CHAPTER 1

INTRODUCTION TO MOBILE AD-HOC NETWORKS.

1.0 Introduction:

Wireless communication is undergoing rapid advancements to meet the demands of

current and future trends of communication. Extensive research and development is

being carried out in this field now-a -days more than ever. Unlike wireless networks

which require a fixed infrastructure like a base station and a main station to

communicate, Mobile ad-hoc networks or MANETs are self configuring, self

organizing mobile nodes that participate to form a wireless network without any

existing infrastructure. Each node participating in this type of network acts as a router

by itself and thereby discovers and maintains the routes to other nodes to

communicate over the network. These MANETs are subject to rapid changes in their

mobility and their performance is affected by topological changes. With limited band-

width and power available to these nodes, the performance of these nodes hugely

depends on the type of routing protocol we choose for communication. The routing

protocol has to be dynamic and should adapt to the frequent link changes and route

changes due to the mobility of the nodes. Minimal convergence time of the routing

protocol, its efficiency in using limited power and bandwidth, meeting the demands

of dynamic topological changes is regarded as an efficient protocol (D.B.Jhonson, et

al. (1999). There are many Routing protocols that have been developed for supporting

MANETs but each one of them have their merits and de-merits. In this paper the

author alleviates that the mobility of the nodes, type of traffic used and size of

topology can affect the performance of routing protocol chosen. Dynamic source

routing protocol which operates entirely on demand is chosen to evaluate its

efficiency in various topologies with varying mobility using TCP and CBR traffic

types. The Dynamic source routing protocol is evaluated by comparing various

metrics such as average end to end delay, packet delivery ratio, normalized routing

load, drop in packets etc. by using a discrete event simulator NS-2.

The results obtained by simulating over seventy different

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scenarios show that there are striking differences in the performance of D.S.R. With

the type of traffic and mobility model’s used. The rest of the paper is organized as

follows. Chapter two discusses the literature review contributed in this field. Chapter

three outlines the methodology used in formulating and approach followed to arrive

at conclusions. Chapter four gives out the theoretical background on the working of

MANETS and D.S.R. protocol. Chapter five presents’ results and analysis obtained

and chapter six discusses results and recommends suggestions for future work in this

field.

1.1 Project description:

Dynamic source routing protocol is implemented in a discrete event simulator NS-2,

which can log events that happen in every fraction of a second, this helps to

understand the characteristic differences and performance degrades that bring out

huge changes in performance. A connection oriented traffic TCP which sends out

acknowledgements and requests for successful delivery of packets and a connection

less traffic CBR is sent over D.S.R. with varying mobility parameters in MANETS

to study the adaptability of the routing protocol in dynamically changing

environments. This work can help researchers and developers to choose an apt

routing protocol to be used for traffic on demand and size of topology they operate

in .This dissertation brings out the limitations and in efficiency of MANETS in their

operation and suggests areas of future research which can improve its performance.

Trace graph, software that can graphically generate outputs from trace

files produced by NS-2 for the user to interpret the results generated in effective

manner is used apart from manual interpretation using Grep, Cat and Awk scripts. A

theoretical frame work is developed and is implemented by simulation to alleviate the

performance of this Routing protocol.

1.2 Aims and objectives:

This dissertation aims at proving that, Dynamic changes in link capacities, speed,

topology, traffic and mobility can degrade or limit the performance of on- demand

routing protocol D.S.R. The performance of D.S.R. is evaluated by using NS-2

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Simulator and various performance metrics obtained are analyzed to justify and

evaluate the performance of DSR protocol.

1.3 Project deliverables:

The main deliverables of this dissertation are:

Understand the theoretical possibilities that can improve quality of services in

wireless communication by using MANETS.

To understand key concepts pertaining to MANETS and routing protocols

used in them.

Understand the limitations and performance peaks of Dynamic source routing

protocol in MANETS.

To implement D.S.R in an effective simulation environment NS-2which can

record changes to a tenth of a second.

1.4 Project Justification:

Providing quality of service is a key factor in the field of wireless communication

technologies for the user’s to rely on this technology. When an infrastructure is absent

or when it cannot be provided such as the case with Mobile ad-hoc networks

providing reliable end to end service is essential. When nodes that act as a router by

itself participate in these type of networks the type of routing protocol used plays a

key role in successful delivery of data and is responsible for the quality of service it

attains.

Numerous works have been done in the field of communication over ad-hoc

networks but yet this extensive research failed to answer many underlying problem

TCP which is a major part of the IP protocol stack serves the demand of the wired

internet world but its inability to address the problems in MANETs paved way for

researches to optimize TCP for better performance in MANETs. In this dissertation,

D.S.R. one of the routing protocols used in MANETs are simulated in NS-2 and its

performance in varying topologies with TCP and CBR traffic is simulated to study the

underlying characteristics of MANETs and D.S.R. handling of various traffic types.

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1.5 Project contribution :

This project supports the existing theories and concepts in MANETs and accepts its

efficiency in most cases but a thorough analysis revealed the need for further

optimization of a routing layer protocol and supporting traffic . This dissertation can

prove that topological changes and number of nodes involved can effect the

performance of routing protocol involved and hence can help researches to design an

apt routing protocol and traffic type that can meet the demands of whatever

environment and network parameters in use.

1.6 Mobile ad-hoc Networks:

This section describes the key concepts pertaining to MANETs, which are unique

characteristics in MANETs that are interesting to use and also challenging to develop

a common underlying frame work to support their characteristics.

Fig:1.6 A Mobile Ad-hoc Network.(By author)

A mobile ad-hoc network can be anything from a portable handheld device to a laptop

or in fact any terminal with wireless support.

Dynamic change in topologies: These nodes can move arbitrarily independent of

each other and hence there exists dynamic changes in topologies with fluctuating link

capacities and the parameters can change unpredictably with time (D.Jhonson,1999).

Multi Hop Routing: Since there is no infrastructure, when delivering from one

source to the destination that is out of the direct wireless transmission range, the

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content messages have to be forwarded via one or more intermediate nodes.

Constrained Bandwidth and power: The nodes that participate in MANET

topologies vary and so will have different signal strengths and propagation

parameters . Interferences and attenuation losses further demand more signal strength

which is less practicable .so, an efficient way to utilize these limited resources has to

be developed.

Security issues: Any routing protocol implemented in MANETs assumes that the

nodes are willingly participating in the network and do not maliciously try to collapse

or degrade the performance of the network. This assumption gives rise to many

security threats that MANETs face due to lack of centralized management attacks

such as Black hole, Wormhole byzantine attacks ( P.Goyal; S.Ajith,November 2010).

Typical applications for MANETs include Military battle fields, emergency

services, disaster relief efforts etc. where deploying an infrastructure is difficult and

time taking. There are many existing routing protocols for ad hoc networks that

perform in a unique way in varying implementation scenarios. Any effective routing

protocol should minimize the routing overhead and thus allow more data packets to

utilize the already constrained bandwidth available. The routing protocols in

MANETs can be classified as:

DSR ZRP CHAMP

AODV FSR AOMDV

TORA LANMAR SMR

ABR DSDV RDMAR LAR NTBR

SSBR OLSR DREAM

ROAM (A. Boukerche, 2009).

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Routing protocols in ad hoc networks

Table driven

Hybrid MultipathSource - initiated

Location -aware

The above table gives a hierarchical list of all routing protocols existing in MANETs

Source initiated or reactive or on demand , Table- driven or proactive, Hybrid,

Location aware and Multipath based protocols are the significant classifications .

Of all these protocols this dissertation focuses on Dynamic source routing protocol

which is a source initiated or on-demand routing protocol which is a widely referred

routing algorithm in MANETS.

1.6.1 Dynamic Source Routing Protocol:

This section describes the salient features of D.S.R. that make it a unique and

efficient protocol for use in MANETs.

