Study and Performance Comparison of MANET Routing Protocols
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i Master Thesis Electrical Engineering Thesis no: MEE 10: 48 September 2010 Blekinge Institute of Techno logy School of Computing 371 79 Karlskrona Sweden Study and Performance Comparison of MANET Routing Protocols: TORA, LDR and ZRP Jia Uddin Md. Rabiul Zasad
Transcript of Study and Performance Comparison of MANET Routing Protocols
Master Thesis Electrical Engineering Thesis no: MEE 10: 48 September 2010
Study and Performance Comparison of MANET Routing Protocols:
TORA, LDR and ZRP
Jia Uddin Md. Rabiul Zasad
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Blekinge Institute of Techno logy School of Computing 371 79 Karlskrona Sweden
This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in ElectricalEngineering. The thesis is equivalent to 20 weeks of full time studies.
Contact Information: Author(s): Jia Uddin E- mail: jia_iiuc@ yahoo.com
School of Computing 371 79, Karlskrona, Sweden
E-mail: [email protected]Examiner: Dr. Patrik Arlos Blekinge Institute of Technology School of Computing
Md. Rabiul Zasad Email: [email protected]
Advisor: Mr. Alexandru Popescu Blekinge Institute of Technology
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371 79, Karlskrona, Sweden E-mail: [email protected]
Blekinge Institute of Technology School of Computing 371 79 Karlskrona Sweden
Internet : www.bth.se/com Phone : +46 455 38 50 00 Fax : +46 455 38 50 57
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ABSTRACT
Ad-hoc network has opened a new dimension in wireless networks. It allows wireless nodes
to communicate with each other in the absence of centralised support. It does not follow any
fixed infrastructure because of the mobility of nodes and multi-path propagations. Link
instability and node mobility make routing a core issue in MANETs. A suitable and effective
routing mechanism helps to extend the successful deployment of MANETs. In this thesis, we
have studied details of TORA, LDR and ZRP routing protocols which are routing protocols
on use in MANET. The effects on the routing efficiencies with a special focus on the pause
time, scalability and node density using throughput, network load, end-to-end delay and
packet delivery ratio as indices of performance evaluation for FTP traffic were observed by
using OPNET 14.0 modular as simulation tool. Based on our observations from literature
and empirical study conducted using OPNET, we have found that among the three protocols,
no single protocol can successfully provide optimum efficiency in different MANET
scenarios.
Keywords: TORA, LDR, ZRP, MANETs.
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Acknowledgements
All respect is to the most gracious, most merciful Almighty, Allah Ar Rahmanur Rahim who
has been guiding us to be here at Blekinge Institute of Technology (BTH), to prepare this
MSc. thesis.
We were really quite fortunate to be acquainted with our respected supervisor Mr. Alexandru
Popescu, and we are immensely grateful for his kind co-operation, directives and valuable
inputs during the period of our thesis work. He has been an oasis of support in carrying
through the grey moments of this endeavor.
Deep respect and gratitude should also be ascribed to our thesis examiner, Dr. Patrik Arlos
and Head of Department, Anders Nelsson for their overall cordial supervision which has
served to improve the quality of thesis work and to make us better students. We want to
extend our heartfelt appreciation to our program coordinator- Mr. Mikael Åsman and student
administrator of international office- Ms Lena Magnusson for their kindness, helpful
support, inspiration, and guides in all aspects during our study period at BTH.
In this special moment, we are deeply mindful of our family members for their precious care,
love, inspiration and sacrifice. Their material provisions, sacrifices, prayers and emotional
support have been quite invaluable during our sojourn in Sweden. Of these, we are very
grateful.
Jia Uddin & M d. Rabiul Zasad
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LIST OF FIGUREs Figure 1.1 Infrastructure based wireless network
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Figure 1.2 Mobile Ad-Hoc Network 10
Figure 4.1 Classification of MANET Routing Protocols
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Figure 4.2 Directed Acyclic Graph
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Figure 4.3 A complete tree diagram of route maintenance in TORA
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Figure 4.4(a) Route creation process in LDR using the successor-path reset 24
Figure 4.4(b) Increase sequence number and send an advertisement 24
Figure 4.5 Example of LDR 26
Figure 4.6 A complete block diagram of ZRP with different components 28
Figure 4.7 A scenario of Bordercasting (low dense network and non-mobile nodes)
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Figure 4.8(a) A Scenario of Bordercasting of node ‘a’ (node density is high and nodes are stationary)
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Figure 4.8(b) A Scenario of Bordercasting of node ‘j’ (node density is high and nodes are stationary).
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Figure 4.8(c) A scenarios of Bordercasting of node ‘q’ (node density is high and nodes are stationary)
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Figure 4.9(a), (b) The scenarios where the nodes are mobile 33
Figure 4.10 A scenario of Selective Bordercasting. 34
Figure 4.11 BRP Query Detection process 35
Figure 4.12 BRP Early Termination process 36
Figure 5.1 A complete overview of designing project in OPNET 38
Figure 5.2 Scenario of Mobile Ad-hoc Network with 25 nodes. 40
Figure 5.3 (a) Packet delivery ratio of ZRP [8], (b) End to end delay of
ZRP [8], (c) Control traffic received graph of TORA, (d) End to
end delay graph of TORA
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Figure 5.4 (a) Network Load of LDR [27], (b) Delivery Ratio of LDR [27],
(c) Data Latency of LDR [27], (d) Network Load of TORA, (e)
Control traffic received graph of TORA, (f) Average Delay of
TORA
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Figure 5.5 (a) Throughput graph of ZRP [31], (b) Average end to end delay
of ZRP [30], (c) Packet received graph of ZRP, (d) Throughput
Graph of TORA, (e) Delay Graph of TORA, (f) Average
received packet graph of TORA
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Figure 5.6 (a) Packet Delivery Ratio of ZRP [18], (b) Throughput graph of ZRP [18]. (c) End to end delay graph of ZRP [18], (d) Throughput graph of TORA, (e) End to End delay of TORA, (f) Average received packet of TORA
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LIST OF ACRONYMs
AODV……………..……………………..……………..Ad-hoc On-demand Distance Vector
ABRP……………………………………….....….Adaptive Bordercast Resolution Protocol
BRP………………………………………......……………..Bordercast Resolution Protocol
BPS……………………………………………….....………………………..Bit Per Second
CBR……………………………………………………..………………….Constant Bit Rate
CLR………………………………..…………………..…...…………………….Clear Packet
DB……………………………………..…………………….....…..Distributed Bordercasting
DUEL………………………………….……………………..….Diffusing Update Algorithm
DSR……………………………………..………………………..….Dynamic Source Routing
DAG.......................................................…...........................................Directed Acyclic Graph
ET……………………………………………..…...……………..……………Early Terminal
FTP……………………………………………..……...…………..……File Transfer Protocol
FDC……………………………………………..………...……..Feasible Distance Condition
FZRP……………………………………………..…………...Fisheye Zone Routing Protocol
GRP………………………………………………..…………....Geographic Routing Protocol
GUI……………………………………………………..……..……..Graphical User Interface
GZRP…………………………………………....Global positioning Zone Routing Protocol
IARP…………..………………………………….....…………....Intra-zone Routing Protocol
IP Address……..………………………………..………………….Internet Protocol Address
IETF……………………………………………………....….Internet Engineering Task Force
LAR……………………………..…………………………....……..Location Aided Routing
LSA…………………………………..………………………..…..Link State Advertisements
LDR……………………………………..……………………….........Label Distance Routing
MAC………………………………………..……………………......Medium Access Control
NDC……………………………………………………………Numbered Distance Condition
NDP…………………………………………………..…………Neighbor Discovery protocol
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NS-2………………………………………………………….………….Network Simulator-2
OPNET………………………………………..……….Optimized Network Engineering Tool
OLSR………………………………………..……..…………..Optimized Link State Routing
OSPFv3……………………………………………….……....Open Short Path First version3
PDR…………………………………………………………..………....Packet Delivery Ratio
QD………………………………..…………………………..……………….Query Detection
QRY……………………………………..……………………....……………….Query Packet
RFC……………………………………………………………………Request For Comments
RREQ……………………………………………………..………..…………...Route Request
RREP……………………………………………………………..…..…………...Route Reply
RERR………………………………………………………………………………Route Error
RIP………………………………………………………..…….Routing Information Protocol
RQPD…………………………………..…………..……….Random Query Processing Delay
RDB………………………………………………...........……...Root-Directed Bordercasting
RADAR……………………………………................................Radio Detection and Ranging
SDC………………………………………………………..….……...Start Distance Condition
TCP……………………………………………………..……..Transmission Control Protocol
TTL……………………………………………………..…………..…………...Time To Live
UDP………..……………………..……………………..……………User Datagram Protocol
UPD……………………..…………………………………..………………..…Update packet
WMN…………………………………………………………………Wireless Mesh Network
WSN…………………………………………………………….....Wireless Sensor Network
Wi-Fi…………………………………………………………..………..…...Wireless Fidiliety
Wi-MAX………………….….…………..Worldwide Interoperability for Microwave Access
ZRP……………………………..…………..………………………….Zone Routing Protocol
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Contents Abstract 1 Acknowledgement 3
List of figures 4
List of Acronyms 5
Contents 7
FIRST CHAPTER 1.1 Introduction 9
1.2 Thesis Outline 11
SECOND CHAPTER 2.1 Review of the State of the Art
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THIRD CHAPTER 3.1 Research Problem
15 3.2 Aim of the thesis
15 3.3 Research Questions
15 3.4 Research Methodology
