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A Novel Optimization of the Distance Source

Routing (DSR) Protocol for the Mobile Ad Hoc

Networks (MANET)

Syed S. Rizvi

1

, Majid A. Jafri, and Khaled Elleithy

Computer Science and Engineering Department

University of Bridgeport

Bridgeport, CT 06601

{srizvi, majidals, elleithy}@bridgeport.edu

Aasia Riasat

Department of Computer Science

Institute of Business Management

Karachi, Pakistan 78100

aasia.riasat@iobm.edu.pk

1

Contact author: srizvi@bridgeport.edu,

Abstract- This paper presents a new scheme for the Distance

Source Routing (DSR) protocol which shows the improvement

over the two major metrics of the DSR protocol: Route

Discovery and Route Maintenance. In addition, we present a

mathematical model that includes probability density function

for these two observed metrics. Our simulation results

demonstrate a significant improvement in the route discovery,

transmission time, and the overall network utilization. As an

interesting side result, our analysis also shows that the

proposed model can be used to effectively reduce the packet

losses.

Keywords- DS-CDMA, bit error rate, data throughput, multiuser

communications

I. INTRODUCTION

The Dynamic Source Routing (DSR) protocol is dealt

under On-Demand Routing (ODR) protocol which is just an

exact opposite to the Table-Driven Routing (TDR) [2, 3].

Generally, there are two main phases use in the DSR

protocol. One is the Route Discovery (RD) phase which

discovers all the possible paths for the packets to be

transferred from a particular source to a destination. It is

essential to properly maintain the RD phase since

maintaining a separate table for storing routing details

involves cost issues. The second phase of the DSP protocol is

the Route Maintenance (RM) phase which fixes all the

possible paths from one particular source to a destination [5].

In DSR, the packets are transmitted only one time for each

node. If the node does not receive the packet, the previous

node is responsible to make attempts in order to transmit the

packet. On the other hand, if the destination node receives

the packet successfully, an acknowledgment is transmitted

back to the source node for the received packet. Since the use

of the DSR protocol does not require the maintenance of a

cache table, it allows us to avoid unnecessary updating works

which results space and time saving advantages.

In the existing DSR scheme, the malfunctioning of one or

more links along a certain route requires the retransmission

of all packets back to the originating source node. This

unnecessary amount of retransmission results a significant

transmission overhead that can severely degrade the overall

network performance by increasing the average time delay.

In order to minimize the transmission overhead and

maximize the network throughput, we present an alternative

scheme that can be used to optimize the performance of DSR

protocol. Specifically, our proposed scheme suggests

improvement in the RD and the RM metrics of the DSR

protocol. Based on the proposed optimization, we derive a

mathematical model which proves the correctness of the

proposed scheme.

II. PROPOSED OPTIMIZATION FOR THE DSR PROTOCOL

Our main goal is to maintain the original underlying

architecture of the DSR protocol. Therefore, we consider the

DSR scheme as a black box. The DSR protocol fails to

maintain route consistency in the presence of broken links.

When one of the links goes down, the DSR protocol locates

an alternate route and transmits back the packet to the source

node where the packet was originated. On contrary to the

actual scheme of the DSR protocol, our proposed scheme

uses a reserve direction search method. In our proposed

scheme, the packets would be transmitted to the immediate

prior node where the actual error was occurred. The

proposed scheme then finds one or more alternative routes

from the current location to the destination. This implies that

the whole searching procedure of the proposed scheme will

T. Sobh et al. (eds.), Novel Algorithms and Techniques in Telecommunications and Networking,

DOI 10.1007/978-90-481-3662-9_46, © Springer Science+Business Media B.V. 2010

be done in the opposite direction starting from the

destination node. Our simulation results demonstrate that the

proposed scheme considerably increases the chance of

finding a valid route for salvage packets that are typically

stored in the send buffer.

For instance, consider an example for locating a route

based on the reverse direction search scheme as shown in

Fig. 1. It can be observed that the route finds by the RD

procedure from node A (source node) to L would be:

ADEIL. During transmission of the packets, it is

detected at run time that the shortest link between node E

and I goes down. Consequently, the proposed scheme

immediately starts searching the best available alternate

routes. In order to reach the destination node, the proposed

scheme locates the neighboring nodes (i.e., node B, D, and H

from node E). This process of finding the alternate route

from the location of error results an optimal alternate route:

A

D

E

I

H

L. This implies that our proposed scheme

neither send any feedback to the destination node A nor it

initiates the route discovery from the source point. Therefore,

repeating this search in the reverse direction from the current

location of error to the neighboring nodes results a

significant increase in the chance of finding a valid

optimized route.