The Dynamic Source routing protocol is a source- initiated on demand routing

protocol where it allows the nodes involved in the network to be completely self

configuring and self organizing. It is drafted by the MANET working group to the

international engineering task force (IETF) for use in ad hoc networks. Network

nodes participating in this protocol act as a router forwarding and receiving packets

between neighboring nodes, allowing communication over multiple hops to reach

nodes that are not directly with in the range of their signal. As each node joins or

leaves the network or when the link capacity and status fluctuates the route

information is dynamically added or erased on demand.(D.B.Jhonson, D.A.Maltz,

J.Brosch, July 2004). D.S.R works on two main mechanisms,

I. Route discovery

II. Route maintenance .

Route discovery mechanism contains route request (RREQ) and route reply RREP

packets , when a source node wishes to send packets to the destination it broadcasts a

RREQ packet to its neighbors. The RREQ packet is sent out initially with a hop count

of 1 and the hop count is increased gradually once the previous RREQ cannot find a

route to the destination. Every node maintains a Route cache to store Routes they

learn actively or passively and update their caches with available routes . When this

RREQ message finally reaches the destination or reaches a node that has a route to

the destination, that particular node send out a route reply RREP message to the

originator of the packet. The RREP packet contains the complete route to reach the

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destination.

Route maintenance is continuous process where in any node wishing to send packet

to the destination has a route but cannot reach the destination due to link failure or

node unreachable the source node and all the intermediate nodes involved as

forwarders update their route cache with this information. D.S.R checks the validity

of the routes by acknowledgement packets or even by passive acknowledgements by

nodes overhearing packets. When the route is not found and no ack is received, the

node gives out a Route error message RERR. Upon receiving this RERR packet the

source node can utilize an alternative route if found in its route cache or can initiate a

new RREQ to find a valid route.

RREP

RREQ D->E

RREQ C->D

RREP RREQ B->C RREQ

RREP RREP

Fig:1.6.1 Route Discovery and Route Reply in DSR (By Author)

In the illustration given above when a source node A wants to communicate to

destination node E, it sends a RREQ packet to B. When B is not the destination, B

further broadcasts this message and adds its own address into the route cache of the

message packet and so will be the case with C and D. When node E receives this

message it sends a RREP by examining its own route cache to A. RREP can be sent

back on the same route only if the routes are bi-directional. So, when the underlying

MAC is an 802.11 MAC layer which utilizes bi-directional links the links have to be

bidirectional in order to use the same route for an RREP. The destination node has to

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initiate a new route discovery to find its own route to A. The route information is

piggybacked in the RREP packet to avoid a new route discovery at every

intermediate packet.

When the network is partitioned as will be the case when there are a few valid routes

available , each node tries to initiate a new route discovery to find routes and thus

may lead to RREQ broadcasts overwhelming the network. To avoid this, the nodes

follow an exponential back off algorithm to limit the production of repeated RREQ

for the same target node.

Some additional features of Dynamic source Routing protocol that make it a unique

protocol with minimal routing overhead shall be described in this section :

Route caching

Packet salvaging

Automatic route shortening

Increased spreading of route error messages.

Flow Establishment.

1.6.2 Route Caching: A source node that listens ,forwards or overhears any packet it

sends, should add any usable routing information on that packet into its own route

cache .The route used by the source packet or the route contained in a RREP packet

should also be cached but only in the forward state in the case of unidirectional links.

A route can be cached in both directions only if the MAC protocol in use utilizes bi-

directional links for link layer acknowledgements such as 802.11 Distributed

coordinate function.

To avoid the presence of stale routes when sending a RREP

using cached information ,the RREP sender should concatenate itself and the source

route to itself from source node in the RREP packet and verify the route to avoid any

duplicate nodes that might involve in the route path. This operation ensures that there

are no stale routes in the process (D.Jhonson, Y.Hu, D. Maltz, Feb2007).

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1.6.3 Packet Salvaging: This is yet another useful property of D.S.R. algorithm.

When a node receives a packet to be forwarded to some other node and the knows

that the destined forwarding link is broken ,but has an alternative route to the

destination , that particular node instead of dropping the packet it salvages the packet

and adds this new route information into the route cache of the message packet. In

order to prevent salvaging from entering into a loop, endlessly salvaging the packet

the intermediate node should also send a RERR message to the original sender to

indicate that the link is broken and hence the source can stop routing the packet on

that particular path.

The nodes that do not have a route to the destination or can they be

salvaged as mentioned above are maintained in a maintenance buffer to be sent into a

queue to transmit. However, these actions have a time limit after which such nodes

having no route or to be discarded once the buffer reaches its limit.

1.6.4 Automatic Route Shortening: In this technique the source route sent by the

originator can be altered or modified with a much shorter route by an intermediate

node if it overhears a packet not destined to it but has a route to the destination.

Before it modifies the route the intermediate node sends a gratuitous route reply to

the original sender of the packet .

B,C,E,F C,E,F E,F

Fig: 1.6.4

Every node also maintains a gratuitous route table to limit the number of times the

same route being used. This process removes the un necessary overhead information

on the packet.

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A B C E F

1.6.5 Increased spread of route reply packets: Whenever a source node receives a

route error packet in reply for its RREQ, the source node when broadcasting its next

RREQ packet to its neighbors piggybacks this information in the RREQ packet. This

move avoids RREP packets from flooding the network. The neighbor nodes update

their cache before processing this RREQ.

1.6.6 Flow state Establishment: This is an optional feature in D.S.R. that can further

reduce routing overhead in the network. A flow is a hop by hop route to the

destination progressed through the nodes the network , without the need for a source

route to the destination in its route cache. A route from the source to the destination

might have multiple valid paths and the path with the least number of hops to the

destination shall be considered as a default flow to that particular route. The flow

state shall contain the address of the source and destination and any node that does

not have a source route in its header or a flow id set in its header is forwarded along

this default flow for that request (D.Jhonson, Y.Hu, D. Maltz, Feb2007).

1.6.7 Preventing route reply storms: When multiple nodes receive a RREQ and

have a valid link to the destination, there is a possibility of multiple RREP to the

same request to the sender. This results in RREP storms which could cause

unnecessary congestion in the network. To prevent this from happening a node in its

promiscuous mode waits for a time delay before sending its RREP, to check if any

other node sends a RREP with a much shorter route. The delay is defined as:

D = H * ( h-1+r ) ………………………… 1.6.7

Where, D= delay, H = constant delay variable, h = length in number of network hops,

r = Random floating point number between 0 and 1(D.Jhonson, Y.Hu, D. Maltz,

Feb2007).

During the delay time every node can listen for RREP packet to the originator in their

promiscuous mode but when the hop count of the RREP it listens is equal to or less

than the hop count available in its cache, this node stops sending a RREP as it infers

that the sender has a much better route to the destination.

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In order to implement above mentioned features the following data structure has to be

added. It is required to learn about all the types of information that a node maintains

in its cache when it process this algorithm. Any node that participates in D.S.R

routing has the following tables and buffers.

Default flow ID table

Route request table

Gratuitous route reply table

Automatic route shortening table

Route cache

Send buffer

Network interface queue and Maintenance buffer.

Blacklist

Every node maintains all these tables in their caches apart from default timers and for

implementing DSR (D.Jhonson, D.Hu, Y.Maltz, Feb, 2007).

1.7 Methodology Used for Implementation :

A combination of Software resources , rich literature on MANETS, discrete event

simulator NS-2 and an output analyzer for ns-2 traces Trace graph were utilized for

implementing the aim and fulfilling the objectives of this dissertation.

The theoretical concepts of D.S.R are observed and evaluated in practice when

analyzing trace files to note the practical working of D.S.R. and its handling of

packets when the network is at stress.

The methodology is divided into phases and milestones are identified upon

completing each phase, to advance to the next phase.

Phase 1: A thorough review of all the important literature contributed in this field of

MANETS and also for the Network Simulator NS-2 is studied, the gaps and in-

coherence in the writings has been acknowledged.

Phase 2 : A theoretical background has been established to implement the protocol

and Tool command language is developed on top of C++ to design a software

simulation model for the D.S.R. algorithm using NS-2 simulator.

Phase 3: The simulation results obtained from phase 2 are analyzed and interpreted

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using Trace graph – a graphical interface for analyzing raw traces from NS-2 along

with CAT, GREP and AWK scripts.

Phase 4: In this phase, the results obtained are discussed, compared with previous

results and suitable recommendations and conclusions are documented to further

improve the performance of the protocol.

