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CHAPTER 2
PERFORMANCE EVALUATION OF ROUTING
ALGORITHMS FOR MOBILITY MODELS IN AD HOC
NETWORK
In this chapter, the performance of existing routing strategies in ad
hoc networks is investigated. Routing protocols such as DSDV, DSR and
AODV are chosen and simulated in a common wireless network simulation
platform using Network Simulator version 2 (NS2). In addition to the
performance study, mobility models are also proposed and implemented, which
are more realistic, and the performance of these routing protocols is compared
in more realistic scenarios.
Related works (Broach et al 1998, Das et al 1998, Jhonson et al 1999
and Lee et al 1999) that also perform comparative evaluation of ad hoc routing
protocols can be found in the literature. However, these articles compare the
protocols and use only a single mobility models. These papers evaluate a single
class of protocols using performance metrics such as throughput and pure
control overhead that only show the effectiveness of the protocol. In this
chapter, the performance of existing protocols is investigated for different
categories in various network scenarios such as differences in mobility models,
mobility rates, traffic patterns, etc. The proposed mobility model defines an
exponential distribution model for speed and position with its intuitively more
appealing natural formulation than earlier assumptions. This model is applied to
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different routings protocols and its network performance is evaluated with
different mobility patterns. The ultimate purpose of this work is to find which
routing strategy is best for which environment.
2.1 ROUTING PROTOCOLS
Routing protocols proposed for mobile ad hoc networks are
categorized by reactive and proactive protocols. In this chapter, in order to
investigate the performance of the existing protocol for MANET one proactive
and two reactive protocols are chosen and discussed in the following sections.
2.1.1 Destination Sequenced Distance Vector
DSDV is a table driven algorithm based on the classical Bellman-
Ford or Routing Information Protocol (RIP) routing mechanism. The
improvement made to the Bellman-Ford algorithm includes freedom from loops
in routing tables by using the concept of sequence numbers.
Every mobile in the network maintains a routing table in which all of
the possible destinations within the network and the number of hops to each
destination are recorded. Each entry is marked by a sequence number assigned
by the destination node. The sequence numbers enable the mobile nodes to
distinguish stale routes from new ones, thereby avoiding the formation of
routing loops. To maintain the consistency of routing tables in a dynamically
varying topology each node periodically transmits updates immediately when
significant new information is available.
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The data broadcast by each mobile node for each new route contains
its sequence number and destination address, the number of hops (metric)
required and the sequence number to reach the destination determined by the
destination. The route with the most recent sequence number is always used. In
the event of two updates having the same sequence number, the route with the
smaller metric is used, in order to optimize the path. Mobile nodes cause broken
links as they move from place to place. A broken link is described by a metric
of infinity. When a link to a next hop is broken in any route, it is immediately
assigned an infinity metric and updated with an odd sequence number.
To avoid periodic updates, which generate a large amount of network
traffic, DSDV supports full dump and incremental updates. In the first case, the
routing packets carry all available information and require multiple Network
Protocol Data Units. Whereas in the second case smaller incremental packets
are used to relay only that information which has changed since the last full
dump. Each of these broadcasts should fit into a standard size NPDU, thereby
decreasing the amount of traffic generated. In DSDV, the mobiles also keep
track of the setting time of routes and, by delaying the broadcast of a routing
update, by the length of the setting time, the network traffic is reduced.
2.1.2 Dynamic source routing
The DSR is an on-demand routing protocol based on the concept of
source routing. This protocol allows nodes to dynamically discover a source
route across multiple network hops to any destination in the ad hoc network.
When using source routing, each packet to be routed carries in its header the
complete ordered list of nodes through which the packet must pass.
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The protocol consists of two major phases viz Route discovery and Route
maintenance.
When a mobile node wants to send a packet to some destination it
checks its route cache and whether it has any route to the destination. If it has
an unexpired route, it will use this route to send a packet to the destination.
Otherwise, it will initiate a route discovery procedure by broadcasting a RREQ.
Each node hears the route request packet and adds its own address to a source
route. Node S generates a route request to node D and broadcasts the route
request. Nodes B, C and E in turn receive a RREQ from S. Suppose node C
receives the RREQ for the first time it add its address in the route request
packet and rebroadcasts it to the next node H and ignores it if it is already
received. The forwarding of the route request is constructed so that copies of
the request are propagated hop-by- hop outward from the source node until
either the target of the request is found or until another node is found that can
supply a route to the target.
Route reply is generated when the route request reaches either the
destination itself or an intermediate node, which contains in its route cache an
unexpired route to the destination. Figure 2.1 shows that destination D, on
receiving the first RREQ, sends a RREP on a route obtained by reversing the
route appended to receive the RREQ. The RREP includes the route from S to D
on which the RREQ was received by node D. If the node generating the route
reply is the destination, it places the route record contained in the route request
into the route reply. If the responding node is an intermediate node it appends
its cached route to the route record and then generates the route reply.
