehaior is agnostic to


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instantaneous TCP state and is )ased on expressions for the long-term TCP throughput!

%oweer& the$ assumed that the aria)ilit$ is independent of TCP d$namics which is at

odds with the enironment considered here as well as the commercial enironment!

#inall$& the authors of studied optimization of transmission power to maximize TCP

throughput! The$ explicitl$ considered TCP d$namics in the selection of the transmission

power leel! %oweer& the resulting solutions were ;uite complex& re;uiring detailed TCP

state knowledge! #urthermore& our focus is also different from this work since we stud$

the impact of rate adaptation for )oth single and multiple TCP sessions which was not

considered!


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SYSTEM

DESIGN

A s$stem stud$ is conducted )efore deeloping an$ project to know the pros and

cons of existing s$stem! 0uch anal$sis forms a )asis for creating alternatie design

strateg$!

Prob!" D!s#rip$ion%

we motiate the pro)lem and present the s$stem model including assumptions regarding

different aspects of the s$stem operation! #or ease of exposition& we shall use the

CDMA+/// x"TT 56 s$stem as an example of a practical s$stem suited to our

proposed adaptie resource allocation mechanism& although our schemes also appl$

e;uall$ to other wireless s$stems that d$namicall$ adapt wireless channel rates in

response to user sending rates!

*llustration of a cellular hop!


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The a)oe figure depicts the wireless hop in a t$pical cellular network! *t

comprises a )ase station& mo)ile deices& and a )uffer at the )ase station for each user!

The channel scheduler resides at the )ase station 2or in the case of CDMA+/// x"TT&

the ase 0tation Controller3 and determines the rate allocated to each mo)ile session! #or

the purposes of this work& we focus on mo)ile sessions that inole TCP )ulk transfers

on the downlink! The channel scheduler is assumed to hae the a)ilit$ to d$namicall$

assign different wireless transmission rates 2termed channels3 to each user in a sector! #or

example& CDMA+/// x"TT supports fie different rates ranging from F!G to .4!G


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achieed )$ reducing processing gain 2e;uialentl$ shortening the (alsh orthogonal

code3!

This makes them much more suscepti)le to interference compared to low-rate

channels& and conse;uentl$& onl$ a small num)er of users ma$ use a high-rate channel

simultaneousl$! #or example& 4/ users ma$ simultaneousl$ use a F!G-


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made in a judicious fashion that not onl$ accounts for TCP )ehaior )ut is also fair across

users!

Propos!( Sys$!"%

The proposed work motiates the case for TCP-aware d$namic rate allocation as a means

to increase throughput of TCP sessions oer wireless channels! *n order to achiee this

o)jectie& such a scheduler should )e a)le to 3 choose control aria)les such as coding

rate that $ield the optimal set of data rates 2and corresponding #1"s3 from the erspectie

of TCP throughput and +3 set channel rates in a manner that is cognizant of TCP

d$namics! The proposal of a simple scheduler that captures the aforementioned properties

and its anal$sis form the main o)jectie of this project!

The proposed work explore the cross-la$er optimization of MAC and ph$sical la$er

parameters with respect to TCP sending rate

! TCP session from a set of channel rates! At the ph$sical la$er& we explore the set of

channel rates that maximizes TCP throughput!

+! #or a single TCP session& we deelop an anal$tical expression for the stead$-state

throughput of a longlied TCP session in such an enironment! ,ur model explicitl$

captures the dependenc$ of the scheduler on TCP sending rate as well as the impact of

the presence of two distinct rates and #1"s on TCP! 1ach channel transmission rate

results in a different roundtrip time 2"TT3 and #1"! This s$stem is used to stud$ the

)enefits of cross-la$er optimization of the d$namic rate adaptation feature of modern

cellular networks with respect to TCP throughput! *ndeed& a ke$ )enefit of an anal$tical


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model is the significant speedup in the numerical optimization process compared to

length$ simulations! *n some instances studied in this paper& using ns-+ simulations to

find the optimal configuration re;uired seeral da$s of computations& while the same

optimization took just a few minutes using our model!

4! (e demonstrate how the anal$tical expression can )e used to choose "# control

aria)les that maximize TCP throughput! #or example& we identif$ the optimal coding

rates to )e used in each of the two states when coding rate is used to control data rate and

#1"! The model is also applied to determine the optimal spreading factors& which is

representatie of rate control in current CDMA networks! ,ur studies show that

throughput improements on the order of . to +/ percent can )e o)tained for a single

TCP session! #urthermore& most of )enefits of adaptie rate allocation are o)tained with

just two channel rates!