1.8 How this dissertation is organized:

The dissertation is presented in chapters according to the methodology discussed in

the previous section.

Chapter 1 gives an introduction and brief overview on the theory of Dynamic Source

Routing.

Chapter 2 discusses about the literature contributed in this field with information

about the mechanism of TCP and underlying 802.11 MAC distributed coordinate

function working.

Chapter 3 covers the Implementation of Dynamic source routing and the use of NS-

2, along with scripts and resources utilized for analyzing trace files.

Chapter 5 and 6 discusses the results obtained from various simulations and analyzes

the results with conclusions and recommendations for future work.

Chapter Summary: This chapter Introduces this dissertation with an overview on

Mobile ad-hoc networks, states the aims, objectives and deliverables of the

dissertation chosen. Brief theoretical information about Dynamic Source Routing

protocol and its features are discussed. Finally, this chapter concludes by explaining

the methodology used in reaching the aim of the project.

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CHAPTER 2

LITERATURE REVIEW

2.0 Introduction:

To meet the demands of the growing digital world, the quest for new and improved

quality of services and support in the field of wireless communication brought many

theories and solutions through research and development, proposing better

architectures in wireless communication.

Bluetooth, ZigBee, Infrared, Satellite, WI-FI, WI-Max are the several progressive

advancements in this field of communication .Each technology uses a unique

spectrum and bandwidth for data delivery and developed its own support

infrastructure. During emergency operations and disaster relief services establishing

these architectures for communication is a tedious task and at times may not prove an

ideal solution in the given time frame. This is exactly when, the need aroused for a

Dynamic infrastructure communication network , that can organize and support itself

without the need for a fixed infrastructure. Mobile ad-hoc networks served the

purpose though they are in the research and development phase. To progress these

networks into more reliable and commercial use, it is essential to improve the quality

of service these networks provide.

When the network does not have any underlying support, the nodes that participate in

this type of network solely rely on the routing protocol used in the network. Several

routing protocols have been proposed by research groups for use in ad-hoc networks

but all these routing algorithms have their limitations and practical implications in

real networks. To verify the validity of these protocols involves high costs in real time

and hence simulators are developed to test their performances by implementing them

on software (D.Cavin, et al. 2009)

A few research groups such as the CMU Monarch project group implemented test

bed experiments on ad-hoc networks. A majority of the literature available relies on

simulations to test the performance of various protocols. It is to be noted that

simulations are far from being perfect. According to (C.Newport, 2006) most

simulation models make simplifying assumptions about radio behavior to test the

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networks. When it is complicated and costly to conduct experiments on a real time,

the reliance on simulation demands in return a careful scrutiny of the network

parameters being used for simulation and the approach of the simulation.

2.1 Reliability of MANET routing protocols :

Several research efforts have been put on this new paradigm that can establish a

unique proposal and build a platform for a common routing algorithm that can be

used in all environments with all types of traffic models. In spite of these efforts there

are many unanswered questions that prevail, allowing new research methodologies to

be developed for this solution. (D.Binsen,etal.,2009) conducted simulation

experiments on the performance of D.S.R and A.O.D.V routing protocols and

concluded their results that D.S.R. adapts quickly to link changes and topology

changes than A.O.D.V by aggressive use of its link cache and route cache properties

and it outperformed A.O.D.V. in their analysis, but end to end delay parameter with

varying pause time metric gave less predicted results to support D.S.R. (J.C.cano and

P. Manzoni, 2004) presented an analysis result on the performance of TCP and CBR

traffic models in various types of mobility models such as Random waypoint group

mobility (RWG), Random direction group (RDG), Manhattan group mobility (MHG),

sequential group mobility model (SQG). Their findings indicated that group mobility

models have a major impact on the performance of the network and the behavior of

TCP and CBR traffic types in these mobility models is random and fluctuated in an

inherent pattern.

In an implicitly assumed environment where most of the network and

environment parameters are left unchanged, many researchers have simulated ad-hoc

protocols to study the performances. It is hard to copy cat precise real time effects in

a simulation but the reliance of this technology depends on this precision to extract

the exact outputs and study the differences. (C.Newport, 2006 ) simulated a real time

test bed environment on MANETS , where the simulation was carried for months

observed a different subset of the values he predicted previously.

TCP traffic performance over constant bit rate traffic in D.S.R.is simulated, using

Omni directional antennas and random way point mobility model to infer that D.S.R.

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performance with CBR traffic performed better than TCP (P.Bakalis, B.Lawal, 2010).

Load balancing in MANET routing protocols is one of the area that needs spurious

attention. Due to the limited processing capacity and resource availability in nodes,

when the network gets partitioned at times, some of the intermediate nodes play a

crucial role in forwarding packets . It is to be noted that the limited processing power

available may not serve the network demand and would lead to congestion. So, a

routing protocol that can address this problem efficiently is needed in MANETs

(M.Rajabzadech,et.al.,2008).

The performance of TCP in these ad-hoc protocols can be improved by making

modifications to the existing TCP characteristics.

2.2 Back ground information on TCP Mechanism:

The Transmission control protocol is an efficient protocol designed for wired

networks. However, it is found that it performs badly in mobile ad-hoc network

(MANETs). Wired networks have sufficient high bandwidth links, infrequent changes

in topology and low bit error rates. The problem of using TCP in MANETs is the

interpretation of packet loss as congestion by TCP . Unlike cellular networks where

only the last hop of the routing is sent through wireless, MANETs network consists of

all fluctuating wireless links having varying signal strengths.(R.D.oliviera, T.braun,

J2002).

TCP is a greedy mechanism in which the window size is increased until full

capacity of the channel is utilized, when a packet loss occurs it infers the loss as

congestion and reduces its window size and initiates congestion control mechanisms.

When a TCP connection is first initiated, when there is a prolonged disconnection the

size of the congestion window (CWND) is set to one Sender maximum segment size

(SMSS) allowing only one packet to be sent. From then each for each ACK the

CWND is raised by one until the CWND reaches slow-start threshold (ssthresh). This

is called Slow-start mechanism of TCP. During congestion the ssthresh is set to half

of the CWND size.(L.K.Law, 2009).

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During the result of a time out in receiving an ack packet. In TCP it uses two

indications to enable fast recovery . In this phase instead of waiting for an ACK from

a timeout event the sender if receives N DUPACKs2 , the sender can retransmit the

missing packets .

Ssthresh = CWND/2, CWND = ssthresh+3, where 3 is the number of DUPACKs it

receives. After receiving a non duplicate ACK, TCP sets the CWND to sstresh value

and exits from this congestion avoidance phase. This fast recovery mechanism,

avoids the Slow-start phase of TCP from triggering again and enable the traffic to

quickly catch up for transmission (A.Boukerche,2009).

2.3 Problems of TCP in MANETs :

TCP misinterprets route failures as congestion . When a large packet drop occurs in

MANETs due to route failure the packets in the buffer are dropped as a result TCP

starts timeout events and trigger congestion control mechanisms . This increases

convergence times of TCP and degrades routing protocol performance.

TCP considers Wireless errors as congestion. Due to signal fading and interference

effects, the link layer mechanism might fail to recover the link, the TCP receives

DUPACKs and misinterprets the link failure as congestions though there isn’t any and

decreases the window size. This mechanism also degrades performance.

Exposed node problem is another significant problem studied when the underlying

MAC is an IEEE 802.11 protocol. A node which is within the transmission range of

the sender but out of range of the destination. (L.M. Mackenzie, 2009). This arises

interflow and intraflow contention which leads to high transmission delays.

TCP has rather large RTO timeouts to detect that a retransmitted packet is lost during

retransmission. This large waiting time increases the delay and lead to buffer time out

of packets in the maintenance buffer.

To avoid these problems the conventional TCP experiences in MANETs, several

modified versions of TCP have been proposed to work in MANETs. TCP- Vegas,

TCP-Westwood, TCP-Jersey, Split-TCP, TCP-BuS, ATP are some of the significant

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proposals that provided significant improvement.[S.papanastasiou; O.Mohammed

and L.M.Mackenzie, 2009]. Studied the behavior of all different versions of TCP in

MANETs evaluating D.S.R.,AO.D.V and D.S.D.V protocols. The behavior of all

versions of TCP followed a pattern of decrease in throughputs with increased

mobility rates. TCP- Reno traffic performed least compared to all other traffic types

due to MAC layer effects such as hidden terminal effects during routing.