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RREP [S,C,H,D]
Figure 2.1 Route Reply in DSR
Route maintenance is the process of monitoring the status of a source
route while in use, so that any link-failure along the source route can be
detected and the broken link removed from use. Route error packets and
acknowledgements are used to maintain the route. Route error packets are
generated at a node when the data link layer encounters a fatal transmission
problem. When a route error packet is received, the hop in error is removed
from the node route cache and all routes containing the hop are truncated at that
point. In addition route error message acknowledgements are used to verify the
correct operation of the route links. The parameter values of DSR used for the
simulation are given in Table 2.1.
Table 2.1 Parameter values for DSR
Time between retransmitted Route Requests 500 msecs
Max. time where the same request can be sent 10 secs
2.1.3 Ad hoc On-Demand Distance Vector
AODV is an improvement on the DSDV algorithm because it
minimizes the number of required broadcasts by creating routes on demand
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basis as opposed to maintaining a complete list of routes in the DSDV
algorithms. In the AODV algorithm the flooded route request packets are used
to find routes as done in DSR. The AODV algorithm maintains a routing table
in all intermediate nodes instead of a route cache. Nodes forwarding the request
remember the earlier hop taken by the request packet. This hop information is
used to forward the reply packet back to the source. The route reply packet sets
up the routing table entries on its path. If any node has a route to the required
destination, it can reply to a request. It also uses a technique called route expiry,
where a routing table entry expires after a predetermined period, after which
fresh route discovery must be initiated. It uses HELLO messages to determine
the connectivity among the neighbors.
2.2 MOBILITY MODELS
The mobility models in ad hoc networks deal with individual motion
behavior of the nodes. Many researchers use the random mobility model
(Zonoozi and Dassznayake 1997) according to which the speed and direction of
motion in a new time interval have no relation to their past values. The
modified version of the random mobility model (Basagni et al 1998) is used in
DREAM protocol. The mobile host has a random direction at every simulation
clock tick, but a constant speed during the entire simulation period. In Ko’s
simulation model (Ko and Vaidya, 1998) the mobile hosts are allowed to move
along a path that is made up of several segments that are exponentially
distributed. The direction of each segment is chosen in a random manner.
According to Das et al model (1998), a node chooses its speed,
direction and distance based on predefined uniform distribution, and then
calculates its next destination and the time to reach the destination. Johnson’s
57
model (1996) is an extension of the random walk. Here the mobile host first
stays at a location for a certain time and then moves to a new random chosen
destination at a speed uniformly distributed between [0, MaxSpeed]. Haas
(1997) presents an incremental model in which the speed and direction of
current movement randomly diverge from the previous speed and direction after
each time increment. However, Sanchez (1998) studies the relationship among
mobile hosts that move with the same purpose. For example, in a military
environment, it is most likely that several mobile hosts move with a common
objective.
2.3 PERFORMANCE EVALUATION
The performance of the mobile ad hoc network for various mobility
models is studied with the help of the Network Simulator package NS2 (Kevin
Fall and Kannan Varadhan 1998). In NS2 the initial network topology is
generated by the random position of the node. Upon receiving the various
simulation input parameters such as the number of nodes (N), simulation area
(A), speed (s), pause time (tp) and simulation time (T), mobility is initiated. The
node positions are then updated and the shortest path and number of hops
required to reach the destination are computed. Based on the number of active
nodes (me) and their respective data rates the packets are routed to the required
destination. The trace file containing the status of the nodes (receive, send) and
links (failure, connectivity), types of packets (control, data, acknowledgment)
and average hop count is then generated and the process goes on till the
simulation time is over. The performance parameters such as throughput,
overhead and delay of the simulated mobile network are then computed. These
parameters are defined as
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Throughput: Measured as the ratio of the no. of data packets delivered to the
destination and the no. of data packets sent by the sender. This number presents
the effectiveness of the protocol.
End-to-end delay : Measured in ms as the time between the reception of the
last and first packet / total no. of packets reaching the application layer. This
delay includes processing and queuing delays in each intermediate node.
Control overhead : Measured as the ratio of the number of control packets
transmitted during the entire simulation period by data packets transmitted.
The simulation procedure in NS2 can be described as shown in
Figure 2.2. The network simulator assumes the mobile speed as a uniformly
distributed random process. In this study, more realistic models with
exponential and normal distribution, which assign lower probabilities for higher
speed are considered. The simulation of the mobile network is carried out on
800MHz Pentium III processor, 40GB Hard Disk capacity and Red Hat Linux
version 6.2 operating system with the parameter specifications shown in
Table 2.2.
