Performance Comparison of Ad Hoc Routing Protocols: An ...

Performance Comparison of Ad Hoc Routing Protocols: An
Implementation Study
Dr. Kendall Nygard
Professor,
Dept. of Computer Science
North Dakota State University, Fargo
Phone No.:701-231-8203
E-mail: Kendall.Nygard@ndsu.edu
Kanwalinder jit Kaur
PhD Student,
Dept. of Computer Science
North Dakota State University, Fargo
Phone No.701-364-7994
E-mail: kanwalinder.gagneja@ndsu.edu
ICWN'08: International Conference on Wireless Networks
ABSTRACT
Using simulation methodologies, we empirically compare the performance of TORA,
AODV and DSR routing algorithms for ad hoc mobile networks. Four performance
metrics are evaluated. The results show that the throughput of sending/receiving bits is
highest for DSR, average with AODV and lowest with TORA. The throughput of
dropping bits in DSR is almost Zero, average with AODV and highest with TORA. The
throughput of sending bits versus average simulation end to end delays for DSR is the
highest, average for AODV and lowest for TORA. For sending bits versus average
simulation jitter the throughput is highest for DSR, average for AODV and lowest for
TORA.
Key Words: Ad Hoc Mobile Networks, Jitter, Throughput, Routing Protocols.
INTRODUCTION
Routing has long been a key challenge in Mobile Ad-hoc Networks (MANETs). Many routing
protocols for MANETs have been proposed and these protocols can be classified into different
categories using several criteria. If classified by the manner in which they react to network
topology changes, routing protocols can be grouped into proactive protocols and reactive
protocols [11]. If classified by the role of routing nodes and the organization of the network,
routing protocols can be grouped into flat protocols and hierarchical protocols.
Proactive protocols propagate topology information periodically and find routes continuously,
while reactive protocols find routes on demand. Performance analysis and simulation results
typically show that reactive protocols outperform proactive protocols in terms of packet delivery
ratio, routing overhead, and energy efficiency [10]. We focus our work on reactive protocols. The
Dynamic Source Routing protocol (DSR), Ad hoc On-demand Distance Vector routing protocol
(AODV), and Temporally Ordered Routing Protocol (TORA) are all reactive routing protocols.
1. Dynamic Source Routing (DSR): Because it is a reactive routing protocol, the
Dynamic Source Routing (DSR) Protocol manages a MANET without using periodic tableupdate
messages as do the table-driven routing protocols. DSR was designed for use in multi-hop
wireless ad hoc networks. DSR allows the network to be completely self-organizing and selfconfiguring,
which eliminates the need for an existing network infrastructure or administration.
The process to find a path is only executed when a path is required by a node (On-Demand
Routing) [3, 4, 5, 7], which avoids the misuse of bandwidth. The sender using the DSR protocol

knows the whole path from the source to the destination node (called Source-Routing) and
includes the addresses of the intermediate nodes of the route in the packets. DSR does not use
hello-messages between the nodes to notify their neighbors of their presence. DSR basically is
based on the Link-State-Algorithms [11], in which each node is capable of saving the best route
to a destination. Also if a change appears in the network topology, then the whole network will
get this information by flooding.
2. Ad hoc On demand Distance Vector (AODV): The Ad hoc On demand Distance Vector
(AODV) routing algorithm is also designed for MANETs. It is an on demand algorithm, meaning
that it maintains routes as long as they are needed by the sources. AODV uses sequence numbers
to ensure the freshness of routes [3]. These routes are loop-free, self-starting, and scale to large
numbers of mobile nodes.
3. Temporally-Ordered Routing Algorithm (TORA): The Temporally-Ordered Routing
Algorithm (TORA) is an algorithm for routing data across MANETs. TORA does not use a
shortest path to the greatest extent possible for message propagation. TORA generates and
maintains a Directed Acyclic Graph rooted at a destination. No three nodes can have the same
height. Data can flow from nodes with higher heights to nodes with lower heights, meaning that
data can only flow downhill and can not flow back to the source [6, 13]. By maintaining a set of
totally-ordered heights at all times, TORA achieves loop-free routing.
t time of a link failure
oid originator id
r reflection bit indicates 0=original level 1=reflected level
d integer to order nodes relative to reference level
i the nodes id
The triplet (t, oid, r) is called the reference level. And the tuple (d, i) is an offset within that
reference level. Each node maintains a neighbor table containing the height of the neighbor
nodes. Initially the height of all the nodes is NULL and their quintuple is (-,-,-,-,i). The height of a
destination neighbor is (0, 0, 0, 0, dest).
EVALUATION
We used simulation to evaluate the three routing algorithms. The algorithms were implemented
using ten mobile nodes in a predefined network. In this network the source node is 0, and the
destination node or sink is 1. In all three algorithms, the initial route for data transmission is 0-3-
4-7-1 as shown in figures 1 and 2. But as the transmission progresses the nodes move, resulting in
the new and different route shown in figure 3. The random movement model is used for nodes
movement. The performance metrics addressed are the throughput of sending/receiving bits,
throughput of dropping bits, throughput of sending bits versus average simulation end to end
delays, and throughput of sending bits versus average simulation jitter.
SIMULATION ENVIRONMENT
The ns-2 simulator [1, 12] was used for the study. The hosts are placed on a square field of 600m
x 600m. The protocol used for data transmission is TCP/UDP. Acknowledgment Packets are also
TCP/UDP. Any source-destination (S-D) pair could be chosen for data transmission. The packet
size is 24 bytes. Each connection starts at a time from 1 simulated second and the simulation runs
for 150 simulated seconds.