The author (L.Xia, 2007). Conducted a mathematical analysis of TCP

performance in D.S.R and particularly in 802.11 MAC layer mediums. A qualitative

study identified that false route breakages due to RTS failures are mainly due to

hidden terminal effect and wireless channel error. TCP Reno and Impatient- Reno are

investigated using Glomosim simulator and a new datagram oriented end to end

transport protocol has been proposed.

2.4. 802.11 MAC Layer Mechanism and MANETs:

Several authors cited the effect of underlying MAC mechanism and its implications

on MANETs routing protocols. 802.11 MAC layer uses CSMA/CA technique to

avoid collisions in the network. If it detects collision it initiates a random back-off

value before using the channel again.

IEEE 802.11 reports a link failure if it is not able to communicate with another node

in fixed retransmit attempts. It the destination node is in transmission range but does

not respond due to fluctuating behavior which is prevalent in MANETs, then 802.11

MAC prediction of link failure is false. In the later case the system initiates random

backoff and reports route failure and in response D.S.R. updates its cache. This can

generate large routing loads on the network and high delays.

IEEE 802.11 uses Short retry limit (SRL) to detect lossy packets between RTS and

CTS packets and a Long retry limit to detect lossy packets between data and ACK

packets. By default, the value of SRL is set to seven and that of LRL is set to four

maximum retransmission attempts after which the link is detected as failure by IEEE

802.11.(A.Boukerche, 2009).

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In MANETs, it is found that Mobility, Congestion, Interference and Hidden node

terminal problems are the main factors that degrade the performance of MANETS.

Hidden node problem can be handled by 802.11 RTS/CTS mechanisms but Extended

hidden node, Exorted hidden node and Exposed node problems are the ones that

802.11 fails to solve. (G.Bhatia and V.Kumar, Nov 2010).

There are several cross layer mechanisms proposed to solve link failures in MANETs.

A cross layer mechanism is one in which packets lost in MAC layer are sent after a

short delay by the network layer. This reduces delay in the network and need for

congestion control algorithms. Delayed retransmission (DR) and adaptive delayed

retransmission (ADR) are some of the cross layer approaches. It is found through

simulation by the author (G.Bhatia;V.Kumar,Nov 2010) that cross layer scheme delay

is proportional to the number of packets in send buffer. So, they developed an

Adaptive retry limit algorithm (ARL) which tabulates the received signal strength

(RSS) of the node in its cache table. The ARL works by sending maximum retry

attempts during packet loss to the nodes with lowest RSS, minimal retry attempts for

highest RSS and an in between value for the nodes with a medium RSS value. This

has enhanced the performance of D.S.R and A.O.D.V. routing protocols by reducing

the routing load and packet losses due to link failures.

Summary: There are several mechanisms developed at both physical and network

layer level to improve the performance of MANETs, however, the need for a common

solution to all platforms has not been resolved yet. Traffic types, Interference,

Mobility are the main factors that effect the performance of MANETs. A unique

transport layer solution used with Hybrid routing protocols may prove beneficial to

improve the quality of service in MANETs. This chapter discusses the vulnerabilities

in different layers of protocol stack used in MANETs and discussed the effect of

MAC layer used in MANETs.

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CHAPTER 3

SIMULATION MODELLING OF DSR IN NS-2.

3.0 Introduction:

In this chapter a brief explanation of the simulation modeling of D.S.R in NS-2

simulator is discussed. The modeling of D.S.R in NS-2 simulator is significant in

analyzing the results obtained. Precise design architecture is essential to model the

algorithm. The network parameters chosen during simulations should be as close as

possible to real test bed environments to justify the performances.

There are significant state-of-the-art simulators for MANETs that can efficiently

model ad-hoc algorithms. Each simulator has the same underlying algorithm modeled

in a unique way to obtain better performance. NS-2, OPNET-Modeller, Glomosim,

Omnet++ are some of them to name a few. Any simulation model consists of three

phases of operation, 1.Definition of the model 2. Collection of data 3.Experimental

design 4. compiling of the simulation for actual ‘run’.

3.1 Components of a Mobile Ad-hoc network :

A group of Mobile nodes form an ad-hoc network, with wireless transmission

capabilities. The nodes internal architecture is defined in terms of protocol

stack.

Wireless communication occurs in propagation media with transmission and

radio models defined.

The real network is embedded into a topological area, this is defined by the

environment size and structure parameters.

Every node moves inside the defined topological area. Hence, the mobility

pattern of the node has to be defined.

Nodes utilizes onboard battery power, the energy consumption model of a

node has to be defined.

Finally, to generate traffic data traffic generation phenomenon has to be

defined.

19

All the above methodologies give shape to a simulated MANET environment by

using NS-2 simulator. This dissertation focuses on the effect of mobility and traffic

types on MANETs performance

The parameters chosen and methodology implemented is discussed in detail in this

chapter.

Simulator Used NS-2.34 version

Components in NS-2.34 TCL 8.4.18

TK 8.4.18

Otcl 1.13

TclCL 1.19

NS 2.34

Nam 1.14

Xgraph 12

System Configuration Used

for Simulation

Processor Intel(R) dual core

@1.20GHZ.

RAM DDR2: 4GB

Operating system Ubuntu 10.10 (Maverick

version). Gnome: 2.32.0

Disk space 320GB (320MB required

for NS).

Table:3.1 General parameters required for simulation.

The NS network simulator from U.C. Berkeley/LBNL, is an object-oriented discrete

event simulator targeted at networking research and available as public domain. Its

first version (NS- 1) began in 1989 as a variant of the REAL network simulator and

was developed by the Network Research Group at the Lawrence Berkeley National

Laboratory (LBNL), USA.

20

NS uses two languages for its operation and this in turn facilitates its ease of use . It

uses object oriented programming C++ for implementing algorithms that run over

large data and on the other hand , experimenting different scenario's with slight

change in parameters is sufficed by Otcl language. The combination of these

languages uses TclCL as a front end to manipulate simulation parameters which

together gives a faster run time for the simulations.

NS has emerged as a great importance in the field of Network research on MANETs

and also the most used simulator for academic researchers.(K.Fall and K.Vardhan,

2010).

3.2 Mobile Node: The mobile node is a split object implemented in C++ in NS-2. A

mobile node is attached with several additional features to the original ns Node. A

function of a mobile node is to receive a packet, examine it and map it as per the

algorithm defined. The mobile node is implemented in a protocol stack, defining all

the parameters required for its functioning.

3.2.1 Node configuration:

Routing Protocol :

Current version of NS-2 supports five ad-hoc routing protocols Destination Sequence

Distance Vector (DSDV), Dynamic Source Routing (DSR), temporally ordered

Routing Algorithm (TORA), Adhoc On-demand Distance Vector (AODV) and

Protocol for Unified Multicasting through Announcements(PUMA). (K.Fall,

K.Vardhan, 2010).

Routing

protocol

Link

layer

ARP

attached

IFQ

Priority

queue

MAC

layer

Physical

layer

Net- -

interface

Propagation

Model

Wireless

channel.

Fig: 3.2.0 Protocol stack of a Mobile Node (By author)

21

Mobile node

Link layer: Link layer in a mobile node has an ARP node attached to it for address

resolution.ARP converts IP addresses to MAC address and a routing agent like DSR

handles packets to a link kayer. The destination address in the MAC header is set by

this layer.

IFQ (Priority Queue model): An effective queuing technique is essential for un-

interrupted data flow for prioritizing traffic types. A number of queuing techniques

exist such as DropTail, RED, and CMUPriqueue etc.

MAC Layer: An underlying MAC mechanism is essential for any communication.

This dissertation currently uses IEEE 802.11 Distributed coordinate function as the

MAC layer. NS-2 supports TDMA MAC along with the one used by the author.