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FOURTH CHAPTER 4.1 Routing Protocols in MANET 17
4.2 TORA 18
4.2.1 Properties of TORA 18
4.2.2 Functions of TORA 19
4.2.2.1 Route Creation 19
4.2.2.2 Route Maintenance 20
4.2.2.3 Route erasure 22
4.2.3 Conclusion 22
4.3 LDR 23
4.3.1 Working Principle of LDR 23
4.3.2 Route Process 24
4.3.3 Route Discovery 25
4.3.3.1 Initiate Solicitation 25
4.3.3.2 Relay Solicitation 26
4.3.4 Set route of LDR 26
4.3.5 Conclusion
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4.4 ZRP 28
4.4.1 IARP 29
4.4.2 IERP 29
4.4.2.1 Route Discovery in IERP 29
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4.4.2.2 BRP (Bordercast Resolution Protocol)
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4.4.2.2.1 Bordercasting (low dense network with stationary nodes)
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4.4.2.2.2 Bordercasting(High dense network with stationary nodes)
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4.4.2.2.3 A scenario where nodes are in Mobile
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4.4.2.3 Selective Bordercasting 33
4.4.2.4 Adaptive Bordercast Resolution Protocol (ABRP)
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4.4.3 Query Control Mechanism 35
4.4.3.1 Query Detection 35
4.4.3.2 Early Terminal 35
4.4.3.3 Random Query Processing Delay (RQPD
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4.4.4 Conclusion 36
FIFTH CHAPTER
5.1 Simulation Environments of MANET 38
5.2 Modeling of MANET scenarios in OPNET 38
5.3 Impact of Pause time on MANET routing protocols 40
5.3.1 Scenario-1 (ZRP vs. TORA) 40
5.3.2 Scenario-2 (LDR vs. TORA) 42
5.4 Impact of number of node and network scalability on MANET routing protocols
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5.4.1 Scenario-3 (ZRP vs. TORA) 44
5.4.2 Scenario-4 (ZRP vs. TORA) 47
SIXTH CHAPTER 6.1 Conclusion
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6.2 Future Work 51
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1 FIRST CHAPTER
1.1 Introduction Wireless networks have continued to play prominent roles in day to day communication. It
is widely used in military applications, industrial applications and even in personal area
networks. It has been very popular in different applications in view of its different valuable
attributes which includes simplicity of installation, reliability, cost, bandwidth, total required
power, security and performance of the network. But similar to wired networks, it also make
use of fixed infrastructures[7] such as cordless telephone, cellular networks, Wi-Fi,
microwave communication, Wi-MAX, satellite communication and RADAR etc.
Figure 1.1: Infrastructure based wireless network [32].
Nowadays, next generation wireless ad-hoc networks are widely used because of user base
of independent mobile users, need for efficient and dynamic communication in
emergency/rescue operations, disaster relief efforts, and military networks and also for
different applications [3], [22]. The network covers a large geographical area without fixed
topology which may change dynamically and unpredictably. These networks improve the
scalability of the network compared to the infrastructure-based wireless networks because of
its decentralized nature. In any critical scenarios such as natural disasters, military conflicts
etc, ad-hoc network provides better performance due to the minimum configuration and
quick operations [18], [24].
Ad-hoc networks can be classified into three categories depending on their applications:
Mobile Ad-hoc Networks (MANETs), Wireless Mesh Networks (WMNs) and Wireless
Sensor Networks (WSN). A MANET is an autonomous collection of mobile nodes [4];
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these nodes are struggling to cope with the normal effect of radio communication channels,
multi-user interference, multi-path fading, shadowing etc.
Figure 1.2: Mobile Ad-Hoc Network [32].
The design of an optimum routing protocol for MANET is highly complex. The need to
design an efficient algorithm, which will help to determine the connectivity of network
organizations, link scheduling, and routing in such dynamic scenarios, becomes very
important [5]. The efficiency of a routing algorithm depends on the efficient and successful
route computation. Usually the shortest path algorithm is an effective approach to calculate
the optimal route in static networks but this simple idea is not always true in a MANET
framework [21]. Many factors: such as extended power [3], quality of wireless links, path
losses, fading, interference, and topological changes [21] have to be considered for
determining a new route. Networks should adaptively change their routing paths depending
on scenarios at any instance to improve any of these affects [18].
In MANETs, a lack of any of these requirements may degrade the performance and
network reliability. The Internet Engineering Task Force (IETF) - MANET working group is
working continuously to ensure the standard of routing protocols. The working group
standardized the functionalities of IP routing protocols, which are suitable for wireless
routing applications within both static and dynamic topologies [10].
There are three categories of MANET routing protocols: table driven, on-demand and
hybrid. In a table driven protocol , each router may contain one or more routing tables but
these do not exist in on-demand routing protocols. In on-demand, a new route is created
based on demand. Although proactive routing protocols provide high reliability and low
latency in new route decision, these protocols do not perform well in high mobile node
scenarios because of the necessity of maintaining big routing tables for thousands of mobile
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nodes. As a result, routing information cannot update new routing tables and this causes
more traffic overheads and decreases the total bandwidth efficiency [33]. But reactive
protocols also face some limitations as the source node needs to wait for the response of the
sending route request. This culminates into significant delay and reduces the performance in
real time traffics [33]. Hybrid routing protocols integrate the advantages of proactive and
reactive protocols.
1.2 Thesis Outline This thesis report consists six individual chapters. Chapter one contains a brief introduction
to MANET and the currently available routing approaches in MANET. Chapter two deals
with state-of-the-art and provides a background to this work in addition to presenting related
works. The problem statement and project aim with research questions are presented in
chapter three. Chapter four contains detailed working principle of MANET routing protocols
especially LDR, TORA and ZRP. Chapter five presents simulation results with analysis
along with reasons for choosing OPNET modular as a simulator along with working
principles. Finally in Chapter six we make a conclusion of our complete work on the basis of
the theoretical and empirical study with a clear future plan, which will channel future
researchers into probable areas of future researches in this area. Relevant references were
provided to conclude the whole write up.
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2 SECOND CHAPTER
2.1 Review of the State of the Art There has been a lot of research endeavors in the past decade geared towards designing an
efficient routing protocol that is suitable for real time network scenarios in MANET.
Different routing protocols follow different strategies to avoid loop in routing. If destination
node is not available in the network or due to the link failure, routing may culminate into an
infinite loop problem. To ensure loop-free routing, some protocols use destination sequence
number, DAG algorithm (calculating path always in unidirectional) and feasible distance.
Where DSR uses the source route to avoid the loops, TORA uses a link reversal algorithm
and AODV uses a sequence number for each destination. Routing loop and maintenance of
complete reachability are the two factors that directly influence the routing efficiency [27].
In [3] and [6], the performance of AODV, DSR, TORA and OLSR routing protocols were
observed using random waypoint model for different size networks and different network
densities in OPNET. In these research works, AODV and OLSR were shown to have greater
packet delay and network load compared with TORA, while TORA has lower throughput
than AODV and OLSR. In heavy traffic environments and high congestion network
scenarios, AODV works better than OLSR and TORA.
Normally Random Waypoint, Random Walk and Random Directions are used to design a
MANET in different simulators [4]. In Random Waypoint mobility model, AODV protocol
shows the better performance than DSDV and TORA with respect to packet delivery ratio
and end-to-end delay. In high mobile node contexts AODV also shows better throughput
than DSDV, TORA and DSR protocols [4].
OPNET modeler 14.5 is used to investigate the performance of routing protocols OLSR,
AODV, DSR and TORA for various network sizes, node mobility and traffic load [5], [11].
Experimental results show that TORA shows better performance in medium and large-sized
networks under high traffic loads. DSR is well suited for lower node mobility in small size
networks. It also performs better at high node mobility in large networks. AODV was
discovered to perform well in medium-sized networks at high traffic load. OLSR also
performs comparatively better in many cases than others, but its performance suffers and is
degraded when node mobility and traffic load are increased. In similar scenario, TORA
exhibit a decrement in throughput than AODV and OLSR. In AODV, the routing decision is
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taken based on the distance reported with respect to the reply- associated with the destination
sequence numbers. LDR also uses sequence numbers but it is controlled by the destination to
which it belongs. Ordering of nodes is done based on the label to each destination and it
always ensures loop-free routing in any scenarios using the label, which is combine with
feasible distance and destination sequence numbers [25].