A. Proposed Reverse Direction Search Scheme

In order to formulate the proposed scheme, we present a

model that shows simple steps that need to be implemented

for finding a valid and optimize route in the presence of link

failures. The model is presented in Fig. 2. The model is

typically divided into two parts. The upper part of the model

represents the RD procedure where as the lower part

represents the RM procedure. The RD procedure is based on

an exhaustive search of an internal cache. During the

transmission of a packet, if one of the links goes down, the

proposed scheme mentions that the packet will be

immediately forwarded to the next available node and starts

transmitting from the new location. Unlike the DSR

protocol, the proposed scheme minimizes the transmission

overhead by avoiding the unnecessary transmission of data to

the source node in the presence of a faulty link. In other

words, the proposed scheme does not provide any feedback to

the source node that leads to a significant improvement in

the network throughput. Since the RD can be done on the

current node, we do not need to focus on the source node.

This implies that the proposed scheme suggests the best

Fig. 2. Flow chart showing proposed model of DSR algorithm

Fig.1. Finding the alternate path in DSR protocol according to the

proposed scheme

RIZVI ET AL. 270

delivery of the packets even in the presence of link failure. In

addition, the repetition of the packets due to the flooding will

be cut down.

In the proposed model, we mainly focus on the RD and the

RM. During the RD process, if the entries are found in the

internal cache of the next node, the proposed scheme

determines the optimal path that will be used to forward all

the packets to the next node. At that current node location,

the same procedure for searching the optimal path will be

repeated over the passage of time in order to find the best

path towards the destination. An empty entry in the internal

cache represents that there is no valid route exist for a

particular destination. In such a scenario, the proposed

scheme will lookup into the next neighbor’s cache and

determine the best available route for the desired destination.

Once the optimal route is discovered, the packet can then be

transmitted. In the RM process, whenever there is a link

failure along the path, the packet would not go further at the

point of error and there is no need to send any feedback to

the original source node. Instead, the proposed scheme

determines and performs the RM process on the best

available alternate path.

B. Mathematical Model

We derive our mathematical model based on the proposed

reverse direction scheme. In our mathematical model, we

show that the transmission of packets via an alternate route

is more efficient as compared to transmitting packets from

the source node using a primary route. This is especially true

in the presence of error. All system variables, along with

their definition, are listed in Table I.

The accuracy of the proposed scheme is essentially

dependent on how efficiently we can discover the alternate

routes in the presence of faulty links. In general, the accuracy

is partially related to a certain interval by which we perform

the RD procedure for a specific type of network traffic such

as a stream of packets. In particular, we first need to derive

an expression for a random variable, x, that can be used to

characterize the behavior of RD process with respect to time.

Therefore, in order to implement the proposed scheme, one

must measure the frequency of route discoveries. In order to

determine the interval between the route discoveries, the

following mathematical expression can be derived for a

random variable, x:

( )

xf x dx

+∞

−∞

∫

(1)

It should be noted that equation (1) is based on the PDF

which is used to find the frequency of route discovery for a

particular pair of source and destination.

Figure 4 represents the proposed scheme with the primary

and the secondary paths along with their corresponding

links. It can be seen in Fig. 3 that the node P represents the

primary route whereas the node S represents the secondary

route. If an error occurs in the primary route, the proposed

scheme will immediately discover an alternate route S

1

rather

than going back to the source node A. In other words, in the

presence of faulty links, the proposed scheme searches the

internal cache and determines the alternative route S

1

which

is typically stored in the local cache.

For this particular scenario, the success of the proposed

scheme is heavily dependent on the rate at which one may

need to execute the RD procedure. In addition, the success of

the proposed scheme is not only dependent on the rate at

which the RD procedure will be performed but also

dependent on the accuracy and the efficiency by which the

alternate routes will be determined. In order to find the

frequency of an alternative RD, we assume that an event E

might occur at a discrete point in time in the network which

causes an error in one of the two types of routes (i.e., the

primary P and the secondary S routes). Thus the

transmission of an event can be mathematically described as:

1 1 2 1 2 1 3 1 2 3 2 1

( ( ) ) ( ( ( ) ) ...

E PS P P S S P P P S S S

= + + + + +

(2)

TABLE I

SYSTEM PARAMETERS AND DEFINITIONS

Parameters Description

P

i

This represents the ith link in a primary path.

S

i

This represents the ith link in a secondary path.

X

Pi

Life time of the ith primary route.

X

S

i

Life time of the ith secondary route.

X

R

Minimum life time for the collection of all values in

the primary path links

T

Intervals for route discovery

E

o

An event that shows any of the given link fails

f

T

(t)

Frequency of route discovery

Z

i

Maximum life time among all available values.

i

P

Represents the faulty primary link due to an event E

i

S

Represents the faulty secondary link due to an event E

Fig. 3: Proposed scheme with primary and secondary path and their links

A NOVEL OPTIMIZATION OF THE DISTANCE SOURCE ROUTING (DSR) PROTOCOL

271

where

i

P

represents the faulty primary-link where as

i

S

represents the faulty secondary-link which caused due to the

occurrence of an event E at discrete point in time within a

network.