Network interface: This Physical interface closely approximates the Direct

Sequence Spread Spectrum technique of radio interface model. It records each

transmitted packet with data related to information like the transmitting power,

energy, wavelength etc. This information is used by the radio propagation model to

determine if a packet being received by it has the minimum requirements for Wireless

transmission.

Radio propagation model: There are three types of Radio propagation models in

use in NS-2. Free space model, Two ray ground reflection and shadowing models.

The propagation model follows Friis formulae to calculate the power received. This

dissertation implemented the two ray ground deflection model , it defines a line of

sight between transmitter and receiver in direct path and ground reflection path.

Hence, the power received is given by the equation:

Pr (d) = PtGtGrht2hr2/d4L.-----------------------(3.2.1)

Where, Pt is the power of transmitter; Gt,Gr are the gains of the transmitting and

receiving antennas; ht,hr are the heights of transmitting and receiving nodes and L is

the system loss model for two ray ground L=1. (K.Fall, K.Vardhan, 2010).

22

Antenna: An Omni directional antenna with unity gain is implemented in this

dissertation procedure.

Energy Model: The energy model is a node attribute in NS-2. The nodes are defined

with an initial energy at the beginning of the simulation with a 281.8mW power for

both t to transmitting and receiving. Every time a transmission occurs the energy of

the node is decremented by one. The energy of the node parameters is given as an

input to the radio model to verify the minimum energy requirements of a mobile

node.

Addressing Scheme : Default and hierarchical addressing scheme are available in ns.

The default addressing scheme uses a 32 lower bits for port-id, 32 higher bits for

node-id and one higher bit for multicast. Whereas, the hierarchical addressing scheme

uses 32-bit for port-id and a 32-bit for node-id in 3 levels of hierarchy (10 11 11) and

(9 11 11) for multicast address.(K.Fall, K.Vardhan, May 2010).

Topology: Topology has to defined before the node configuration for the nodes to

parse in the environment. By default flat grid topology model is used by defining the

length and width of the topological area.

3.3 Traffic generation and Mobility:

In NS-2.34 simulator traffic the C++ class agent defines various parameters to a

simulated packet. The source address, destination address, size of packet in bytes,

type of packet, flow id of the packet, flags and a default TTL values are defined by

this agent. NS-2 supports several classes of agents, this dissertation in fulfilling its

aim, utilizes TCP and CBR traffic on top of UDP agent to test the performance of

DSR in MANETs. Traffic generation is facilitated by defining a source and sink

agent and an application like FTP or telnet is set up between them

This dissertation experiments constant bit rate (CBR) traffic which is a connection

less, UDP traffic to TCP traffic using FTP as an application over it in DSR.

23

A sample code is written below, to illustrate the methodology in generating traffic be-

tween nodes.

Fig 3.3 : Traffic Generation in mobile nodes. (L.Xia, 2007).

The code explained above creates a TCP agent, TCP sink and establishes traffic

between them by establishing a flow.

3.3.1 Traffic and Mobility generation for Large Network:

When simulating large scenario’s implementing the methodology as described in

section 3.3 for every node in the network may not prove an ideal way of defining

traffic and is highly time consuming. Hence, NS-2.34, provides traffic generation

script’s that can dynamically set up traffic between nodes by defining all parameters

required. It groups the nodes available into Agent nodes and Sink nodes and can

generate either TCP or UDP traffic between them. Movement pattern for nodes is

given in (X,Y,Z) co-ordinates, where Z=0 ; that is nodes move in a two dimensional

space defined by the topology. (K.Fall,K.Vardhan, 2010, pp.134-159).

3.3.2 Random – traffic pattern generators for MANETs:

Traffic –scenario generation script can define random traffic patterns for nodes in

MANETs in ns-2.34. To create traffic files we need to define the type of traffic

connection, the number of nodes involved, maximum number of connections between

the nodes and a random seed value . In defining CBR traffic we also define the rate of

traffic generation whose inverse value is used to compute the interval between the

CBR packets.

24

The command looks like:

Ns cbrgen.tcl –type $cbr/tcp –nn $num of nodes –seed $ seed value –mc $

maxconnections –rate $ rate of generation > <output file >

Where, nn is the number of nodes involved and mc is the maximum no of

connections between the nodes.

The default packet size is 512B but, this can be altered as per requirement inside the

configuration file cbrgen.tcl. Start times for CBR and TCP are generated with a

maximum value set at 180.0sec and there is no guarantee as to how many number of

sources and sinks can be deployed (M.Griess 2005).

3.3.2.1 Seed: It is important to learn about the seed that is specified in this command.

This is commonly neglected and selected as random for CBR and TCP. The value

seed is defined by L’Ecuyer as the implementation of combined multiple recursive

generator. In ns-2.34 the random generator MRG32K3a is used. Seed in a broad sense

is an independent stream of random numbers. This is used to differentiate between

multiple independent replications of simulations.

It is observed during the course of this dissertation that change in the value of seed

gives unique output parameters each time the same set of values are taken for

simulation .Hence, a detailed overview of seed in ns-2 is studied in this dissertation.

The default value of seed is 12345, the value can be changed and it takes the values

from 1 to MAXINT. For independent streams and to obtain non-deterministic

behavior the seed of default RNG is set to zero (K.Fall and K.Vardhan, May2010;

MarcGries tutorial, VINTgroup).

3.4 Mobility models:

There are various types of mobility model defined . The mobility model specifies the

movement pattern of each node inside the defined topological area. The nodes follow

the model to randomly move within the space.

Random way point model (RW)

Reference point group mobility model (RPGM)

Free way mobility model (FW)

25

Manhattan Mobility model (MH)

These are the significant mobility models that are compatible with ns-2. The mobility

files generated by these tools cab be directly piped into the TCL code and the

simulation can be run.

This dissertation uses the Random way point model for defining the movement

pattern of nodes.

3.4.1 Random way point model:

The random way point model was first proposed by Johnson and Maltz, Oct 1998 to

evaluate MANET routing protocols. It is simple and widely available and acceptable.

Hence, it is widely used for educational research purposes. IN this model, each node

starts from a randomly select one location as its destination as the simulation starts.

The initial position of the nodes is given by the Setdest utility which is explained in

detail in section . It travels towards this destination with constant velocity Vmax chosen

uniformly and is independent of the speeds and mobility of other nodes in the

network.

When the node reaches its destination , it pauses for a given amount of pause

time Tpause specified. Soon after this the node again chooses a random destination and

follows the pattern explained above.

When Vmax is uniformly chosen from [0 Vmax] and Tpause = 0 we can deduce that the

average node speed is 0.5Vmax 2.

By varying the key elements Vmax and Tpause Random way point model can generate

various combinations of mobility patterns can be generated in MANETs.( J.Broch, et

al. Oct 1998).

3.4.2 Setdest tool:

This tool is used to generate positions of nodes and their moving parameters and

directions automatically by executing a command in TCL in ns-2. It generates

movement patterns according to random way point mobility.

This tool is available under ~ns/indep-utils/cmu-scen-gen/setdest directory...

The command is:

./setdest –v 1or 2 -n $num of nodes –p $ pause time –M $ maxspeed –t $ simulation

26

time –x $ maxx –Y $ maxy. > <output file name>

Where, n is the number of nodes, p is the pause time, M is the Maximum speed of the

nodes, t is the simulation time X,Y are the values of the topological area defined. The

initial node positions are generated by this utility in a two- dimensional region.

$ns_ at 3.000000 “$node_(1) setdest <x-co-ordinate> <y-co-ordinate>. <velocity>.

The output of the generated file is stored in the output file name specified and the

values of these patterns are stored by General operations director (GOD), it behaves

as an omniscient observer storing global information about the nodes environment,

position and behavior. It tabs the shortest number of hops required by each node to

reach its destination. It is of the form:

$ns_ at 766.456 “$god_ set-dist 20 5 4”, this information is used by the object god to

infer that the shortest path between nodes 23 and 5 has changed to 4 hops at time

766.456.

The tools explained in the above sections play a key role in this dissertation and are

used to justify the performance of DSR in MANETs.(K.Fall,K.Vardhan, 2010;

M.Gries, 2005).