8! #inall$& we stud$ the )enefits of d$namic rate adaptation for multiple TCP sessions in

a CDMA s$stem& in particular the presence of statistical multiplexing gain! (e propose

two multiuser channel allocation mechanisms for such an enironment9 one& which relies

onl$ on coarse TCP d$namics& called 1MPT scheduler& and another which takes more

detailed TCP rate information into consideration& called A(A"1! The )ehaior of the

s$stem under these two schedulers is explored ia extensie simulations oer the space of

input parameters! The results indicate that multiuser channel allocation strategies hae

onl$ a limited impact on TCP& and most )enefits come from d$namic rate adaptation

Mo()!s%

0ingle-Iser 0cheduler


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Multiuser 0cheduler

0ingle TCP session anal$sis

Numerical results


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MODULE

DESCRIPTION


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MODULE DESCRIPTION

Sin'!*Us!r S#+!()!r

The TCP-aware channel scheduler we consider resides at the )ase station! *t is ;uite

similar in operation to the x"TT scheduler descri)ed with the exception that it assigns a

channel rate )ased on the user's TCP sending rate rather than its )uffer content!

0pecificall$& wheneer the TCP sending rate exceeds 2or drops )elow3 the current

channel rate& the )ase station increases 2decreases3 the channel rate 2accompanied )$ the

corresponding #1"& signal power& etc!3! *f the session sending rate exceeds the maximum

possi)le channel rate& the session experiences packet losses due to congestion! As )efore&

we utilize a two-rate s$stem as the reference example! (e note that modern cellular

s$stems hae fie or more modes& i!e!& the$ can support up to fie or more different

channel rates! %oweer& o)taining succinct anal$tical expressions for TCP throughput

een for three rates is ;uite difficult! Moreoer& our simulations show that there is onl$ a

small improement in s$stem performance )$ considering more than two rates!


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The single-user scheduler operates as follows9 The scheduler decides which of the two

channel rates C/ and C are to )e assigned )ased upon the user's TCP sending rate! *f the

TCP sending rate is )elow C/& the scheduler assigns a channel rate of C/& otherwise& it

assigns C! *n other words where J2t3 is the TCP sending rate at time t& and C2t3 is the

assigned channel rate! The motiation for such a scheduler was presented in 0ection !

*ntuitiel$& when the TCP sending rate is small& a lower #1" is essential 2to aoid time-

outs& etc!3! The scheduler can exploit the knowledge of the low TCP sending rate to trade

off channel rate for channel integrit$! At higher TCP sending rates& it is more appropriate

to assign a larger channel rate at the expense of a higher #1"! This is )ecause& een

though packet loss pro)a)ilit$ due to channel errors increases& a larger channel rate

preents packet loss due to congestion& which would hae happened with pro)a)ilit$ one

were the rate not increased& allowing TCP to transmit at high rates for a longer time! (e

note that there are seeral other features of TCP& for example& time-out alues& window

size& sending state& etc!& which could potentiall$ )e utilized to improe upon our proposed

scheduler! *ncorporation of such features howeer& would make the scheduler complex to

implement as well as to stud$! ,ur aim here is to propose a s$stem that inoles minimal

modifications to schedulers used in current technologies like CDMA+/// x"TT and

1@-D,& and can )e studied anal$ticall$! #rom this perspectie& we )eliee that our

proposal to incorporate knowledge of onl$ TCP sending rate satisfies )oth goals!


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Multiuser 0cheduler

*n this section& we propose two flow-leel channel schedulers& which are extensions of

the single-user scheduler descri)ed in the preious section& for channel allocation among

multiple TCP sessions! (e assume that all users hae the same propagation dela$! This is

not unreasona)le since all major cellular networks deplo$ split- TCP 5.6 on the

downlink impl$ing that TCP sessions on the downlink originate at a common prox$ and&

hence& share a common path! A naie extension of our single-user scheduler would )e to

hae a dedicated high-rate channel for eer$ user in the s$stem! %oweer& our anal$tical

and simulation results for single-user s$stem show that the high-rate channel is not full$