For various pause times and in random waypoint model using QualNet simulator,
simulation results show that AODV performs better than DSR and ZRP with respect to end-
to-end delay, packet delivery ratio and TTL based hop count [8]. DSR and AODV display
better performance than ZRP with respect to packet delivery ratio. David Oliver Jorg has
analyzed the performance of AODV, DSR, LAR and ZRP for various sizes of MANETs in
[2]. In small networks, all protocols have shown better performance but AODV supports
higher packet delivery in large network where ZRP and DSR failed completely [18].
A new approach to hybrid routing protocol, FZRP, is introduced, which combines with
zone routing protocol and hierarchical proactive, Fisheye Routing protocol. Normally, it
works on two levels of zone- basic zone and extended zone. This approach offers more
advantages in a lager zone with small increment of maintenance overheads. FZRP shows
better efficiency than traditional ZRP for different zone sizes such as size 2 and size 4 [16].
Geographical routing merges with ZRP in geographical zone routing protocol (GZRP)
[17]. GRP routing is used instead of BRP- based IERP for the maintenance of global route.
Experimental results show that GZRP has performed better with respect to different network
metrics; SD_Query (indicates the number of source to destination queries that were found),
ToT_Number_Successful_Query (total number of successful queries), Avg_Number_Hops
(the average number of hops), Avg_Delay and Avg_Nbr_Query_GRPS (average number of
queries received per nodes using the GPS optimization scheme) in FreeBSD 2.2.7 simulator
[17].
Network simulator, QualNet is used to compare the performance among AODV, OLSR
and ZRP with respect to PDR, end-to-end delay and throughput in different scenarios such as
low density and high density [8], [18]. In low-density environments, AODV shows better
performance in packet delivery ratio. It is Importance to note that variation of CBR does not
affect on packet delivery ratio of AODV, OLSR and ZRP. If the number of nodes increases,
packet delivery ratio of OLSR and ZRP fall down significantly. AODV and OLSR have low
end-to- end delay which is shown to be significantly high in ZRP under similar simulation
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scenario. AODV shows higher throughput in low-density networks whereas ZRP exhibit
lower throughput.
In most of the reviewed works above, researchers considered pause time [8], [22],
[23],[27], [30], network density [2], [3], [31], network size [5], [7], [18],[33], different
mobility models [4], [19] and network traffic [18], [33] individually, in a bid to observe the
effects of these parameters on the performance of existing routing protocols. In our thesis we
are going to observe the effects of these parameters on the performances of TORA, LDR and
ZRP routing protocols. Particular emphasis will be placed on observing three network factors
which are network density, pause time and scalability.
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3 THIRD CHAPTER
3.1 Research Problem The performance of wireless network depends on the different factors such as bandwidth,
power, QoS, routing efficiency etc. Due to the random mobility of nodes and decentralized
nature it is a very challenging issue to obtain better performance in MANETs. Among all
parameters, routing is one of the core factors that have great influence on network
performance. The traditional routing approaches do not always show methods of finding
optimum solution to detecting new routes in such dynamic and adaptive scenarios as being
experienced in MANET. Many MANET routing protocols are already designed and tested
in different simulators; but up till now, no research effort has been able to provide the
optimum routing efficiency to ensure the high network performance. Many factors
including network density, pause time, node mobility, network scalability etc directly have
influence on decision taking in routing. So analyzing the affects of pause time, network
density, node mobility, and network scalability on the performance of routing protocols will
help in designing an efficient routing protocol which is vital issue to improving the
performance of MANET.
3.2 Aim of the thesis The goal of this thesis is to do a detailed study of reactive and hybrid routing approaches
and analyze the performance of MANET routing protocols including TORA, LDR and ZRP
with respect to throughput, end-to-end delay and network load on the aspects of network
scalability, node mobility and pause time.
3.3 Research Questions
• How does proactive routing approach fail to ensure better efficiency in high
mobility of node in MANET scenarios?
• How does reactive approach perform its operations without maintaining big
routing tables for a large network with thousands of mobile nodes?
• In a bid to integrate the advantages of proactive and reactive approaches, how does
hybrid approach perform its operations in large MANETs?
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• How does network density, pause time and scalability affect on the performance of
MANET routing protocols? Does any routing protocol perform better than others
with respect to network metrics?
3.4 Research methodology In Section 3.3 we have mentioned some research questions and we embarked on two
methodologies of approach in a bid to find befitting solutions to these problems. First, we
embarked on a theoretical study and secondly, we tested our intended methods empirically in
a network simulator. By literature review we have gathered knowledge on the involving
factors that have influence on taking decisions in other to create a new route; also, reasons
were given for the performance degradation of proactive routing protocols in high mobile
node scenarios. By studying details on the working principle of TORA, LDR and ZRP, we
have chronicled the knowledge of working approaches of reactive and hybrid protocols,
which are mostly well-suited to MANETs. Comparing the performance among MANET
routing protocols such as TORA, LDR and ZRP with respect to throughput, network load,
delay and observing the effects of network density, scalability and node density on the
performance of routing protocols, we have designed a network model with different
environments in OPNET 14.0. Although OPNET has a lot of attractive features than other
existing simulators, we have faced one limitation in that is it supports only six MANET
routing protocols [34]. As a result we could not check the performance of LDR and ZRP
using OPNET. To complete our task in time we took permission from our supervisor and
thesis examiner so that we can borrow some simulation results of LDR and ZRP from
different other simulators such as QualNet, GloMoSim [9], [27]. We designed same network
scenarios in OPNET for TORA and finally make a comparison among the three protocols
and observed the affects of pause time, network density and network scalability of MANET
routing protocols.
4 FOURTH CHAPTER
4.1 Routing protocols in MANET Many MANET protocols have already been designed and tested in different simulators.
These protocols can be classified in different ways such as being based on network structure
whereby it can be classified as flat routing, hierarchical routing and geographic position-
assisted routing [8], [11].
Figure 4.1: Classification of MANET Routing Protoc In flat routing [23], nodes communicate directly with each other. It can b
three categories such as proactive, reactive and hybrid. Proactive proto
strategies, which are mostly followed by conventional routing protocols. On
is a new emerging technology in ad-hoc networks. Hybrid protocols
properties of both proactive and reactive approaches. MANET routing proto
a rule, do not follow the properties of conventional protocols.
Hierarchical routing plays a prominent role in large networks in which flat r
face constraints. Now-a-days, geographical location information also provid
performance in ad-hoc networks.
MANETs Routing Protocol
Flat Routing
Hierarchical Routing
Geographic Position Assisted Routing
Proactive
Reactive/On-demand
Hybrid
/Table driven
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ols.
e classified into
cols follow the
-demand routing
incorporate the
cols however as
outing protocols
es better routing
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In a proactive scheme, a very small delay is needed to determine the new route but a
significant amount of delay is needed for creating a new route. Pure proactive scheme is not
appropriate for ad-hoc networking environment, because it has to keep the current routing
information in a large network. Hence pure reactive routing protocol requires significant
control traffic due to the long delay and excessive control traffic; as a result it cannot be
implemented in large networks.
Therefore, main focus of our thesis is on on-demand and hybrid routing protocols that are
most suitable in MANET environments than the proactive approach.
4.2 TORA Temporally ordered routing algorithm (TORA) is a reactive routing protocol, which is also
known as link reversal protocol. It is effective in solving the existing limitations of
MANETs. Due to the high mobility of nodes, congestion is one of the major problems in
MANETs. Traditional shortest path algorithm, adaptive shortest path algorithm, and link
state routing cannot work properly in mobile networks. It is difficult to update the routing
tables of dynamic nodes. In TORA, each node broadcasts a query packet and the recipients
broadcast an update packet. It supports the loop-free, multiple route facilities. Using “flat”
non-hierarchical routing algorithm, it also provides better scalability. To discover a new
route, it uses the directed acyclic graph (DAG) algorithm and also uses a set of totally
ordered height values at all times. In this approach, information may flows only in one
direction [19]. Hence it is only unidirectional; there is no chance to fall in an infinite loop. It
performs four basic operations which are route creation, route maintenance, route deletion,
and optimizing routes [20].
4.2.1 Properties of TORA • Distributed routing: each router needs to maintain information about the
adjacent routers only.
• Loop-free routing: the use of DAG ensures that information always flows in one
direction [19].
• Multiple routes are established to improve the congestion [19].
• Minimize the communication overheads to maximize the utilization of bandwidth
[19].
• It provides the support of link status sensing and neighbor’s delivery, reliable control
packet delivery and security authentication.
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In figure 4.2, the source node is ‘a’ and the destination node is ‘g’. Using the DAG, we can
express all possible routes in following ways,
H(a)>H(b)>H(f)>H(g); H(a)>H(b)>H(c)>H(f)>H(g); H(a)>H(c)>H(f)>H(g);
H(a)>H(d)>H(e)>H(g)
f
b a
c g
e
d
Figure 4.2: Directed Acyclic Graph.
4.2.2 Functions of TORA In order to perform the basic operations including route creation, route maintenance and
route erasure, TORA uses three control packets such as QRY, UPD and CLR.