Table 2.2 Parameters used during simulation
Transmitter range 250mSimulation area 1500m X 300mSimulation time 900 secsNumber of nodes 50Bandwidth 2 MHzTraffic type Constant bit ratePacket size 512
59
Initial Topology
Scenario generation___i___Pause time(tp) simulation
| | time (T)seed'^
speech-^, Initiate mobility
ANode Position
Update
no. of nodes (N) simu /ation /
area (A) / Default mobility/ model: Uniform
Mobility models P(x): exponential/
normal
IComputation of shortest path & no. of hops
Connection pattern
Active node selection
no. of active node selection (me) \no. ofpackets/sec/
source (rate)
v yes
Compute throughput, overhead & dela
no
Figure 2.2 Sequence of simulation using NS2
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The performance of Dynamic Source Routing for various mobility
models is plotted in Figures 2.3, 2.4 and 2.5. The throughput performance of the
DSR algorithm shown in Figure 2.3 indicates that the exponential model gives a
steady state throughput of 98% whereas in the uniform and normal distribution
models it progressively decreases to 95% and 90% respectively as the speed is
varied from lm/s to 5m/s. This could possibly be due to the fact that the dwell-
in time probability of the mobiles at higher speeds is small on the exponential
model than in the uniform and normal distribution models.
DSR Throughput Performance
Figure 2.3 DSR Throughput comparisons for various models
The end-to-end delay is very small at lower speeds upto 2m/s
whereas at higher speeds it increases marginally in the uniform and exponential
models but rapidly in the for normal model as shown in Figure 2.4. This might
be due to link breakages at higher speeds and as a consequence more number of
hops are required to reach the destination. At very low speeds, the control
overhead in the normal mobility model is found to be much lower than in other
61
models, which could be because of smaller lower end tail probability and is
shown in Figure 2.5. But, at higher speeds the effect of high-end tail probability
for the normal model is observed in the decreasing trend of the overhead. There
is approximately a linear change in control overhead with speed in the uniform
model whereas it is almost constant in the exponential model.DSR Delay Performance
0.7 ,--------------r--------------- ,---------------- ,---------------- ,---------------- r- i * i ----------j
-q Uniform -e— Exponential
0.6 - —Gaussian
1 1 5 2 2.5 3 3.5 4 4.5 5Speed (m/s)
Figure 2.4 DSR Delay comparisons for various models
1 1-5 2 2.5 3 3.5 4 4.5 5S peed {m/s)
Figure 2.5 DSR Overhead comparisons for various models
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The results of AODV algorithm for various mobility models are
shown in Figures 2.6, 2.7 and 2.8. At the highest mobility, AODV produces less
delay compared to DSR and also delivers more number of packets than the
other two algorithms with minimum packet delivery ratio of 93% for Gaussian
models. The overhead shown in Figure 2.7 clearly exposes those characteristics
of the model. The Exponential model experiences less overhead at higher
mobility than the other two models due to lower probability mobility at higher
speed. When compared to the DSR algorithm the number of control packets are
more for AODV, since it uses HELLO packets periodically, resulting in higher
packet overhead.AODV Throughput Performance
Figure 2.6 AODV Throughput comparisons for various models
Speed (m/s)
Figure 2.7 AODV Delay comparisons for various models
63
AODV Overhead Performance
Figure 2.8 AODV Overhead comparisons for various models
The performance of DSDV shown in Figures 2.9, 2.10 and 2.11
indicates that there is slightly lower throughput at lower mobility compared to
DSR and AODV. This is due to the fact that the packets are sent before routes
converge in the network. As mobility increases more number of packets are
dropped due to periodic route update in DSDV. The delay performance of
DSDV shown in Figure 2.10 exhibits less delay than the DSR for normal
models at high speed because only the packets belonging to valid routes at the
sending instant get through. But, more number of packets is lost until new route
entries are propagated through the network by the route updates. The overhead
performance of DSDV, which is shown in Figure 2.11 for all the mobility
models is very high when compared to those of DSR and AODV.
# of c
ontro
l pac
kets
64
DSDV Throughput Performance
Figure 2.9 DSDV Throughput comparisons for various models
DSDV Delay Performance
Speed (m/s)
Figure 2.10 DSDV Delay comparisons for various models
65
DSDV Overhead Performance
Figure 2.11 DSDV Overhead comparisons for various models
The comparative performance of all three routing algorithms for
various mobility models is given in Table 2.3 and Table 2.4 gives the parameter
ranges for all three algorithms.