3.5 DSR. Algorithm Implementation:

The DSR protocol implemented in ns-2.34 is available at ~ns/ns2.34/DSR/dsr.cc and

dsr.h. The default parameters of DSR can be altered and tested from its configuration

file. DSR routing protocol has two main mechanisms as discussed in section 1 . The

DSR handling of packets to be sent to the destination is illustrated as a flow chart for

the convenience to the audience of this dissertation.

27

DSR protocol Transmission of data packet :

Fig : 3.5.1 DSR data transmission (By author, A.hassan,2008).

3.6 Benefits and Limitations of DSR:

DSR uses no periodic updates, it is a source driven protocol which reacts

quickly to the changes in environment. This reduces un necessary network

overhead, battery power consumption and effective utilization of the channel

for data.

It defines the route in the header of an ongoing packet. Hence, it does not

require a routing table

Route caching can reduce further route discovery overhead. A single route

28

discovery can learn many routes to the destination ,during the process the

intermediate nodes can reply from their local buffers.

Extended propagation of route error messages can ensure there are no stale

routes present with the neighbor nodes.

DSR can use unidirectional or bi-directional links for data and ack packets. If

the underlying MAC is an 802.11 DCF DSR uses bi-directional routes.

DSR supports symmetric and asymmetric links for its operation .This

behavior ensures that the protocol can work well in a link fluctuating

environment.(A.tuteja, R.gujaral, S.Thalia, 2010)

3.6.1 Limitations:

According to IETF documentation on DSR, the protocol is designed

for only 200 nodes and thus is not scalable for large networks.

The route maintenance procedure cannot locally repair a broken link.

Hence, the protocol consumes more processing times in case of

congestion

Packet header size grows in length due to source routing.

Route request floods might potentially overwhelm the network with

network traffic and cause collisions.

Route reply storms are a major concern in this routing method.

Intermediate nodes replying from their local caches gives rise to this

problem

The presence of stale routes in the network has to be prevented.

Chapter Summary: This chapter discusses about the NS-2.34 simulator in detail. All

the components involved in MANETs are explained in detail. The configuration

parameters are discussed in depth and are given a detailed analysis. Various mobility

models were discussed and special focus has been put on the node configuration and

traffic generation methodologies as these parameters play a key role in justifying the

parameters of the DSR protocol in this dissertation. Next chapter presents, analyses,

interprets and justifies the outputs obtained during the course of this dissertation.

CHAPTER 4

29

RESULTS AND ANALYSIS

4.0 Introduction:

The methodology discussed in previous sections of dissertations is implemented to

generate the results presented in this chapter. A detailed logical and theoretical

analysis of the results is documented. Over seventy different simulations have been

carried out. The results obtained from Trace files in NS-2 are fed into a trace graph

analyzer tool Trace Graph to generate simplified outputs from the ASCII format of

the trace files obtained. Apart from using software, AWK scripting, GREP and CAT

commands in LINUX environment are used to pipe out required outputs from traces.

Network animator (NAM) version 1.14, which is an optional component of NS-2 is

used to animate the network and nodal behavior in the network. Nam tool replicates

nodes, traffic, topology and network information and provides monitoring support.

Trace graph tool, which can generate graphs about several metrics of network

performance, simplified the work of the author and hence, more time was spent in

analyzing the results rather than trying to create to readable output formats from

traces.

The output of a NAM generated from trace file is illustrated below:

Fig: 4.0 Route Discovery Fig: 4.1 Packet Dropping

4.1 Simulation Set up:

30

The dissertation aims at evaluating the performance of DSR in a 100*100 and

500*500 topological area with 50 nodes as a constant metric. Hence, the number of

Mobile nodes nor the topology is left unaltered throughout the simulation procedure.

In both topological area’s TCP and UDP traffic is utilized as traffic within the

network to evaluate the packet handling features and limitations of DSR routing

protocol.

Ns simulator version 2.34 is used for simulating the above scenario’s. As explained in

section 4.2 and 4.3 traffic generation tools like cbrgen and setdest utilities were

implemented.

Common Parameters chosen for all Simulation’s:

Simulator version. NS-2.34

Operating system Ubuntu 10.10 version

Topology size 100*100 and 500*500

area.

Channel Wireless

Traffic TCP and CBR

MAC Layer IEEE 802.11 DCF.

Packet size 512bytes

Bandwidth 2Mbps

Traffic rate (CBR) 0.25packets/sec

TCP window size 32

Antenna Omni directional

Mobility Random way point

model

Nodes 50

Simulation run time 300 seconds

Table: 4.1

The common parameters are left un -altered so as to provide linearity between all

scenarios. Energy and power models in ns were not changed and the default values of

31

281.8mW power for transmission and reception is used. A comparative analysis

between 100*100 and 500*500 topologies is documented. Various performance

metrics were considered to justify the performance of the DSR routing protocol.

DSR parameters chosen during simulation:

IFq type CMUPriQueue

IFq length 50

Send buffer time out 30 seconds

MaxrequestRexmt 16 retransmissions

Route cache timeout 30seconds.

GratReplyHoldoff time 1 second

Max salvage count 15 salvages

Default flow timeout 60

Table: 4.1.1

4.2 Performance metrics chosen for Evaluation:

Packet Delivery Fraction: This is defined as the ratio between the number of

delivered packets at the destination to the number of generated packets by CBR or

TCP traffic in this analysis.

Average end-to-end delay: There are possible delays caused by buffering during

route discovery latency, queuing at the interface queue, retransmission delays at the

MAC, propagation and transfer times. Once the time difference between every CBR

packet sent and received was recorded, dividing the total time difference over the

total number of CBR packets received gave the average end-to-end delay for the re-

ceived packets. This metric describes the packet delivery time: the lower the end-to-

end delay the better the application performance (K.Lego et.al.,2009).

Normalized routing load: This is defined as the number of routing packets transmit-

ted i.e. sent and forwarded per data packet delivered at destination. Each hop-wise

transmission of a routing packet is counted as one transmission.

Maximum end-to-end delay: The metric computes the maximum delay experienced

32

by a packet traversing from source to destination in the network. (K.Majumder,

S.K.Sarkar, 2010).

In addition to these metrics packet drops and packet loss is computed. These loses are

due to several transmission time outs, buffer overflows, destination un-reachable etc.

4.3 SCENARIO: 1

Topology Area: 100 *100; Number of Nodes = 50; Max connections = 25

Traffic = CBR; Speed = 10.m/sec; Uniform speed; Simulation time: 300

Pause Times (Uniform): 0; 10; 20; 30; 100; 200; 300. (seconds)

PAUSE

TIMES

Sec.

MAX. END

TO END

DELAY

Sec.

AVG. END

TO END

DELAY

DROPPED

PACKETS

LOST

PACKETS

NORMALIZED

-ROUTING

LOAD

PACKET

DELIVERY

RATIO

(%)

0 0.08031 0.0088 0 0 0.00139 99.99

10 0.06137 0.0087 0 1 0.00140 99.99

20 0.09147 0.0088 0 2 0.00140 99.99

30 0.07885 0.0088 0 0 0.00131 100.00

100 0.093863 0.0088 0 1 0.00140 99.86

200 0.0979 0.0088 3 0 0.00211 99.99

300 0.10417 0.0088 0 2 0.00140 99.99

Table 4.3

Pause time 0 seconds gives continuous mobility factor to the nodes, the nodes move

towards random destinations throughout the simulated time whereas, pause time of

300 sec in a 300sec simulated scenario means the nodes are constant without any

movement throughout the time. This behavior is common to all scenarios and all

simulations in this dissertation.

Analysis: The performance metrics chosen can help us to evaluate the performance

of the network in every layer of the protocol stack. Normalized routing load and

33

packet delivery ratio (pdr) shows the efficiency of the routing protocol chosen.

Packet delivery ratio: In case of CBR traffic the protocol delivered almost all

originated data packets at around 99.86- 100.00% The number of sources is set at 25

and the PDR value obtained shows that DSR performed at its best when the traffic is

CBR and number of sources is low.

Maximum end-to-end Delay:

End-to-end delay may occur due to delay caused during at any level in the network.