utilized impl$ing that such an extension would )e wasteful of s$stem resources& i!e!&

high-rate channels! %ence& we assume that there are onl$ a few high-rate channels as is

the case in CDMA+/// s$stems and propose flow-leel scheduling strategies to

maximize TCP throughput in a multiuser scenario! *n this section& we propose two flow-

leel channel schedulers& which are extensions of the single-user scheduler descri)ed in

the preious section& for channel allocation among multiple TCP sessions! (e assume

that all users hae the same propagation dela$! This is not unreasona)le since all major

cellular networks deplo$ split TCP on the downlink impl$ing that TCP sessions on the

downlink originate at a common prox$ and& hence& share a common path A naie

extension of our single-user scheduler would )e to hae a dedicated high-rate channel for

eer$ user in the s$stem! %oweer& our anal$tical and simulation results for single-user

s$stem show that the high-rate channel is not full$ utilized impl$ing that such an

extension would )e wasteful of s$stem resources& i!e!& high-rate channels! %ence& we

assume that there are onl$ a few high-rate channels as is the case in CDMA+/// s$stems


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and propose flow-leel scheduling strategies to maximize TCP throughput in a multiuser

scenario!

SIN,LE TCP SESSION ANALYSIS

TCP Model

1xisting TCP models t$picall$ assume that the "TT and packet loss statistics are

independent of TCP d$namics in throughput calculations! %oweer& in the wireless

enironment considered in this work& there exists a strong

TCP window size eolution oer a aria)le rate channel! Correlation )etween the

scheduler and TCP sending rate! *n particular& the channel capacit$ C that affects "TT& as

well as packet loss pro)a)ilit$ p are functions of the TCP sending rate! As an illustration&

#ig! + depicts the eolution of window size of TCP in stead$ state when sericed )$ the

proposed TCP-aware channel scheduler! The scheduler assigns rates )ased on the TCP

sending rate and as can )e seen& this in turn affects the window growth rates! *n 0ection G&

we show that ignoring this dependenc$ can result in large errors in throughput prediction!

*n order to tackle the impact of the proposed channel scheduler on TCP throughput& we

use the model deeloped )$ accelli et al! 5K6 for a single fixed rate channel as a starting

point and deelop a model that accounts for the two-rate regime! (e present a more

detailed explanation of our model )elow9


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! (e assume that the TCP ersion is TCP "eno and model the TCP window growth in

stead$ state as a fluid process where the window size grows linearl$ in the a)sence of

loss!

+! The sender is assumed to alwa$s hae data to send and& for anal$tical tracta)ilit$& we

ignore time-outs and slow start!

4! et (2t3 denote the window size of TCP at time t and "2t3 the "TT at time t! *n the

a)sence of a )uffer& if the scheduler is in mode i L /: at time t& we approximate the "TT

"2t3 a "2t3 L "i L a HCi&

where a is the round-trip propagation dela$& is the packet length& and Ci is the channel

capacit$ in mode i!

et J2t3 denote the instantaneous TCP sending rate at time t in )its per second! Then&

J2t3 L (2t3 "2t3

!

.! During congestion aoidance& the TCP window size increases )$ roughl$ one packet

2 )its3 eer$ "i seconds in mode i when there is no packet loss! (e approximate this in

our fluid model with a linear growth rate of L"i! Conse;uentl$& the sending rate grows

at a linear rate of L"+i )itsLs+ in the a)sence of loss! To see this& note the rate of

increase of J2t3 is gien )$

As in 5K6 and 5G6& we assume that the channel losses can )e modeled )$ an

inhomogeneous Poisson process with rate piJ2t3& i /: at time t! K! *f the TCP sender is

not constrained )$ the receier window& then TCP experiences congestion with


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pro)a)ilit$ when its sending rate& J2t3& exceeds C! %oweer& if TCP is constrained )$

the receier window size& the sending rate stops increasing once it reaches the receier

adertised window and it experiences onl$ channel-related losses

T+ro)'+p)$ An-ysis

efore proceeding with the anal$sis& it is worthwhile to discuss an important aspect of the

aria)le rate enironment that directl$ affects the anal$sis& namel$ the )ehaior of the

TCP sending rate at the channel transition points! 0uppose at time t=& J2t3 L C/! The

corresponding window size is gien )$ (2t3 L C/"/! As per the proposed polic$& the

scheduler would then assign a rate of C to the TCP session at time tO resulting in a new