Equation (2) represents a generic equation that shows how

the occurrence of an event in the network may cause an error

in the alternate routes. Equation (2) can be further extended

for the maximum K number of forwarding links within the

available primary paths. It should be noted that the

occurrence of an event E is representing a cause of

malfunctioning in the currently used valid route. Taking

these factors into account, one may write the following

mathematical expression:

1 1 2 2 1 3 3 2 1

1 1

...

k k k

E P S P S S P S S S

P S S S

−

= + +

+ +

(3)

where

i

P

and

i

S

in (3) represent the faulty primary and

secondary links, respectively. Both of these faulty links are

caused due to the occurrence of an event E at a discrete point

in time within a network. It should be noted that we only

consider the values of the most forwarding links that one

may find within the primary path links from the generic

equation (2).

One of our observations about the two phases of the

proposed scheme is the life time of the primary path which

we use to transmit the packets to the desired destination in

the presence of the faulty links. In other words, in order to

effectively implement the proposed scheme, we must

determine the minimum value of the life time for primary

path links. This calculation is essential, since the ration of

determining the accurate valid primary links is critically

dependent on the knowledge of accurate values of lifetime.

The minimum life time of primary path links is simply

chosen from one of the primary links that has a smallest

value for the life time. In other words, if one of the ith

primary routes has the smallest life time value, this will be

chosen as a minimum life time value for the primary path

links. This hypothesis can be changed into a simple

expression:

1 2

, ,....,

R p p pk

X Min X X X

= (4)

where X

R

in (4) represents the minimum life time value for

the collection of all values in the primary path links. The

right hand side expression of (4) represents the life time of

each individual primary route starting from X

p1

to

X

pk

. These

values are considered as a life time of the sub links in the

primary path. Similar to (4), we can further extend our

mathematical model for computing the interval of time for

the RD procedure:

1 2

, ,....,

s s sn

T Max X X X

= (5)

where T represents the intervals of time for the RD and X

Si

represents the life time of the ith secondary route.

Equation (5) gives an estimate of the time to be taken by

the proposed scheme for the RD procedure. This value is

evaluated from the maximum values of the collected time in

the sub links of the secondary path. The right hand side

expression of (5) represents the life time of each individual

secondary route starting from X

s1

to X

sn

. For the sake of the

simulation and the performance evaluation, we assume that

the value of T will be measured in millisecond. Combining

(4) with (5), we can compute the value of the alternative

route discovery as follows:

1 1 2 2 1

1 1

( . ), ( . . )

... ( , , ,.... )

p s p s s

pk sk sk s

Max X X Max X X X

T Min

Max X X X X

−

=

(6)

Equation (6) gives the value of the alternative RD. This

can be considered as the optimum value which is determined

from all the available maximum values for both the primary

and the secondary links. Using (6), we can compute the

values for the RD metrics which is one of the subparts of the

proposed scheme.

Z

i

=

1 1

, , , ....,

p i s s i s

M a x X X X X

−

(7)

where Z

i

represents the maximum life time among all

available values for both primary and the secondary paths.

Recall (1), we can now derive an expression for the

frequency of RD using equations (2) to (6).

1

1

( ) (1 )

i k

NN

t t

T i

i

k k i

f t e e

λ λ

λ

− −

=

= ≠

= −

∑ ∏

(8)

where the right hand side of (8) represents the frequency of

RD.

Equation (7) also has a significant impact on the RD for

the alternate path. Implementing the results of (7) on (8), we

can derive a new expression for the frequency of the RD

which take into account the maximum life time among all

available values for both primary and the secondary paths. In

addition, this implementation describes the PDF in Z

i

with

respect to the RD metrics.

RIZVI ET AL. 272

(

)

( )

1

1

( )

1

1,

( )

( )

(1 )

i

j

i

i

Zi

i

j

k k j

i e j t

f t

e k t

λ

λ

λ

−

+

+

−

=

= ≠

=

−

∑

∏

(9)

where

( )

/ 1,2....

i

j

ki l for j i

λ

= → = and for 1/l

j=i+1.