4.1.1.1 Route Creation Two control packets; QRY and UPD that are used to create a new route within the
network. A QRY packet consists of a destination id, which is used for identifying the
destination node. The UPD packet holds destination id and height of the node. Each node
maintains a route-required flag that is initially unset and also maintains the time of broadcast
for last UPD packet. When a node has no directed link and an unset route-required flag
within a network, it broadcasts a QRY packet to its neighbor nodes and set its route-required
flag. When any node receives a QRY packet, then it checks the following conditions [21]:
• If there is no downstream link and route-required flag is unset, it re-broadcasts the
QRY control packet and sets the route-required flag.
• If there is no downstream link and route-required flag is set, it discards the QRY
packet.
• If the receiving node has at least one downstream link with NULL height, it sets its
height and broadcasts an UPD packet.
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• If the receiving node has at least one downstream link with non-NULL height, then
firstly it compares the time of last broadcast of an UPD packet with the time of link
over which QRY packet was received and became active.
• When the link becomes active in a node, it broadcasts an UPD packet and it discards
the QRY packet.
• If the route-required flag is set (when a new link is established) of any node, then it
broadcasts a QRY packet.
When a node receives an UPD packet from its neighbors, it updates the array heights of
entities and proceeds through the following steps:
• If the route-required flag is set, node sets its height and updates all the entities in its
link state array and unsets the route-required flag. Then it broadcasts an UPD
packet with a new height.
• If the route-required flag is not set, it just updates the entities of the link state array
and applies the route maintenance techniques.
4.2.2.2 Route Maintenance In a mobile Ad-hoc network, TORA maintains the route when any topological change has
occurred. It also ensures the re-establishment of a route between nodes within a finite time.
The route maintenance is needed for a node when its height is non-NULL. If any neighbor
node has NULL value, that neighbor node will not be considered for this operation.
To route maintenance, there are five different cases available in TORA, which is shown in
figure 4.3
Case 1: Generate new reference level
Case 2: Propagate the highest neighbor’s reference level
Case 3: Reflect back a higher sub-level
Case 4: Partition detected and
Case 5: Generate a new reference level.
In case 1, due to link failure the node lost its last downstream link. If the node has any
upstream neighbor node, it updates its reference value. Otherwise, it sets its height to NULL.
If the node has no downstream link, it propagates the reference level to its upstream
neighbors, which is shown in case-2. Due to link reversal, if the downstream links fail then
the node reflects back the reference height with setting the reflection bit according to case 3.
21
If the set reference value is equal to the reference height of neighbor nodes, the node has
detected the partition and has started to erase the NULL height value set by the route which
is shown in case 4. In case 5, generation of a new reference value occurs when the node has
experienced a link failure between the time of propagation of a reference level and reflected
sub-level.
Figure 4.3: A complete tree diagram of route maintenance in TORA [21].
Case 2: Propagate the
highest neighbor’s reference level
Node i loses its last downstream link
Was the link lost due to a failure?
Do all of the neighbors have the same reference level?
Case 1 Generate new reference level
Is the reflect. bit(r) in that ref. level set to 1?
Case 3: Reflect back a higher sub-level
Did this node originally define that reference level (oid =1)?
Case 5: Generate new reference level
Case 4: Partition Deleted & erase invalid routers
Y
Y
Y
Y
N
N
N
N
22
4.2.2.3 Route erasure In case 4 of route maintenance, the node sets its height, which is determined by the
direction of edges to the destination and updates all the entries of its link state array and
broadcasts a CLR control packet. When a node receives a CLR packet, it follows the
following procedures [21]:
• If the reference level in the CLR packet is matched with the reference level of that
receiving node, the node sets its height and sets the height of each neighbor to
NULL. It also updates all the entries in the link state array and broadcasts a CLR
packet.
• If the reference level of the CLR packet does not match with the reference level of
the node, it sets its height of each neighbor. And also updates the entries of
corresponding link state array. At the end the height of each node, which was
partitioned, is set to NULL and erase all the invalid routes within the portion of
network.
4.2.3 Conclusion We can summarize the following characteristics of TORA:
• TORA follows the link reversal algorithm to perform its operations.
• TORA does not require a periodic update.
• To find out a new route, it uses a DAG (Directed Acyclic Graph), which is rooted
at the destination.
• TORA uses three different control messages. It uses:
§ QRY for creating a route.
§ UPD for both creating and maintenance of routes.
§ And CLR for erasing a route.
• When the l i n k f a i l s to re-compute a DAG , it uses the Link Reversal Algorithm.
• To create a new route it follows the on-demand approach and based on-demand it
calls a DAG.
• It has multi-path routing structure.
23
4.3 LDR Label Distance Routing (LDR) protocol is an on-demand routing protocol. In case of on-
demand routing protocols, Count to Infinity problem is an important issue. This problem
occurs when the routing falls in infinite loop due to link failure or absence of destination
node within the network. To avoid this problem it uses destination sequence numbers. It
uses this sequence numbers in such a way that destination node needs to reply fewer RREQs
[26]. Two parameters are used to perform the operations: destination sequence number and
feasible distance (the lowest known distance from a router to a particular destination). Both
are used to reset the distance to a destination node, which allows a node to accept the next
hop to report a distance larger than the node’s feasible distance. Smallest distance to a
destination node is retained by a node of its current sequence number for finding out the
destination. In LDR, ordering of nodes is done based on the label of each destination, where
the label contains value of feasible distance. An important property of LDR is that it ensures
always loop free properties [25]. To overcome the limitations of sequence numbers, it uses
distance label. It uses two unique parameters- feasible distance of DUAL and sequence
number similar to AODV.
4.3.1 Basic working principle of LDR To perform the basic operations, it uses three-control packets- Route Request (RREQ),
Route Reply (RREP) and Route Error (RERR). It assumes that all links have equal unit cost
and it finds the minimum hop through the network by using the available information. To
perform the basic operations, it uses two terms which are advertisement and solicitation.
Advertisement is used to identify the portion of a packet that can be faithfully delivered to
the destination and solicitation is utilized for identifying the portion of a packet that requests
for the information about a destination [28]. RREQ is the tuple {dst, sndst, rreqid, src, snsrc,
fd, dist, flags}, where src is the identifier of a source which is seeking the path to the
destination with identifier dst, snsrc and sndst which are used for sequence numbers of
source and destination node respectively. To control the flooding, it uses rreqid (source-
specific unique identifier). Feasible distances, distance of traverse path of RREQ and control
bits are expressed by fd, dist and flags respectively. RREP tuple {dst, sndst, src, rreqid, dist,
lifetime, flags}, where lifetime is in milliseconds of time remaining for the route to dst. If
‘D’ is a destination node for which node ‘A’ has a route, it maintains a sequence number
organized by D which is and distance to D is , feasible distance to D is and a
current sequence number is expressed as .
4.3.2 Route Process By using solicitations and advertisements, LDR protocol discovers the most reliable
routing path within a network. It always ensures the loop freedom environment using labels
that follow a strict partial order. These labels come from non-negative integers, which form a
sparse with label set. This dynamic routing protocol is continuously re-labeling the portion
of the graph so that it can adapt with changing the node positions. One of the key limitations
is to generate re-label of nodes in dynamically changing topology. To handle such kind of
problem, LDR uses a re-label sub- graph as a successor-path reset; this provides a feasible
advertisement [27].
The figure 4.4(a) shows that a portion of network has out-of-order path. Node ‘A’ issues a
request RREQ for a destination node ‘D’. Hence the sequence numbers are same and B’s
feasible distance is not less than A’s, the RREQ moves to node ‘B’ which is out-of-order
with respect to node ‘A’ for destination node ‘D’.
•
Figure 4.4(a): Route creation process in LDR
As a result it is not possible to create a route {A, B,
relays RREQ. Node ‘C’ is a feasible successor to ‘A’ a
T bit is set and node ‘C’ must relay the RREQ because
path reply.
Figure 4.4 (b): Increase sequence number and
A B
sn=6 d=3, fd=3
sn=6 d=2, fd=2
sn=d=1
A
A B C D
RREQ
sn=5 d=2, fd=2
sn=5 d=2, fd=2
sn=5 d=1, fd=1
sn=5 d=0, fd=0
T T
24
using the successor-path reset [27].
C}. B sets the set-required T bit and
nd could reply with a loop-free path.
of an out-of-order condition along the
send an advertisement [27].
C D
6 , fd=1
sn=6 d=0, fd=0
25
When the node ‘C’ relays the RREQ, it converts the broadcast packet to a unicast packet
and sends it directly to a destination node ‘D’. After that, node ‘D’ will increase its sequence
number and will send an advertisement, this is shown in figure 4.4(b).
4.3.3 Route Discovery
If RREQ or RREP does not follow the order of feasible distance, RREQ unicasts to the
destination node and increases its own sequence number. Then RREP resets the feasible
distance to maintain the proper order. The node which unicasts the RREQ to the destination
node along the path (the path which has satisfied loop free conditions without considering
the T bit), ensures that RREQ has adequate TTL in order to reach the intended destination
[27].