PERFORMANCE ANALYSIS
Figure 1 Initial state of nodes
The performance of the algorithms was evaluated using the ns-2 simulator. The following key
issues are addressed:
1. Throughput of sending bits/receiving bits.
2. Throughput of dropping bits.
3. Throughput of sending bits versus average simulation end to end delays.
4. Throughput of sending bits versus average simulation jitter.
Figure 2 Initial route when data transmission starts from source 0 to destination 1

Figure 3 Final state when simulation ends, showing nodes in different positions in
comparison to initial state (fig. 1)
RESULTS
1. Throughput of sending bits/ receiving bits. For approximately the first 40 simulation
seconds the sending/receiving pattern for all three protocols is almost the same. After 40
simulation seconds the throughput of the TORA method remains almost the same, 2.5X10 5
bits/sec. For DSR the throughput increases to 3.5X10 5 bits/sec by 10 5 bits/sec but for AODV it
decreases to 1.5X10 5 bits/sec by almost 10 5 bit/sec. The sending/receiving behavior again
changes at approximately 95 simulation seconds. Throughput of TORA drops almost to Zero,
throughput of AODV increase to 3.5X10 5 bits/sec (i.e. by about 2X10 5 bits/sec) and for DSR it
dramatically rises to grater than 7X10 5 bits/sec (a total increase of 3.5X10 5 bits/sec). The sending
and receiving pattern are the same in all the three protocols. (fig. 4, 5).
Figure 4 Throughput of sending bits

Figure 5 Throughput of receiving bits
2. Throughput of dropping bits: At 55 simulation seconds the number of dropped bits in
TORA is the maximum 17X 10 4 bits/sec, the AODV has a 9.5X10 4 dropped bit rate, and DSR has
almost no dropped bits. (Figure 6)
Figure 6 Throughput of dropping bits
3. Throughput of sending bits versus average simulation end to end delays. Initially
all three algorithms show some transmission delay. DSR has the highest delay of about 2.0
simulated seconds, AODV has a lower delay of about 0.7 simulated seconds, and TORA has the
least (about 0.3 simulated seconds) when the throughput of sending bits is less than 1X10 5
bits/seconds (Figure 7). In AODV the delay is highest at 1.4 simulated seconds when throughput
is 1.5X10 5 bits/second. For AODV and TORA the delay stops when throughput is 3X10 5
bits/second, but continues for DSR until the transmission ends.

good, but throughput of sending bits versus average simulation end to end delays and throughput
of sending bits versus average simulation jitter is highest (which is not good). Among all three
protocols, AODV shows average behavior for all four metrics. For TORA the throughput of
sending/receiving bits is lowest and throughput of dropping bits is highest (which is not good),
but the throughput of sending bits versus average simulation end to end delays and the throughput
of sending bits versus average simulation jitter is lowest for TORA (which is good). Overall, the
results show that in one environment one protocol works best and in the other environment,
another works best.
FUTURE WORK
Although the empirical work performed thus far is insightful, a complete experimental design is
called for to provide statistical evidence for comparing these protocols. These experiments should
be performed on alternative network structures, including different number of nodes and different
node moving strategies. In this way, more general statements can be made.
REFERENCES
1. Fall K. and Varadhan K., ns notes and documentation, available from http://wwwmash.cs.berkeley.edu/ns/,
1999.
2. Gouda Mohamed G., “Elements of Network Protocol Design”, A Wiley-Interscience Publication, John
Wiley & Sons, Inc., New York, 1998.
3. Lu Yi, Wang Weichao, Zhong Yuhui, Bhargava Bharat, “Study of Distance Vector Routing Protocols
for Mobile Ad Hoc Networks”, the proceedings of First IEEE International Conference on Pervasive
Computing and Communications, (PerCom 2003), pp. 187-194, 23-26 March 2003.
4. Maltz D.A., Broch J., Jetcheva J., Johnson D.B., “The effects of on-demand behavior in routing
protocols for multihop wireless ad hoc networks”, IEEE Journal on Selected Areas in
Communications, Volume 17, Issue 8, pp.1439-1453, Aug. 1999.
5. Marina Mahesh K., Das Samir R., “On-demand Multipath Distance Vector Routing in Ad Hoc
Networks”, the proceedings of Ninth IEEE International Conference on Network Protocols, pp. 14-23,
11-14 Nov. 2001.
6. Pham P. Peter and Perreau Sylvie, “Performance Analysis of Reactive Shortest Path and Multi-path
Routing Mechanism With Load Balance”, the proceedings of 22 nd annual Joint Conference of IEEE
Computer and Communications Societies, INFOCOM2003, pp. 251-259, 1-3 April, 2003.
7. Perkins Charles E., Royer Elizabeth M., “Ad-hoc on-demand distance vector routing”, the proceedings
of Second IEEE Workshop on Mobile Computing Systems and Applications, WMCSA '99, pp. 90-
100, 25-26 Feb. 1999.
8. Randhawa T., Richards J., “Implementation of a kernel mode IPv6 AODV routing daemon to improve
data throughput”, IEEE International Conference on Communications, ICC 2005, Volume 5, pp. 3073-
3077, 16-20 May 2005.
9. Royer E.M., Perkins C.E, “An implementation study of the AODV routing protocol”, IEEE
International Conference on Wireless Communications and Networking, WCNC. 2000, Volume 3, pp.
1003-1008, 23-28 Sept. 2000.
10. Stallings William, “Computer Networking with Internet Protocols and Technology”, Pearson
Education, Inc., 2004.
11. Tanenbaum Andrew S., “Computer Networks”, Fifth Edition, PHI Publications, 2003.
12. http://nsnam.isi.edu/nsnam/index.php/User_Information#Documentation, 2008.
13. http://en.wikipedia.org/wiki/, 2008.