"TT of "! 0ince TCP is a window-)ased protocol& the window size will )e continuous

at the rate transition point! 0pecificall$& we hae

*n other words& the TCP sending rate experiences a discontinuous jump )$ a factor of g

"/L" when the channel capacit$ transitions from C/ to C! 0imilar arguments can )e

used to show that if J2t3 C/ and TCP

#or purposes of anal$sis& we partition the range of the sending rate J2t3 into four

different regions as shown in #ig! 4! The discontinuit$ in J2t3 when the channel rate


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transitions from C/ to C is clearl$ isi)le in the figure! An interesting o)seration is that

)ecause of the discontinuit$& the sample path of J2t3 neer resides in the region C/2C3

NIM1"*CA "10IT0

Packet 1rror Pro)a)ilit$9 The @aria)le Coding Case As mentioned preiousl$& we

assume that the capacit$ Ci and packet error pro)a)ilit$ pi in mode i are functions of the

coding rate =i! %ence& for a gien )it error pro)a)ilit$& the TCP throughput is a function

of the two coding rates& i!e!& J>=/: =?! The relation )etween the capacit$ and coding

rate is straightforward and is gien )$ Ci =i = C=& where C= is the uncoded channel

capacit$! The packet error pro)a)ilit$& howeer& is strongl$ dependent on not just the

coding rate )ut also the coding scheme used! Conse;uentl$& one must either choose a

specific coding scheme& or resort to )ounds on the achiea)le packet error pro)a)ilit$ for

a gien coding rate! ,ne such )ound is the 7il)ert-@arshamo )ound! This was used in

5K6 and we also use it as an approximation! The 7il)ert-@arshamo )ound is a )ound on

the parameters of a code of length and information )it length

exists a minimum %amming distance d )etween an$ two codewords that must satisf$

where d = = L+! 0uch a code can correct at most t )>d = ?L+c errors! %ence& the

a)oe relation )ounds the maximum num)er of correcta)le errors for an$ coding rate! et

pe denote the )it error pro)a)ilit$ for the wireless channel in consideration! 0uppose that

TCP packets hae fixed size of )its! The TCP packets are )roken up into radio )locks


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of size )its for transmission oer the wireless channel! 1ach radio )lock is assumed to

hae < )its of information and > =


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of the coding rate! (e ran +/ simulations with different random seeds for each data point

and the results reported are in the F. percent confidence interal!

*t is worth mentioning that we limited ourseles to low packet error pro)a)ilities in all

the scenarios! The reasons for this are twofold! #irst& TCP is known to perform well onl$

for low packet errors 2less than . percent3& and hence& it represents the region of interest!

The second reason has to do with modeling the packet loss process as an inhomogeneous

Poisson process which is reasona)le onl$ for low packet error pro)a)ilities! *n all the

scenarios considered in this paper& the model matches the simulation results closel$ with

errors t$picall$ less than . percent! To demonstrate the importance of capturing the

correlation )etween TCP and the scheduler as well as the presence of two states& we plot

in #ig! 8 the difference )etween the two-rate model 2which we hae shown a)oe to )e

accurate3 and a single-rate model that takes onl$ one set of parameters due to coding rate

/ into consideration! (e o)sere that there exist regions where there is su)stantial

difference in predicted throughput 2+/ to 4/ percent3! %ence& a single rate model ma$ not

)e alwa$s feasi)le to tune performance in such s$stems!


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FEASIBILITY


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FEASIBILIY STUDY

A feasi)ilit$ stud$ is concerned to select the )est s$stem that meets performance

re;uirements! These entities are an identification description& an ealuation of candidate

s$stems and the selection of the )est s$stem for the jo)!

1conomic feasi)ilit$

Technical feasi)ilit$

ehaioural feasi)ilit$

1conomic feasi)ilit$

1conomic anal$sis is the most fre;uentl$ used method for ealuating the

effectieness of the candidate s$stem! More commonl$ known as costH)enefit anal$sis&

the procedure is to determine the )enefits and saings that )enefits outweigh costs& and

then the decision is made to design and implement the s$stem! ,therwise& further

justification or alterations in the proposed s$stem will hae to )e made if it is to hae an

enhancement to approe!