A given node ‘A’ enters into a route computation for a destination node ‘D’ when it issues
a solicitation for ‘D’ with an identifier IDA. The active node ‘A’ for ‘D’ in computation is
(A, IDA). The computation (A, IDA) will be ended when node ‘A’ will receive any feasible
advertisement for the node ‘D’. If node ‘A’ receives a feasible advertisement for ‘A’, the
computation will be considered as success otherwise it will be treated as failure. If node ‘A’
relays the solicitation, it participates in the computation (A, IDA) and hold data for a period
of time, which is known as engaged in (A, IDA). A relay node records a tuple {A, IDA,
lasthop} where lasthop indicates the previous hop of node participating in computation. A
node may be engaged with different computations but can only enter in the engage state
during computation (A, IDA) at a particular time [27]. A node is known as passive node,
which is neither active nor engaged in a computation. This state is also considered as a
default state of any node.
4.3.3.1 Initiate Solicitation When a node needs to establish a route for a destination node, it first checks the status of
the node by assessing whether the source node is active or not. If the source node is not
active, it changes its status by updating rreqid. Let IDA is an incremented identifier and node
‘A’ issues a solicitation for a node ‘D’ which is identified by (A, IDA) along with a timer
expiry, where t=2. If the timer has expired, node ‘A’ retries to send solicitation, increasing
the TTL based on network policies. If node ‘A’ fails to find out a route to the destination
node ‘D’, node ‘A’ informs the packet origin about the failure and the packet is subsequently
dropped [27].
4.3.3.2 Relay Solicitation Let us consider a node ‘B’ receives a solicitation (A, IDA) for a destination node ‘D’. First
it checks whether the node is passive or not. If it is passive, the receiving node becomes
engaged; otherwise it ignores the solicitation. If the node ‘B’ satisfies the criteria of loop free
conditions (NDC, FDC, SDC), it will issue an advertisement for the destination node;
otherwise it will relay the received solicitation [27].
4.3.4 Set Route of LDR When a node ‘A’ updates a route to a destination node ‘D’ through a successor node ‘B’, it
updates its distance, sequence number and feasible distance for the destination node ‘D’.
Figure 4.5: Example of LDR [27].
Figure 4.5 shows a directed acyclic graph, which consists of six no
and ‘T’ is source and destination node respectively. The numbers indic
and feasible distance to the destination node. Consider that all nodes
same sequence number to the destination node ‘T’ and initially node ‘
route to a node ‘T’ and issues a control packet RREQ. Nodes ‘B’, ‘C’
RREPs. Consider first, node C responses and its measure distance is 3
2. The node ‘C’ replies with a message RREP and updates its meas
receiving RREP, the node ‘E’ updates its receiving distance and feasib
the same time, node ‘B’ generates a RREP and updates its distance by
is not less than the current feasible distance, node ‘E’ ignores the
generates a RREP with a measure distance 1. Receiving this RREP,
feasible distance and measure distance to 2 and set its successor to node
At some future time, if the links e2 and e3 fail, node ‘E’ will issue
feasible distance 2. Node ‘B’ can not reply a RREP because it does no
(current distance is not less than the feasible distance) and node ‘B’
A B C D
E
5/5 4 3/2 1/1
Numbers: hops/FD
e2
e3
e5
e4 e1
T
26
des where nodes ‘A’
ate the stored distance
except node ‘E’ have
E’ does not have any
and ‘D’ respond with
and feasible distance
ure distance to 3. By
le distance with 4. At
4. Hence the distance
RREP and node ‘D’
node ‘E’ updates its
‘D’.
a RREQ with a new
t satisfy the condition
must reset the path to
0/0
/4
27
destination node ‘T’. Although in case of node ‘C’, even if it does not satisfy the condition, it
must forward the RREQ. Finally node ‘D’ will issue a RREP as it satisfies the condition.
Node ‘C’ unicasts the RREQ to the destination node ‘T’ which issues a RREP with setting
distance 0. Node ‘D’ will relay it to ‘C’. When node ‘C’ receives the reply it sets its measure
distance to 2 and keeps the feasible distance also 2. It also relays RREP with distance 2.
When the node ‘B’ receives RREP, it sets its measured distance and feasible distance to 3.
Again it relays the RREP with distance 3. Finally node ‘E’ receives the RREP and set its
measure distance and feasible distance with 4 [27].
4.3.5 CONCLUSION • Similar to AODV, LDR uses the sequence number but it uses a unique loop
freedom algorithm.
• It uses the concept of feasible distance which is followed by DUAL.
• LDR performs its operations by using two phases- route request and route reply. In
order to form a new route i t broadcasts a route request for searching the
destination node. When the destination node receives the request, it will reply using
a control packet, route reply.
• LDR uses two control packets RREQ and RREP to create a loop freedom path
between nodes within Ad-hoc network.
• It uses ordering which is non- increasing with time to ensure the loop freedom
routing.
• It supports multipath routing.
• Feasibility is tested hop-by-hop in LDR.
• To e n s u r e loop free environments, it uses timers. These timers automatically
decrease based on number of hop. If the timer goes to zero, controlled message will
be automatically discarded.
• Compared to AODV, DSR and OLSR, LDR ensures more packet delivery ratio [27].
• At low load scenarios, LDR has very low overhead compared to AODV, DSR and
LSR. OLSR and LDR show similarity in packet latency [27].
• Similar to AODV, LDR has very low MAC-layer drops.
4.4 ZRP Haas and Pearlman first introduced Zone Routing hybrid protocol (ZRP) [24] whereby
whole network area is divided into several small zones to perform its operation. Zone size or
radius does not depend on distance or radius; it depends on the number of hops. It is
applicable in a wide variety of mobile Ad-hoc network with diverse mobility across a large
span. It uses separate strategy to find out a new route between nodes, which are lying within
or outside the zone. There are four elements available in ZRP: MAC level function, IARP,
IERP and BRP. IARP, proactive approach is used to discover a new route within the zone
and in this case, links are considered as unidirectional. But in order to communicate with the
nodes, which sometimes may be located outside the zone, it uses IERP, on-demand routing
approach. These different strategies, such as routing zone topology and proactive
maintenance which improve the routing efficiency and the globally reactive routing using
query/reply mechanism improves the quality of discovering in ZRP [12].
Figure 4.9: A complete block d
Figure 4.6: A complete block
Zone radius is an important parameter
slowly moving nodes and high demand
would be infinitely large. In fixed Intern
Smaller routing zone is suitable for minim
works as a normal flooding protocol wh
direct neighbor nodes, and the other node
NDP (Neighbor Discovery protocol) resp
NDP ICMP IERP
BRP
IARP
ZRP
IP28
iagram of ZRP with different components [18].
diagram of ZRP with different components [13].
of ZRP. A large routing zone is more suitable for
of route scenarios. In fixed topology, network zone
et, pure proactive routing protocols are best suited.
um nodes and where demand of route is low. ZRP
en zone size is exactly one. In order to identify the
s within the zone, ZRP employs MAC protocol and
ectively [13].
29
4.4.1 IARP Intrazone Routing Protocol (IARP) is an important part of ZRP routing protocol. It is not a
specific routing protocol but it is a family of limited-depth, link state, proactive routing. It
establishes new route for nodes, which are located in the same zone. IARP efficiently guides
route queries outward through border-casting and relaying queries blindly from neighbor to
neighbor. IARP helps to enhance the quality of real time applications and proper route
maintenance. It supports unidirectional links as long as the link source and link destination
lie within a same zone. It maintains the local routing information proactively based on
periodic exchange of neighbor discovery messages and all nodes are referred by unique IP
addresses. Although temporary loops may form during the time of new link establishment in
the routing zone, it provides support as a loop free routing protocol [13].
To discover the local neighbors, IARP uses NDP (Neighbor Discovery Protocol) to
communicate with neighbor nodes which are located in the same zone [14], [15]. Since
nodes frequently change positions in MANETS, it may have bigger impacts on routing. The
scope of IARP is same as zone size. TTL is used during the updating of routing table by
IARP. When a query packet moves from source node to its neighbor nodes, TTL
automatically decreases. When query packets arrive at border nodes, TTL goes to zero.
4.4.2 IERP ZRP uses Interzone routing protocol (IERP) to communicate with the nodes of different
zones. It follows reactive approach to find out a new route. To improve the efficiency, IERP
uses BRP instead of sending queries to other nodes by traditional flooding. For
unidirectional links, IERP provides the local support based on the routing information of
IARP [14]. Interzone routing protocol helps to discover the global route and facilitates the
services to maintain the routes based on local connectivity of Intrazone routing protocol.
4.4.2.1 Route discovery in IERP IERP discovers the global route in two phases- route request and route reply [13]. The first
phase is required when a node needs to establish a new route with a destination node, which
is not available in existing routing table. The source node sends a request packet to its
neighbors and then neighbor nodes will also forward this packet to their neighbors.
Destination node will reply containing with detailed information when it will receive the sent
packet by source node, which come through different nodes. Any sent packet contains its
address and link metrics. When this query packet arrives at the destination node, the
30
sequence of recorded nodes will indicate the overall route from source to destination. The
destination node will also use the same route to give feedback to the source node.