Although the delay in seconds is sufficiently low for DSR to perform better in this

scenario, the recorded delay if observed has a co-relation to the number of lost

packets. So, it can be inferred that lost packets are due to the nodes having no route to

reach the destination, DSR waits for a time called MaxmainRexmt after which the

packet is dropped. The RTT time increases which causes sufficient delay.

PAUSE TIMES

0 10 20 30 100 200 3000.00500000000000002

0.00600000000000002

0.00700000000000002

0.00800000000000002

0.00900000000000002

0.01

0.008800000000000030.0087000000000

00010.0088000000000

00030.0088000000000

00030.0088000000000

00030.0088000000000

00030.0088000000000

0003

Average End to End delay versus pause times

Pause time(sec)

Aver

age

end

to e

nd d

elay

(sec

)

Topo = 100 *100 ; nodes = 50;traffic = CBR; simulation time : 300sec.

Traffic = CBR

Fig: 4.3.1

Average end-to-end delay: In this scenario the average end-to-end delay follows a

34

constant pattern at 0.088 seconds whatever be the mobility. It is for this reason that

Maximum delay is also taken into consideration.

Dropped and Lost Packets: The dropped and lost packets are considerably low in

this scenario with a 99.99 to 100% of PDR recorded.

PAUSE TIMES

0 10 20 30 100 200 3000

0.0005

0.001

0.0015

0.002

0.0025

0

0.00139000000000001

0.0014 0.00140.0013100000000000

1

0.0014

0.00211

0.0014

Normalized Routing Load versus pause times

Pause time (sec)

Nor

mal

ized

Routi

ng Lo

ad

Topo = 100*100 ; nodes = 50;traffic = CBR; simulation time : 300sec.

Fig 4.3.2

Normalized routing load: The normalized routing load is the number of routing

packets generated per traffic received by agent. At pause of 200 sec the load increased

to 0.0071 and also three packet drops were recorded. The fluctuating nature of the

links in MANETs due to nodes moving apart can be observed. This tells us that the

network is sufficiently partitioned during 200 pause time and recorded a

comparatively high NRL.

35

4.4 Scenario: 2

Topology: 100 *100; Nodes = 50; Max Connections = 25;

Traffic = TCP; Speed = 10.m/Sec; Simulation Time: 300; Pause times (Uniform): 0;

10; 20; 30; 100; 200; 300. Seconds

PAUSE

TIMES

(Sec)

MAX. END

TO END

DELAY(sec)

AVG. END

TO END

DELAY

(sec)

DROPPED

PACKETS

LOST

PACKETS

NORMALI

ZED

ROUTING

LOAD

PACKET DELIVERY

RATIO (%)

0 82.992 1.5384 839 2388 0.11822 98.58

10 76.7843 1.7472 663 2355 0.0545 98.89

20 46.362 1.5266 892 2396 0.02914 98.75

30 61.304 1.64687 741 2144 0.0561 98.76

100 39.411 1.62142 711 2178 0.0664 98.87

200 72.535 1.8481 731 2405 0.0715 98.92

300 108.974 1.401 650 2196 0.0372 98.96

Table: 4.4

Analysis:

The end-to-end delay parameter recorded an increase in delay with tcp as traffic

source. As the pause time increases the Avg.delay decreased but, the max.end-to-end

delay value is caused due to the presence of delay spikes during simulation. The delay

fluctuations are large and degraded performance of the network.

The delay caused is justified by the value of drop and packet loss; if a retransmitted

packet is lost, the TCP sender waits for time called RTO. The RTO doubles each time

a transmission attempt is made .The extended waiting times can cause spurious

delays and degrade DSR performance.

36

PAUSE TIMES

0 10 20 30 100 200 3001

1.2

1.4

1.6

1.8

2

1.5384

1.7472

1.52661.64687 1.62142

1.8481

1.40099999999999

Average End to End delay versus pause times

Pause time(sec)

Aver

age

end

to e

nd d

elay

(sec

)

Topo = 100 *100 ; nodes = 50;traffic = TCP; simulation time : 300sec.

Traffic = TCP

Fig : 4.4.1

Normalized routing load and PDR: The packet minimum delivery ratio is at during

low pause time of zerosec, at 98.58% and the maximum value is at 300sec pause and

is 98.86%. In spite of delay recorded since TCP is a connection oriented reliable

protocol it could deliver most of the packets to the destination at the expense of high

delay times. The decrease of NRL with respect to increase in pause times can also be

observed.

PAUSE TIMES

0 10 20 30 100 200 3000

0.020.040.060.08

0.10.120.14

0

0.11822

0.05450.02914

0.0561 0.0664 0.07150.037200000

0000001

Normalized Routing Load versus pause times

Pause time's

Nor

mal

ized

Routi

ng Lo

ad

Topo = 100*100 ; nodes = 50;traffic = TCP; simulation time : 300sec.

Traffic = TCP

Fig : 4.4.2

The increase in NRL is due to The increase in number of RREQs, the increase in the

frequency to update route cache , frequent change in the number of hops required to

reach the destination.

37

4.5 Scenario 3 :

Topology: 500 *500; Nodes = 50; Max Connections = 25; Mobility: Random Way

Point Model; Traffic = TCP; Speed = 10.m/Sec Uniform Speed; Simulation Time:

300 Pause times (Uniform): 0; 10; 20; 30; 100; 200; 300. (Seconds).

Results:

PAUSE

TIMES

MAXIMUM DELAY

END TO END

AVERAGE

DELAY

DROPPED

PACKETS

LOST

PACKET

PACKET

DELIVERY

RATIO

NORMALIZED

ROUTING LOAD

0 90.3812 1.01343 686 2385 98.987 0.1039

10 107.6964 1.01851 585 2784 99.070 0.0892

20 124.7185 0.99269 581 2721 99.134 0.0409

30 163.6568 1.04729 646 3014 99.022 0.0684

100 55.2897 1.0893 544 1734 99.124 0.0773

200 81.817 0.99076 513 3571 99.272 0.0410

300 42.042 1.30113 452 1007 99.083 0.0296

Table: 4.5.1

Analysis: When using DSR for large topologies it is observed that the network is

subject to partitions at times during simulation. It is observed that TCP performed

better in a 500*500 topology with respect to every parameter than in a 100*100

topology network.

Though TCP performance improved in this scenario, the network is still subjected to

spurious packet drops due to buffer full or nodes unable to find destination within the

MaxHoldofftime.

The packet delivery fraction improved at an average of 0.500 % as compared to

100*100 topology with TCP traffic in the network.

38

Graphs:

PAUSE TIMES

0 10 20 30 100 200 3000.8

0.9

1

1.1

1.2

1.3

1.4

1.013429999999991.01851 0.99269

1.047291.0893

0.99076

1.30113

Average End to End delay versus pause times

Pause time (sec)

Aver

age

end

to e

nd d

elay

(sec

)

Topo = 500*500 ; nodes = 50;traffic = TCP; simulation time : 300sec.

Traffic = TCP

Fig: 4.5.2

PAUSE TIMES

0 10 20 30 100 200 3000

0.02

0.04

0.06

0.08

0.1

0.12 Normalized Routing Load versus pause times

Pause time's

Nor

mal

ized

Routi

ng Lo

ad

Topo = 500*500 ; nodes = 50;traffic = TCP; simulation time : 300sec.

Traffic =TCP

Fig: 4.5.3

There is an increase in the Normalized routing load in 500*500 topology than in the

100*100 topology area. When a network is partitioned due to inefficient load

balancing techniques, some of the intermediate nodes become crucial for forwarding

packets, which increases the network load. When, the buffer size of such intermediate

nodes reaches maximum, it seizes to perform well .Therefore, an increase in NRL is

39

recorded. This is also due to frequent use of RREQ and route cache overhead

increase, which is justified in large topologies.

4.6 Scenario: 4

Topology: 500 *500 area; Nodes = 50; Max Connections = 25; Traffic = CBR; Speed

(Uniform) = 10.m/Sec; Simulation Time: 300sec; Pause times (Uniform): 0; 10; 20;

30; 100; 200; 300.