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T!#+ni#- .!-sibii$y

Technical anal$sis centre on the existing computer s$stem 2%ardware&

0oftware etc3 and to what extend it can support the proposed addition! This inoles

financial considerations to accommodate technical enhancement! *f the )udget is a

serious constraint& then the project is judged not feasi)le!

B!+-/io)r- F!-sibii$y

An estimate should me made of how strong a reaction the user staff is

likel$ to hae toward the deelopment of a computerized s$stem! *t is common


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DESIGN AND

DEVELOPMENT

01 DESI,N AND DEVELOPMENT


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01212 INPUT DESI,N

*nput design is the part of oerall s$stem design which re;uires er$ careful

attention! ,ften the collection of input data is the most expensie part of the s$stem& in

terms of )oth the e;uipment used and the num)er of people inoled: it is the point of

most contact for the users with the computer s$stem: and it is prone to error! *f data going

into the s$stem are incorrect& then the processing and output will magnif$ these error!

*n this s$stem inputs are gien in two wa$s& the 1xisting users can directl$ enter into

the s$stem using login form& and new users hae to register all their details in the

registration form proided!

Put *nput 0creen 0hots here QQQQQQQ

*nput design is the er$ important part in the project and should )e concentrated well as it

is prone to error! The data that are to )e inserted are to )e inserted with care as this pla$s

a er$ important role! *n order to get the meaningful output and to achiee good accurac$

the input should )e accepta)le and understanda)le )$ the user!

.!!+ ,ITPIT D10*7N

,utput design pla$s a er$ important role in a s$stem! 7etting a correct output is a task

that has to )e concentrated& as a s$stem is alidated as a correct one onl$ if it gies the

correct output according to the input!


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Put output 0creen 0hots here QQQQQQ

%ere in this project in all the three da$s of inductions if the emplo$ee has completed all

hisHher input& then the output shows the status as completed or his status will )e pending!


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SOFTWARE SPECIFICATION

N0 is an o)ject oriented simulator! ack end is C eent scheduler! Protocols mostl$ !

#ront end is oTC! Creating scenarios& extensions to C protocols! ,)jects created in

oTC hae a corresponding o)ject in C

Cheap - does not re;uire costl$ e;uipment

Complex scenarios can )e easil$ tested

"esults can )e ;uickl$ o)tained ! more ideas can )e tested in a smaller timeframe

The real thing isnRt $et aaila)le

Controlled experimental conditions

"epeata)ilit$ helps aid de)ugging

Disadantages9 "eal s$stems too complex to model

#eatures of N0-+

Protocols9 TCP& IDP& %TTP& "outing algorithms etc

Traffic Models9 C"& @"& (e) etc

1rror Models9 Iniform& )urst$ etc

"adio propagation& Mo)ilit$ models

1nerg$ Models

Topolog$ 7eneration tools

@isualization tools

1xtensi)ilit$


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0ending data

Create IDP agent

Create C" traffic source for feeding into IDP agent

Create traffic sink

0ending data

Connect two agents

0tart and stop of data

Creating TCP Connections

Create TCP agent and attach it to the node

Create a Null Agent and attach it to the node

Connect the agents

Traffic on top of TCP

#TP

Telnet

*ntroducing 1rrors

Creating 1rror Module

*nserting 1rror Module

Tracing

All packet trace

@aria)le trace

0imulators help in eas$ erification of protocols in less time& mone$ N0 offers support

for simulating a ariet$ of protocol suites and scenarios! #ront end is oTC& )ack end is

C! N0 is an on-going effort of research and deelopment


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SYSTEM

IMPLEMTATION


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SYSTEM IMPLEMENTATION

0$stem implementation is the important stage of project when the theoretical

design is tuned into practical s$stem! The main stages in the implementation are as

follows9

Planning

Training

0$stem testing and

Changeoer Planning

Planning is the first task in the s$stem implementation! Planning means deciding

on the method and the time scale to )e adopted! At the time of implementation of an$

s$stem people from different departments and s$stem anal$sis inole! The$ are

confirmed to practical pro)lem of controlling arious actiities of people outside their

own data processing departments! The line managers controlled through an

implementation coordinating committee! The committee considers ideas& pro)lems and

complaints of user department& it must also consider9

The implication of s$stem enironment:

0elf selection and allocation for implementation tasks:

Consultation with unions and resources aaila)le:


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0tand)$ facilities and channels of communication

TRAININ,

To achiee the o)jecties and )enefits from computer )ased s$stem& it is essential

for the people who will )e inoled to )e confident of their role in new s$stem! This

inoles them in understanding oerall s$stem and its effect on the organization and in

)eing a)le to carr$ out effectiel$ their specified task! 0o training must take place at an

earl$ stage! Training sessions must gie user staff& the skills re;uired in their new jo)s!