4.4.2.2 BRP (Bordercast Resolution Protocol) Bordercasting is used instead of traditional broadcasting to improve the efficiency of
global reactive routing protocol. It is a message distribution service, which is used to direct
queries in network across overlapped routing zones. BRP is used by IERP to find out the
global routes in ZRP routing protocol. Similar to IERP and IARP, BRP is not a complete a
routing protocol; it works simply as a packet delivery service. One of the important features
of BRP is that to construct a new bordercast tree, it uses the routing table, which is provided
by IARP for each node. BRP maintains the information of the destination node where the
queries have to be delivered. When a node receives a query packet in IERP, first it checks
whether the destination node is available in local zone or not. If it is not available then it
forms a new bordercast tree to broadcast the query to neighbor’s nodes. The same procedure
will continue until the destination node is known [14].
4.4.2.2.1 Bordercasting (low dense network with stationary nodes) The bordercasting uses the topology information, which is provided by IARP to direct
query request to the border zones. It also uses the routing tables that are provided by IARP to
guide the route query away from the source query. For better understanding of the working
principle of BRP in ZRP, we have considered different scenarios which include when nodes
are stationary, when nodes are stationary but network density is high and a scenario
consisting of mobile nodes.
In figure 4.7, nodes ‘a-h’ is considered as stationary to explain the formation of route by
BRP.
d
f h
c b e
a g Figure 4.7: A scenario of Bordercasting (low dense network with non-mobile nodes [16].
ac
Here source node ‘a’ wants to establish a new route with the destination node ‘h’ where
zone size is 2. Node ‘a’ first forwards a query packet to all nodes within the zone. Here
nodes ‘c’ and ‘b’ are within the zone and d, f, e are border nodes. Using the IARP, nodes ‘b’
and ‘c’ indicate that destination node is not available within the zone and form a new
bordercast tree with detailed information of destination node. Node ‘b’ forwards this query
packet to node ‘e’ which states that destination node ‘h’ lies within the same zone and then
replies with a correct route.
4.4.2.2.2 Bordercasting (High dense network with stationary Nodes) The process of computing multicast tree and attaching the routing instructions to the packet
are called RDB (Root-Directed Bordercasting) and DB (Distributed Bordercasting). In figure
4.8(a), zone size is considered as 2.
Figure 4.8(a): A scenario of Bordercasting of node ‘a’ (node density is high and n
stationary) [15].
In figure 4.8 (a), node ‘a’ wants to establish a new route with a destination node ‘w
IARP first it checks whether the destination node is available or not within zone
destination node is not within zone. So in order to establish a global route it uses B
source node sends a query packet to its neighbor nodes d, l, j, i, h and e.
a
b
c
d
e
f
g h
i
j
k
l
o
m
p
n
q
v
r s
t
wu
31
odes are
’. Using
. Hence
RP. The
Figure 4.8(b): A scenario of Bordercasting of node ‘j’ (node density is high and nodes are
stationary) [15].
The neighbor node ‘j’ also uses IARP to find out the destination node ‘w’. Hence the
destination node is not available at the local zone of node ‘j’ again it forms a new bordercast
tree.
Figure 4.8(c): A scenario of Bordercasting of node ‘q’ (node density is high
stationary) [15].
i
g
m
n
o
p
q
r s
u v
c e
d k
b
l
f
a m
j
n
p
o
s
k
c e l
b
f
g
i
q
v
o
r
u
3
and nodes a
t
w
2
re
h
h
wt
j
a
As the neighbor nodes ‘a’ and ‘i’ have already considered for forming previous bordercast
tree, these nodes will not be considered for this new bordercast tree. The packet will only
be forwarded to the neighbor nodes ‘q’ and ‘p’ according to figure 4.8 (b). The destination
node is not available in the local zone of nodes ‘q’ and ‘p’. So again, the query packet will
only be forwarded to the neighbor nodes, which are not already covered. Here the query
packet are forwarded only to neighbor node‘s’ which is shown in figure 4.8 (c). Finally,
destination node ‘w’ belongs to the local zone of node ‘s’ and thus the destination node is
found. In this way using the BRP node, desire destination node is found in ZRP.
4.4.2.2.3 A scenario where nodes a re mo bile In order to design a MANET scenario in the figure 4.9(a) and (b), nodes are considered as
mobile. As a result topology changes can occur at any instance. Here node ‘c’ and‘d’ move
in different directions and within a short time they may be disconnected from neighbor
nodes. Therefore, nodes ‘b’ and ‘e’ may lose their connection. Node ‘f’ may come closer and
will establish a new connection with nodes ‘e’ and ‘a’. Constructing the bordercast tree
according to the new zone structure, IERP selects a new global route among different nodes
of different zones with the help of BRP.
Figure 4.9(a), (b): The scenarios where the nodes are mobile [14].
4.4.2.3 Selective Bordercasting Although bordercasting approach has more advantages than the traditional flood
has some limitations in terms of efficiency. To improve the efficiency, a new ap
bodercasting that aims to improve the efficiency is selective bordercasting. In this
a
b
c
d
e
f
a
c
b
d
f
ing,
pro
app
e
33
still it
ach to
roach,
34
a node knows the information of the extended nodes. If an outer peripheral nodes overlap, a
node does not consider the peripheral nodes from its bordercast recipients.
Figure 4.10: A scenario of selective bordercasting [14].
In the figure 4.10, the neighbor nodes of ‘x’ zone are u, z and y. Here the zone of ‘x’ node
has overlapped with the zone of peripheral nodes ‘u’ and ‘y’. Using this selective concept,
node ‘x’ removes the node ‘z’ from its bordercasting tree because node ‘c’ and ‘d’ can
reach via the nodes ‘u’ and ‘y’ respectively. As a result, selective bordercasting reduces the
sizes of bordercasting tree compared to traditional bordercasting approach and it also helps
to reduce the processing de lay and improves the overall routing performance [14].
4.4.2.4 Adaptive Bordercast Resolution Protocol This is an approach, which improves the routing efficiency and minimizes the packet loss
and end-to-end delay of ZRP [14]. In traditional BRP, routing zone is always fixed. Hence
MANET topology changes randomly; this fixed radius does not always provide optimal
efficiency. In Adaptive Bordercast Resolution Protocol (ABRP) automatically sets the zone
size based on the topology and node density instead of fixed zone. In low node mobility and
low packet traffic, ABRP increases the zone radius. For high node mobility and high packet
traffic it automatically decreases zone radius to keep the better knowledge about the nodes
within network. When the zone size decreases, the route computation time and bandwidth
loss will automatically decrease. Based on the parameter threshold, which depends on the
optimal node density, ABRP automatically sets the zone size. The ABRP shows the better
performance than traditional BRP [15].
4.4.3 Query control mechanism IERP uses Border Routing Protocol to construct a new bordercast tree of neighbor nodes.
In some scenarios, neighbor nodes may overlap with different zones and as a result, same
neighbor node may forward same route request in several times which increase the traffic
and these redundant query packets waste the transmission capacity. To reduce this problem,
ZRP uses the query control mechanism. In this approach of forming a new routing table,
query packets will not forward those neighbor nodes, which are already covered by previous
query. Three control mechanisms use in ZRP: Query Detection, Early Terminal and Random
Query-processing Delay.
4.4.3.1 Query Detection BRP uses two levels of Query Detection- QD1 and QD2. QD1 is used to relay the queries
to the peripheral nodes and QD2 is used for those nodes those are not connected with
peripheral nodes. It is used for a single channel within the zone shown in figure 4.11.
Figure 4.11: BRP Q
4.4.3.2 Early Terminal BRP also uses another technique whic
node already has considered for anothe
node ‘b’ receives a query packet. Node
with node ‘a’. According to node a’s bo
of a’s peripheral nodes. Node ‘b’ reco
QD1
QD2
35
uery Detection process [14].
h is Early Terminal (ET) to discard the packet, if the
r node. In figure 4.12 from bordercasting node ‘c’,
‘b’ will also receive a duplicate query packet to relay
rdercast tree, node ‘b’ should relay the query to two
gnizes the both peripheral nodes that already have
QD1
considered. Based on the ET-criteria, node ‘b’ prunes both peripheral nodes from its
bordercast tree [13].
Figure 4.12: BRP Early Termination
4.4.3.3 Random Query Processin In overlapping zone scenario, one node may
bordercast trees, which may cause collision fre
Random Query Processing Delay (RQPD) [
approach, nodes send requests for constructing t
4.4.4 Conclusion • ZRP is a hybrid protocol.
• Zone size is an important factor in ZR
denser nodes and for dynamic character
solution. Using ABRP app roach in Z
• Smaller zone size is suitable for low dens
• Zone size is measured by number of hop
• In this approach if the zone size is o
intelligence and it acts just as a tradition
• ZRP consists of proactive, IARP and rea
• For discovering the local route it uses
routing protocol.
• For global route discovery, it uses the
protocol.