Equation (9) describes the summation of all the possible

routes which can lead us to the desired destination. Equation

(9) can be further extended for the following given

expressions:

1 1 2 2 1

1 1

( . ), ( . . )

... ( , , ,.... )

p s p s s

pk sk sk s

Max X X Max X X X

T Min

Max X X X X

−

=

1 1

( , , .... )

i pi si si s

Z Max X X X X

−

=

1 2 3

( , , .... )

k

T Min Z Z Z Z

=

Based on the above three expressions, we can approximate

the PDF of T for the frequency of RD as follows:

0

( ) lim [ ]/

T

dt

f t p t T t dt dt

→

= ≤ ≤ + (10)

Equation (10) gives the value for the frequency of the RD

in terms of a PDF function. Relating (8) and (9) with (10),

we can derive the following mathematical expression

1 1, 1

1

1, 1

( ) ( ) [ ]

( ) ( ) (1 ( ))

kk

T Zi j i

i j j

kk

T Zi i

i

j j

f t f t p z z

f t f t Fz t

= = ≠

=

= ≠

= >

= −

∑ ∏

∑

∏

(11)

where, F

zi(t)

in (11) was introduced from (7) to make Z

i

as a

function of PDF.

Equation (11) shows that we derived the expected

expression which can be used to compute the interval

between the rout discoveries. In other words, one could use

(11) to determine the frequency of the alternate RD process.

The same frequency value can be used to measure the

efficiency of the network. In addition, the final results show

that the use of the proposed reverse direction scheme with

the derived mathematical model can effectively minimize the

transmission delay especially in the presence of collisions

(links error) or faulty links due to the malfunctioning.

III. SIMULATION RESULTS

We simulate our model based on the predicted data from

the existing DSR model suggested in [1, 4]. For the sake of

simulation and the performance evaluation, we consider two

major metrics for RD and RM. These metrics are considered

for the evaluation of the efficiency of a network.

For the sake of the first simulation (see Fig. 4), we

characterize the behavior of the RD phase of the proposed

scheme with respect to the number of nodes present in the

network. The purpose of this experiment is to show the

performance of the RD phase for discovering the alternate

primary and the secondary path. During the simulation, we

consider that as the number of nodes increases in the

network, the more packets will be accumulated in the

network that could affect the performance of the RD phase. It

can be clearly evident in Fig. 4 that the RD phase of the

proposed scheme performs better for the primary paths

discoveries than for the secondary path. When we have small

Fig.4. Number of nodes versus RD

Fig. 5. Packet loss in fractions versus number of nodes

A NOVEL OPTIMIZATION OF THE DISTANCE SOURCE ROUTING (DSR) PROTOCOL

273

number of nodes, it can be seen in Fig. 4 that the

performance of the RD phase for both primary and secondary

path discoveries is overlapping. However, as network grows

in terms of the number of nodes, the performance differences

between the primary and the secondary path is obvious.

Fig. 5 shows the packet losses (in the fraction value) with

respect to the number of nodes during the transmission using

both primary and the secondary paths. In addition, Fig. 6

represents a comparison between the time delay (represents

in seconds) and the number of nodes. It can be seen in Fig. 6

that the time required to discover the primary paths using the

RD phase is very low as compared to the time required to

discover the secondary paths.

Based on the simulation results of Fig. 6, we can observe

that the time delay for primary paths is not only small but

also linear with respect to the number of nodes. In other

words, when we increase the number of nodes in the

network, more packets will be accumulated that make a

linear increase in the time delay for discovering the

secondary paths which is not really desirable as far as the

optimum performance of the DSR protocol is concerned.

IV. CONCLUSION

In this paper, we presented a new scheme that improves

the retransmission mechanism for the existing DSR protocol.

In order to support our hypothesis, we provided a complete

mathematical model that shows the formulation of the

proposed scheme. In particular, we investigated the RD and

the RM phases with respect to the proposed reverse direction

scheme. We also showed that how effective the proposed

scheme would be when we implement it with the reverse

direction search for discovering the primary paths. Our

analysis also suggested that the discovery of alternate

primary paths from the current source of error significantly

improves the network performance in terms of RD process,

time delay, and the packet losses. Moreover, we have

experimentally verified that both the RD and the RM metrics

perform well with the proposed scheme than the existing

infrastructure of the DSR protocol. Our performance

evaluation is also well supported by the simulation results

presented in this paper.

REFERENCES

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2002), San Antonio, TX, January 27-31, 2002.

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table driven routing for ad-hoc wireless networks,” In Proc. IEEE

International Conference on Communications (ICC 2000), June 2000.

Volume 3, Issue 2000, pp. 1702 – 1706, 2000.

[3] J. Raju and J. Garcia-Luna-Aceves, “Efficient On-Demand Routing Using

Source-Tracing in Wireless Networks,” In Proc IEEE Global

Telecommunications (GLOBECOM 2000), Vol. 1, Issue 2000, pp. 577 –

581, November 2000.

[4] B. Johnson, A. Maltz, and Y. Chun, "The Dynamic Source Routing

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[5] V. Park and M. Corson, "A Highly Adaptive Distributed Routing

Algorithm for Mobile Wireless Networks," Sixteenth Annual Joint

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Fig. 6. Time delay versus number of nodes

RIZVI ET AL. 274