The attendance to sort out an$ ;ueries!


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TEST PLAN

UNIT TESTING

A program represents the logical elements of a s$stem! #or a program to run

satisfactoril$& it must compile and test data correctl$ and tie in properl$ with other

programs! Achieing an error free program is the responsi)ilit$ of the programmer!

Program testing checks for two t$pes of errors9 s$ntax and logical! 0$ntax error is

a program statement that iolates one or more rules of the language in which it is

written! An improperl$ defined field dimension or omitted ke$words are common

s$ntax errors! These errors are shown through error message generated )$ the computer!

#or ogic errors the programmer must examine the output carefull$!

(hen a program is tested& the actual output is compared with the expected

output! (hen there is a discrepanc$ the se;uence of instructions must )e traced to

determine the pro)lem! The process is facilitated )$ )reaking the program into

self-contained portions& each of which can )e checked at certain ke$ points !The

idea is to compare program alues against desk-calculated alues to isolate the

pro)lems!


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FUNCTIONAL TESTING

#unctional testing of an application is used to proe the application deliers correct

results& using enough inputs to gie an ade;uate leel of confidence that will work

correctl$ for all sets of inputs! The functional testing will need to proe that the

application works for each client t$pe and that personalization function work correctl$!

T!s$ #-s! no D!s#rip$ion E&p!#$!( r!s)$

Test for all peers All peers should work

without errors!

+ Test for arious peer in a distri)uted

network framework as it displa$ all

users aaila)le in the group

The result after execution

should gie the accurate

result!


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NON-FUNCTIONAL TESTING

This testing used to check that an application will work in the operational enironment!

Non-functional testing includes9

oad testing

Performance testing

Isa)ilit$ testing

"elia)ilit$ testing

0ecurit$ testing


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LOAD TESTIN,


*t is necessar$ to ascertain that the

application )ehaes correctl$ under

loads when S0erer )us$' response is

receied!

0hould designate another

actie node as a 0erer!

PERFORMANCE TESTIN,


This is re;uired to assure that an

application perforce ade;uatel$& haing

the capa)ilit$ to handle man$

identification of we) pages& deliering

its results in expected time and using an

accepta)le leel of resource and it is an

aspect of operational management!

0hould handle large input

alues& and produce

accurate result in a

expected time


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RELIABILITY TESTIN,


This is to check that the serer is rugged

and relia)le and can handle the failure of

an$ of the components inoled in

proide the application!

*n case of failure of the

serer an alternate serer

should take oer the jo)

SECURITY TESTIN,

*t is necessar$ to check that the application's data is secured!

T!s$

#-s! no

D!s#rip$ion E&p!#$!( r!s)$

+

Checking that the user identification is

authenticated

Check whether all the modules are

secured with integration

*n case failure it should not )e

connected in the framework

The integration is successful

WHITE BOX TESTING


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(hite )ox testing& sometimes called glass-)ox testing is

a test case design method that uses the control structure of the procedural design to

derie test cases!

Ising white )ox testing method& the software engineer can derie test cases!


1xercise all logical decisions on their

true and false sides

All the logical decisions

must )e alid

+ 1xecute all loops at their )oundaries and

within their operational )ounds!

All the loops must )e finite

4 1xercise internal data structures to

ensure their alidit$!

All the data structures must

)e alid

BLACK BOX TESTING

lack )ox testing& also called )ehaioral testing&

focuses on the functional re;uirements of the software! That is& )lack testing ena)les

the software engineer to derie sets of input conditions that will full$ exercise all

functional re;uirements for a program! lack )ox testing is not alternatie to white )ox

techni;ues! "ather it is a complementar$ approach that is likel$ to uncoer a

different class of errors than white )ox methods! lack )ox testing attempts to find

errors in the following categories!

T!s$ D!s#rip$ion E&p!#$!( r!s)$


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#-s! no

To check for incorrect or missing

functions

All the functions must )e alid

+ To check for interface errors All the interface must function normall$

4 To check for errors in a data

structures or external data )ase

access!