• ZRP maintains the routing zones bas
discovery messages by BRP and ABRP
a
b c
d36
process.
g De lay (RQPD) simultaneously send request for forming the
quently. To reduce this collision BRP uses
13]. To improve the performance in this
he bordercast trees at random time interval.
P. Larger zone size is required for higher
of ZRP; fixed routing zone is not an optima l
RP zone size will automatically change.
e nodes and vice versa.
not by the distance or radius.
ne, this ZRP routing does not follow any
al flooding approach.
ctive, IERP components.
the MAC level function, NDP and IARP
IERP on-demand or demand driven routing
ed on the periodic exchange of neighbor
.
37
• ZRP protocol also supports the IP addressing architecture.
• ZRP is a loop free routing protocol. IERP ensures the loop freedom property in
route discovery-based on the total source routes [12].
• ZRP provides the support of utilizing multi-channel, link layer t echnology
assuming a unique IP address for network interface of each node.
5 FIFTH CHAPTER
5.1 Simulation Environments of MANET Different simulators were used MANET. They include NS-2/3 (Network Simulator-2/3)
[23], OPNET (Optimized Network Engineering Tool) [25], GloMoSim [18] etc. In this thesis
we have used OPNET version 14.0 to design mobile Ad-hoc networks due to the following
reasons [33], [34]:
• It provides a very attractive virtual network environment that is prominent for the
research studies, network modeling and R&D operations and performance analysis
of routing.
• It plays a key role in today’s emerging technical world in developing and improving
the wireless protocols such as Wi-Max, Wi-Fi, UMTS, etc.
• It is widely used in new power management systems over sensor networks and
enhancement of network technologies such as IPv6, MPLS etc.
• Many well-known organizations are using these technologies for their applications.
• It is reliable, robust and efficient compared to other simulators.
• It is good for performance study among existing systems based on user conditions.
• It is easy for understanding the network behaviors in various scenarios.
• It is very flexible and provides a user-friendly graphical interface to view the results.
5.2 Modeling of MANET scenarios in OPNET
Figure 5.1: A complete overview
The complete working procedu
network model, select individual
collected simulation results [33].
Design Network Model
Run Simulation
Result Analysis
Select individual Statistics
38
of designing project in OPNET.
re in OPNET can be divided into four sections- designing
statistics, collect simulation results and finally analyze the
39
For the designing the network model, firstly, we need to run the OPNET module and set
the proper name and scenarios in black scenarios. We have to drag and paste the following
entities: application configuration, profile configuration, mobility configuration, server and
node configuration. Application configuration is used to specify the required application
among available applications such as HTTP, FTP, TCP etc. TCP is connection-oriented
traffic, which provides many advantages than others. But it needs huge time as a delay for
ensuring guaranteed packet delivery. If we compare FTP to TCP, FTP is most compatible in
many network scenarios where guaranteed packet delivery is not needed. Therefore, in our
thesis we have chosen FTP traffic for designing our network scenarios. Profile configuration
is used to create user profiles for the designing of network and it can also be specified on
different nodes to generate the traffic within the network scenario. We have designed profile
as FTP heavy in our designed models. Using FTP heavy enable us to simulate a scenario
whereby large data packets are sent from end to and across the network.
We have also configured the server and node with mobility according to our simulation
environments. It supports the IEEE 802.11(Wi-Fi) and we have also configured the
supported services based on the configured profile. When we configured the mobility of the
node, which determines the characteristics of nodes such as mobility model, node speed etc,
all scenarios are tested choosing only TORA routing protocol rather than LDR and ZRP
because these two protocols do not support the OPNET.
In the workspace pop-up menu, we have to configure the statistics for different discrete
events in simulations choosing the “Individual DES statistics” option. These statistics are
basically applied in either global or scenarios-wise statistics and object statistics. Global
statistics is used for collecting data from the whole designed network model and object
statistics is from individual nodes. Based on the designers’ requirements, it may be collected
from global or object statistics. We have chosen global statistics of wireless LAN- delay,
throughput and network load to observe the performance of protocol for different network
environments.
40
Figure 5.2: Scenario of Mobile Ad-hoc Network with 25 nodes.
5.3 Impact of pause time on MANET routing protocols
5.3.1 Scenario 1 (ZRP vs. TORA)
(b)
(a)
41
(d)
(c)
Figure 5.3: (a) Packet delivery ratio of ZRP [8], (b) End to end delay of ZRP (sec.) [8], (c)
Control traffic received graph of TORA (bytes/sec), (d) End to end delay graph of TORA
(sec).
To observe the effect of pause time on MANET routing protocols, the simulation
environment of Figure 5.3(a) and (b) are modeled in a Quarlnet simulator [8] and Figure
5.3(c) and (d) designed in OPNET 14.0 with ZRP and TORA routing protocols respectively.
Similar statistical values are configured in all scenarios in different simulators such as
random waypoint model, 50 nodes, network area 1500x1500m2, node speeds of 0-20 m/s and
the total simulation time of 120s. The performance of the protocol is measured in terms of
end-to-end delay and packet delivery ratio for various pause times under FTP traffic. The
average time taken by the packet in order to traverse the network is named as delay
which is also called data latency [1] and the packet delivery ratio is calculated by
dividing the number of packets received by the destination through the number of packets
originated by the application layer of the source [18].
In Figure 5.3, we can see that the simulation results of 50 nodes hybrid protocol- ZRP and
reactive protocols-TORA show the different characteristic curves of total received packet
graph/packet delivery ratio. The ZRP graph shows that the packet delivery ratio does not
fluctuate much with the increment of pause time, which is shown in Figure 5.3 (a). ZRP
delivers almost 40 percent of all packets initiated by the source at any pause time [8]. And
the variation of pause time makes a changed in averaged packet received in TORA, which is
shown in Figure 5.3(c). The simulation results show that maximum average packet received
is 505 bytes/second at 60 second of pause time. With the increment of pause time, the
42
amount of received packet decreases. The experimental results show that for 90, 120 and 150
seconds of pause times, the amount of average received packets are 337, 168 and 168
bytes/seconds respectively.
In Figure 5.3 (b), the end-to-end graph shows that with the increment of pause time, the
average end-to-end delay increases in case of ZRP but it shows drastic increase when pause
time increases from 120 to 150 seconds [8]. At 30seconds of pause time the average end-to-
end delay is 0.018seconds and with the increment of pause time, it slightly rises and at
120seconds of pause time it comes 0.03s. Figure 5.3(d) shows that delay is less at lower
pause time of TORA. This graph follows the increasing trend with the increment of pause
time.
5.3.2 Scenario 2 (LDR vs. TORA) To observe the effect of pause time on MANET routing protocols, the simulation
environments of Figure 5.4(a), (b) and (c) are modeled in GloMosim simulator [27] and
Figures 5.3(d), (e) and (f) are in OPNET 14.0 of LDR and TORA routing protocols
respectively. The similar statistical values are configured in all scenarios in different
simulators such as random waypoint model, 50 nodes, network area 1500x300m2, nodes
speed is 1-20 m/s and total simulation time of 900seconds [27], [29]. The performance of
the protocols is measured in terms of Packet Delivery Ratio, Network Load and End-to-End
Delay/Data Latency for various pause times of 0, 50, 100, 200, 500, and 700 seconds under
FTP traffic. Network load represents the total load in bit/sec submitted to wireless LAN
layers by all higher layers in all WLAN nodes of the network [3].
(a)
(b)
43
(c)
(d)
(e)
(f)
Figure 5.4: (a) Network load of LDR (bits/sec) [27], (b) Delivery Ratio of LDR [27], (c) Data
Latency of LDR (bits/sec) [27], (d) Network Load of TORA (bits/sec), (e) Control traffic
received graph of TORA (bytes/sec) and (f) Average Delay of TORA (sec).
The network load graph shows that the variation of pause time has a high effect on the
performance of LDR compared to TORA. The Figure 5.4(a) shows that the network load
44
slowly decreases with the increment of pause time for LDR routing protocol. Here at
50seconds of pause time, the network load is 0.5 bits/sec and where at 500 and 900 seconds
of pause times it was approximately 0.3 and 0.1 bits/sec respectively [27]. The Figure 5.4 (d)
shows that variation of pause time does not affect much the network load of TORA. In case
of dynamic change, the variation of pause time may cause a small change to the network
load. At lower pause time, it shows lower network load and vice versa.
Packet delivery ratio does not have much influence on the variation of pause time of LDR
and TORA, which are shown in Figures 5.4(b) and 5.4(e) respectively. For different pause
times 0-900 seconds, packet delivery ratio graph of LDR maintains a steady level [27] and
Figure 5.4 (e) shows that the variation of pause time does not affect on the average packet
received through TORA. The simulation results show that at 0 – 900 seconds of pause time,
the average received packet is 168 bytes/sec.