Results:

PAUSE

TIMES

MAX. END

TO END

DELAY

AVG. END

TO END

DELAY

DROPPED

PACKETS

LOST

PACKETS

NORMALI

ZED

ROUTING

LOAD

PACKET DELIVERY

RATIO

0 38.382 0.819 563 1483 0.0932 97.573

10 24.387 0.3174 509 1379 0.0921 97.497

20 83.635 0.26106 237 1508 0.0100 99.170

30 48.3817 0.98131 147 975 0.0873 99.548

100 18.667 0.2817 484 1273 0.0770 98.032

200 4.97101 0.03483 41 320 0.0370 99.899

300 0.3004 0.01994 7 0 0.0190 99.995

Table: 4.6.1

A drastic change in performance can be observed in a 500*500 topology area

employing CBR traffic. The end-to-end delay metrics showed improvement in

contrast with scenario 3. It can be observed that the delay decreased with increase in

pause times and also the number of lost and dropped packets also decreased.

In this topology area the performance of CBR is better in reducing the network load

and decrease in packet drops. During Low pause times i.e. at 0, 10, 20 pause times.

Packet delivery ratio recorded is lower than that of TCP in a 500*500 topology but

during high pause times CBR performed better than TCP.

40

Graphs:

PAUSE TIMES

0 10 20 30 100 200 3000

0.2

0.4

0.6

0.8

1

1.2

0

0.819

0.3174000000000010.26106

0.98131

0.2817

0.03483 0.01994

Average End to End delay versus pause times

Pause time (sec)

Aver

age

end

to e

nd d

elay

(sec

)

Topo = 500*500 ; nodes = 50;traffic = CBR; simulation time : 300sec.

Traffic = CBR

Fig: 4.6.2

From the packet delivery ratio it can be inferred that CBR traffic being a connection

less protocol does not guarantee successful delivery of packets as opposed to TCP

which is more reliable in providing this metric. The high pdr ratio’s of TCP come at a

cost of increase in delay which is unacceptable.

PAUSE TIMES

0 10 20 30 100 200 3000

0.020.040.060.08

0.1

0

0.09320000000000010.0921

0.01

0.08730.077

0.0370.0190000000000001

Normalized Routing Load versus pause times

Pause time's

Nor

mali

zed

Routi

ng Lo

ad

Topo = 500*500 ; nodes = 50;traffic = CBR; simulation time : 300sec.

Traffic = CBR

Fig: 4.6.3

The normalized routing load on the traffic has also reduced and it is justified due to

the fact that CBR traffic do not require ack packets for successful delivery

41

confirmation.

This reduces the number of packets received at the agent level which in turn reduces

NRL.

4.7 Comparative Analysis:

A comparative analysis of PDR of both TCP and CBR traffic in large and small

topological areas of 500*500 and 100*100 is plotted for evaluation.

0 10 20 30 100 200 30097

97.5

98

98.5

99

99.5

100

97.573 97.4970000000002

99.17

99.548

98.032

99.899 99.995Packet Delivery Ratio of various Traffic types and

Topologies

500 * 500 TCP500 * 500 CBR100 *100 CBR

Pause tIme's(Sec)

Pack

et D

eliv

ery

Ratio

(%)

Fig: 4.7.1

From, the plot obtained we can derive that:

TCP performance in successful delivery of packets, on an average in large topology is

better than CBR traffic.

In a 100*100 topology area CBR showed peak performance results in all metrics

chosen. Whereas, in large topological area CBR traffic failed to perform well in terms

of PDR, this is because of large number of dropped packets at the buffer and the

unreliable behavior of UDP traffic. But, it can be justified that quality of service with

CBR in MANETs is higher than that of TCP traffic due its low overall end to end

delay.

42

0 10 20 30 100 200 3000

0.5

1

1.5

2

2.5

0.8190.317400000000

001 0.26106

0.98131

0.28170.03483 0.01994

1.01343

1.01851 0.99269

1.04729

1.08930.99076

1.30113

Pause time versus Average End to End Delay

Average End to End delay for CBR Average End to End delay for TCP

Pause time (seconds)

Aver

age

End

to E

nd d

elay

TOPO LOGY= 500 * 500

500*500 TOPOLOGY

Fig: 4.7.2

The average end-to-end delay parameter for 500*500 topology area is also plotted for

the convenience of audience to detect changes occurred easily. TCP traffic

experienced more delay than CBR traffic. The delay spike at pause 30 seconds in

both traffic types is the effect of topology size. The nodes being too far from each

other, the network is subjected to partition and delay is increased. The effect of traffic

type in MANETs can be clearly justified with this statistical analysis.

Chapter Summary: This chapter Presents, analyzes, discusses, interprets and

justifies the results obtained during simulations. The performance metrics chosen for

simulation are defined; the parameters used in simulating DSR in MANETs are

presented and explained in detail. It is concluded by justification that CBR

outperformed TCP when used in DSR protocol in MANETs.

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Chapter 5

Conclusion and Recommendations

5.0 Introduction:

This chapter presents a summary of the results obtained in all simulations and

provides justified analysis on the results obtained during the simulation. The results

observed during this dissertation phase are compared with the results of previous

research’s that studied the performance of DSR in MANETs.

5.1 Problems Encountered During Simulation:

Ns-2 simulator software has compatibility issues with different versions of

GUI in Linux environments.

The performance and run time of simulator ns-2, is limited by the system

resources.

Analyzing raw trace files using AWK and GREP tools posed a challenge to

the author until trace graph analyzer tool is introduced.

The traffic generator script cbrgen.tcl in ns-2 cannot guarantee the number of

sources and sinks that can be produced

The use of Drop tail queue for DSR during early stages of dissertation didn’t

work and it was later found by research that the default queue type for DSR in

ns-2 is CMUPriQueue.

Trace Graph software cannot load traces more than 70Mb effectively and

consumes more time to process.

5.2 Recommendations for future research:

This dissertation implemented DSR in ns-2 and carried out more than seventy

different simulations using TCP and CBR traffic. During the course of

dissertation the behavior of the routing protocol along with the compatibility

and limitations of DSR protocol and software simulator were experienced.

More research on the security considerations in MANETs have to be

undertaken to make the environment more reliable.

44

TCP ‘s performance in MANETs can be improved by putting further research

in to the use of Hybrid routing protocols which combine the features of

proactive and reactive routing protocols in MANETs.

A new transport layer protocol like TCP can be developed for MANETs which

has features that can better suit MANET environments as well as providing

security.

5.3 Conclusion:

The author presented the behavior of TCP and CBR traffic in DSR protocol in

dynamically fluctuating environments in terms of mobility, speed and quality

of service. Various performance metrics were chosen to evaluate the

performances. The ways to evaluate a MANET environment by a theoretical

and practical methodology has been presented while using NS-2 simulator.

The results obtained demonstrated the weakness of TCP in adapting to

MANET environment. The high delay caused by TCP traffic is due to the

miss- interpretation of link failure as congestion and initiating congestion

control algorithms which increased end-to-end delays in the network.

DSR protocol performed better in small network topologies with low

mobility, with CBR traffic than in large topologies with CBR as traffic source.

This behavior justifies the limitations of the routing protocols described in

IETF documentation on DSR. TCP could provide more reliable delivery of

data packets in large environments (500*500) during high mobility, despite

spurious degradation in performance, increasing overall delay in the

network.The author concludes by detailed analysis that DSR protocol’s

performance with CBR traffic is considerably better than with TCP traffic in

MANETs.

The normalized routing load and overall delay is higher for TCP traffic than

CBR whatever be the mobility and environment. DSR showed significant

performance in small topology area during low mobility conditions.

The results obtained during the course of dissertation can be considered as

reference in optimizing DSR and improving the quality of service in

45

MANETs.

5.4 Updated Gantt chart:

A Gantt chart that represents the work done in the given time frame during the

course and mile stones achieved during the process is included in the report.

Results and analysis phase has been changed over to simulation modeling and

20 days were allocated for developing the methodology. Generation and

justification of results has been allocated to 24 days, a week shorter than

anticipated to catch up with the allocated time. Finally, the dissertation is

finalized for submission on 13 May, 2010.

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