Table 2.3 Comparative performance of ail three routing algorithms for
various mobility models
\ Mobility \models
Routing \ Algorithms \
% of Throughput Overhead Delay (secs)
UniformExponential Gaussian
Uniform Exponential
GaussianUniform Expo
nentialGaussian
DSR High High Low Low Low Medium Low Low Medium
AODV High High Medium Medium Medium Low Medium Low High
DSDV Medium Medium Low Very high Very high Very high Medium Low High
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Table 2.4 Parameter ranges
RangesParameter\^^ Low Medium High
VeryHigh
Throughput 85 - 90 % 90-95% 95-100 % -
Delay < 0.05 sec 0.05-0.1 >0.1 -
Overhead <2000 2000 - 5000 5000-10000 >10000
The numerical result of the relative performance of the routing
algorithm for various traffic load conditions and the rate of transmission of
packets are given in Tables 2.5 and 2.6. For DSDV algorithm with Gaussian
mobility model the network simulator could generate a scenario and define the
connection pattern but does not generate the trace file and therefore the results
are not given in Table 2.6.
Table 2.5 Parameter comparison for various mobility models under
various traffic loads
Speed = 3m/s # of packets per sec = 4
RoutingAlgorithms
TrafficLoad(me)
% of Throughput Overhead Delay (secs)
UniformExponential Gaussian
Uniform Exponential
GaussianUniform Expo
nentialGaussian
DSR
5 95.14 97.26 91.08 861 908 981 .04154 .0714 .127610 97.38 96.91 90.19 1120 1551 1893 .02365 .0367 .353715 97.2 97.36 91.59 2179 1865 4615 .04329 .0517 .161820 1 97.38 92.1 3091 2939 4561 .02524 .03645 .063830 97.1 97.37 91.27 4995 3567 6340 .07231 .02574 .2805
AODV
5 95.70 95.98 93.36 4195 5241 5943 .01166 .01577 .022210 96.42 96.32 93.98 6549 5557 7073 .02055 .02728 .022715 96.63 97.15 94.69 9685 9445 14500 .01152 .01194 .022120 96.34 95.97 94.48 13.8*10’ 12.2*10’ 1.91*10’ .01245 .01159 .012930 96.56 96.78 90.02 18.9*10’ 16.1*10’ 24.1*10’ .01234 .01347 .0861
DSDV
5 92.44 94.65 93.31 44.9*10’ 44.7*10’ 43.2*10’ .07925 .04150 .058310 93.93 91.38 90.15 44.8*10’ 40.8*10’ 43.7*10’ .08212 .02375 .05715 94.20 90.34 90.03 44.9*10’ 44.7*10’ 43.6*10’ .05067 .02346 .081520 2.78 93.23 8822 44.4*10’ 40.2*10’ 44.4*10’ .02172 .03645 .058330 94.23 93.07 89.22 44.8*10’ 44.6*10’ 45.0*10’ .07349 .03255 .2837
67
Table 2.6 Parameter comparison for various mobility models under
different speeds
me = 10 # of packets per see = 10
RoutingAlgorithms
Speed(m/sec)
% of Throughput Overhead Delay (secs)
UniformExponential Gaussian Uniform
Exponential
GaussianUniform Expo
nentialGaussian
DSR
i 100 95.31 99.24 8 1083 67 .0029 .0903 .01242 93.33 92.93 89.13 1285 1359 1196 .0556 .1572 .04243 93.28 92.69 84/72 1370 1493 1113 .0502 .1059 .09774 66.24 92.39 81.85 1947 1308 2490 .2549 .2148 .12185 90.59 100 81.92 1214 8 2684 .1872 .0029 .4315
AODV
1 96.70 94.68 96.99 3819 3385 2837 .0236 .0517 .01752 93.73 93.73 95.32 5541 4944 4037 .0637 .0158 .04783 92.61 92.85 88.72 5528 5140 10.6*103 .0368 .0292 .02824 93.1 93.52 86.55 6407 6099 8.3*103 .2369 .0214 .01395 91,94 92.77 84.14 7388 5757 10.9*103 .1983 .6813 .4060
DSDV
1 97.12 96.39 44.9*103 44.9*103 .0131 .01392 94.54 94.52 44.8*103 44.8*103 .0122 .04883 92.32 91.86 44.9*103 44.6*103 .0283 .01374 91.17 92.65 48.9* 103 44.9*103 .0546 .01645 93.45 91.95 44.8*103 44.5*103 .0494 .0366
2.4 SUMMARY
In this chapter, the effect of various mobility models in ad hoc
networks with DSR, AODV and DSDV routing algorithms are studied. The
performance results of the all three algorithm are presented in detail. From the
simulation, it is observed that AODV and DSDV requires more control over
head as the network traffic increases. DSR is more suitable for smaller network
due to source routing. Also from the results of the throughput, end-to-end delay
and the control overhead parameters, it is found that the exponential model
outperforms the uniform and normal models for a wide range of speeds and
traffic loads. Based on this study, it is concluded that the exponential mobility
models are more suitable for the analysis and simulation of mobile ad hoc
networks.