The delay/data latency graph shows that the variation of pause time, affects the
performance of LDR to a greater extent than TORA. Figure 5.4(c) shows that at lower pause
time, the data latency is high of LDR. If pause time increases, the end-to-end delay will
slightly decrease with an incremental increment of pause time. At 100 seconds of pause time,
the end-to-end delay is 0.07s and at 700 and 900 seconds of pause time its values become
0.3s. But in TORA Figure 5.4 (f) shows that maximum delay is 0.013721s at 0 second of
pause time and for all other pause times 100-900 seconds the delay is 0.012983s. 5.4 Impact of number of node and network scalability on MANET routing protocols
5.4.1 Scenario 3 (ZRP vs. TORA) To observe the effect of node density and scalability on the performance of MANET
routing protocol, the simulation environments of Figures 5.5(a), (b) and (c) are designed in
QualNet simulator [30] and the Figures 5.5(d), (e) and (f) are in OPNET 14.0 for ZRP and
TORA respectively. The similar statistical values are configured in all scenarios in different
simulators such as random waypoint model, network size 500x500m2 for 10 and 25 nodes,
area 1000x1000m2 for 50 and 100 nodes and area 3000x3000m2 for 200 nodes and node
speed is 0 to 30 m/sec. The performance of the protocols ZRP and TORA is measured in
terms of packet delivery ratio, network load and end-to-end delay/data latency for various
pause times at FTP traffic.
45
(a) (b)
(c)
(d)
46
(e)
(f)
Figure 5.5: (a) Throughput graph of ZRP (bits/sec) [31], (b) Average end to end delay of ZRP
(seconds) [30], (c) Packet received graph of ZRP, (d) Throughput Graph of TORA (bits/sec),
(e) Delay Graph of TORA (sec), (f) Average received packet graph of TORA (bytes/sec). We have observed that in a small network, throughput is high at lower dense network.
Whereas for 10 nodes, the throughput is 2000 bits/sec and within same network size for 25
nodes, it falls down to approximately 400 bits/sec. If we increase the network size, inverse
characteristics are shown compared to, small networks, where a fewer amount of throughput
is achieved at lesser number of nodes and vice versa. But for larger area and 200 nodes, it
goes down gradually. Similar characteristics are observed as seen in, graph for received
packet in ZRP, which is presented at Figure 5.5(c) where for few nodes the amount of
received packet is high, but it automatically goes down with incremental increment of nodes.
The characteristics curve of end-to-end delay of ZRP for the variation of nodes at Figure
5.5(b) shows that the number of node does not affect the average end-to-end delay. For any
number of nodes, the average end-to-end delays are very few.
On the other hand, as the Figure 5.5(d) shows, different curves shown in TORA represent
no radical change in throughput with the variation of nodes. But for fewer nodes, throughput
is slightly high. In Figure 5.5(e) for the lesser number of nodes, the higher the delay and vice
versa. The variation in the amount of packet received depends on the variation in the number
of nodes, which is presented in Figure 5.5(f) and where maximum packet received is 505
bytes/sec for 10 nodes and 168 bytes/sec for 25 nodes. For 50 and any amount of nodes
between 100 and 200, the average received packet is 337 and 168 bytes/sec, respectively.
47
5.4.2 Scenario 4 (ZRP vs. TORA) The node density and scalability affect on the performance of MANET routing protocol as
observed. The simulation environments of Figures 5.6(a), (b) and (c) are designed in
QualNet simulator [18] and the Figures 5.6(d), (e) and (f) are in OPNET 14.0 for ZRP and
TORA, respectively. Similar to QualNet same the statistical values such as random waypoint
model, for different areas of different amount of nodes such as for 2, 50, 150 and 200 nodes,
the sizes are 0.119716 Km2, 3 km2, 9 km2 and 12 km2,respectively and node speed 0 to 10
m/sec are configured in all scenarios in OPNET. At FTP traffic, the performance of the
protocols ZRP and TORA is measured in terms of packet delivery ratio, throughput and
average end-to-end delay/data latency.
(a)
(b)
(c)
(d)
48
(e)
(f)
Figure 5.6: (a) Packet Delivery Ratio of ZRP [18], (b) Throughput graph of ZRP (bits/sec)
[18]. (c) End to end delay graph of ZRP (sec) [18], (d) Throughput graph of TORA
(bits/sec), (e) End to End delay of TORA (sec), (f) Average received packet of TORA
(bytes/sec).
In ZRP routing protocol, the packet delivery ratio shows that the variation of number of
nodes and as well as size of area do not show an influence after a certain limit. Figure 5.6(a)
shows that for less than 50 nodes, packet delivery ratio is high and this curve maintains a
steady level for more than 50 nodes. Figure 5.6(b) shows that throughput goes down
automatically depending on the increment of the nodes. For 50 nodes, the throughput is
around of 150 bps and for 150 and 200 nodes it goes down 95 and 50 bps, respectively. The
average end-to-end delay depends on the amount of node. With the incremental increase of
nodes, end-to-end delay is also shows a gradually increasing trend. For 100 nodes, it is
1.2sec and 2.3sec and 3.4sec for 150 and 200 nodes, respectively.
Characteristics graphs of TORA, Figure 5.6(d) show that if the node increases
proportionately to the increment of network area, then the throughput is higher for lesser
number of nodes and it shows only a marginal change, for a large variation of nodes.
For 2, 50, and 150 nodes the throughput is 1779312, 1706071, 407529 bits/sec respectively.
In f igure 5.6(e), the end-to-end graph shows that the increases of network size with the
increment of node affect the performance. For 150 nodes, the delay is maximum, 0.14419
sec and for any amoun t o f nodes the d e l a y is almost 0.01490sec. The average
received packet graph also shows the similar characteristics graph of delay, which is
49
presented in Figure 5.6(f), for 150 nodes, the received packet is at a maximum 337
bytes/sec and for any other nodes; it is 168 bytes/sec.
50
6 SIXTH CHAPTER
6.1 Conclusion Our literature study has revealed that designing an efficient routing protocol is a fundamental
issue that is very pivotal to improving the overall performance of MANET where nodes are
highly mobile. Since traditional routing protocols are table driven, they do not work efficiently
in adaptive scenarios synonymous with MANET because it is not an easy task to maintain big
routing tables with proper routing information for thousands of mobile nodes. The reactive and
hybrid routing protocols work more efficiently in such adaptive scenarios. Tables are normally
completely absent in these adaptive scenarios and new routes are established on demand basis
using some control packets. LDR and TORA routing protocols were found to be more suitable
to these adaptive scenarios. The hybrid protocol-ZRP uses proactive and reactive approach
depending on the prevailing network environment and as a result it integrates the benefit of
proactive and reactive approaches.
We summarize the characteristics of these three routing protocols analyzing the scenarios 1-4
in following ways:
Packet delivery ratio does not fluctuate much with an incremental increment of pause time
like TORA. The end-to-end delay shows some abnormal effects in ZRP, but in TORA with the
increment of pause time, the end to end also gradually increases from scenario one. The
network load and delay graphs show that the variation of pause time has a profound effect on
the performance of LDR compared to TORA but the packet delivery ratio does not have
much influence. In LDR, the increment of pause time, delay is slightly decreasing but in
TORA it does not fluctuate much on delay scenario two.
The variation of number of nodes and area causes similar characteristics in both ZRP and
TORA where for few nodes, the amount of received packet is high, but it automatically goes
down on the basis is of increment of nodes. It causes much influence on the end- to-end
delay of TORA than ZRP. The number of node does not have much effect on average end-
to-end delay of ZRP and for any number of nodes; the average end-to-end delays are very
few. In TORA, the greater delay is observed for the lesser node and vice versa. It also has
more effect on throughput of TORA than ZRP. In ZRP, for a small network, throughput is
high for low network density. But there is no radical change in throughput for the variation
of nodes. But for few nodes, throughput is slightly high such as observable in scenario three.
51
The variation of number of nodes as well as size of area does not have much influence
much on the packet delivery ratio after a certain limit. After this limit in both cases a steady
level is maintained in both TORA and ZRP. In ZRP the throughput rate goes down
automatically depending on the increment of the nodes but in TORA, it shows inverse
characteristics and the changes are quite few for a large variation of nodes. It also has much
effect on the end-to-end behavior of ZRP than that of TORA as shown in the graph. In ZRP
if we increase the nodes, end-to-end delay will increase and vice versa.
From the above discussion, we can conclude that different factors including pause time,
node density and scalability have substantial influence on the overall efficiency of TORA,
LDR and ZRP routing protocols. The variations in the behavior of the different routing
protocols are attributable to their different, reactive, hybrid and proactive natures. No single
protocol is found to perform up to the optimum efficiency with respect to network load,
throughput and packet delivery ratio for the variation of pause time, node density and network
size in such dynamic, adaptive and highly variable environments.
6.2 Future work
Our thesis goal was to draw a comparison among TORA, LDR and ZRP with respect to
different metrics including network size, node density and pause time. We have chosen
OPNET version 14.0 as a simulator. But it supports only six MANET routing protocols
where LDR and ZRP are not included. So in our simulation part we did not make
simulation of LDR and ZRP in OPNET. Future works can be geared towards designing
MANET environments in another simulator, which supports all MANET routing protocol
either in ns -2/ns-3 or QualNet to observe the performance of TORA, LDR, ZRP and other
routing protocols
52
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