The data)ase updation and retrieal must

)e done

8 To check for initialization and

termination errors!

All the functions and data structures must

)e initialized properl$ and terminated

normall$


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CONCLUSI

ON

CONCLUSION


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*n this project& proposed techni;ues for optimizing the rate adaptation feature of

modern CDMA s$stems in a TCP-aware fashion! The proposed s$stem adapts its channel

rate in response to the TCP sending rate& allowing it to trade off channel rate and #1" in

a TCP-friendl$ manner! #or the single TCP session case& this project deeloped an

anal$tical model for a two-state s$stem that explicitl$ accounts for the interaction

)etween our proposed scheduler and TCP d$namics as well as the presence of two

distinct regimes in terms of channel rate& packet error pro)a)ilit$& and "TT! The model

was utilized to show how to select either error coding or processing gain in optimizing

the rate adaptation scheme to improe TCP throughput! *mproements of . to +/

percent were o)sered compared to a s$stem that does not exploit rate adaptation!

#urthermore& this project also ealuated s$stems that use three channel rates ia

simulations and o)sered that the$ $ield no significant gains compared to a two-rate

s$stem! #inall$& we extended the rate adaptation framework to multiple TCP sessions in

a CDMA s$stem! *n such an enironment& the num)er of high-rate channels is less than

the num)er of actie users& and thus& the high-rate channels must )e shared in a fair

fashion! This project proposed two channel allocation policies )ased on preemption and

presented extensie simulation results on their performance! This project results indicated

that the rate adaptation feature with selected rate com)inations& rather than the channel

allocation polic$& is affecting the s$stem throughput This project also showed that )$

exploiting statistical multiplexing gain& a s$stem with just a few high-rate channels

achiees per-session throughput close to that of a single-session s$stem with potential

saings in )oth )andwidth and energ$ )udget!


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51/53

BIBLIOGRP

AHY

[6 Telecommunications *ndustr$ Assoc!& T*A 1*A *0-+///&

www!tiaonline!orgHstandardsHsfgHimt+kHcdma+///H& Mar! +///!

5+6

Networks9 A Cross-a$er Measurement 0tud$& Proc! 1ight *nt'l Conf! Passie and

Actie Network Measurement 2PAM '/K3& Apr! +//K!

546 1! Chaponniere& 0!


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5B6 M! orzi& A! Chockalingam& and "!"! "ao& UThroughput Anal$sis of TCP on

Channels with Memor$& *111 V! 0elected Areas in Comm!& ol! B& no! K& pp! +BF-

4//& +///!

5/6 A! Chockalingam and 7! ao& UPerformance of TCPH"P Protocol 0tack on

Correlated "a$leigh #ading D0-CDMA inks& *111 Trans! @ehicular Technolog$& ol!

8F& no! & pp! +B-44& +///!

56

5+6 1! Altman& C! arakat& and @!M!"! "amos& UAnal$sis of A*MD Protocols oer Paths

with @aria)le Dela$& Proc! *111 *N#,C,M '/8& Mar! +//8!

546 M!C! Chan and "! "amjee& UTCPH*P Performance oer 47 (ireless inks with "ate

and Dela$ @ariation& Proc! ACM Mo)iCom '/+& pp! K-B+& +//+!

586 V!P! 0ingh& W! i& and N! am)os& UChannel 0tate Awareness ased Transmission

Power Adaptation for 1fficient TCP D$namics in (ireless Networks& Proc! *111 *nt'l

Conf! Comm! 2*CC '/.3& Ma$ +//.!

5.6 (! (ei& C! hang& %! ang& V!

5F6 M! 7haderi& A! 0ridharan& %! ang& D! Towsle$& and "! Cruz& UTCP-Aware

"esource Allocation in CDMA Networks& Proc! ACM Mo)iCom '/G& pp! +.-++G& 0ept!

+//G!


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5+/6 #!V! Mc(illiams and N!V!A! 0loane& The Theor$ of 1rror-Correcting Codes! North-

%olland& FKK!

5+6 M! 7haderi& A! 0ridharan& %! ang& D! Towsle$& and "! Cruz& UModeling TCP in a

Multi-"ate Multi-Iser CDMA 0$stem& Proc! Networking& Ma$ +//K

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