ChapterPDF Available

A Novel Optimization of the Distance Source Routing (DSR) Protocol for the Mobile Ad Hoc Networks (MANET)

Authors:

Abstract and Figures

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.
Content may be subject to copyright.
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
[1] P. Papadimitratos and Z. Haas, “Secure Routing for Mobile Ad hoc
Networks,” In Proceedings of the SCS Communication Networks and
Distributed Systems Modeling and Simulation Conference (CNDS
2002), San Antonio, TX, January 27-31, 2002.
[2] J. Raju and J. Garcia-Luna-Aceves, “A comparison of on demand and
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
Protocol for Mobile Ad Hoc Networks. (DSR)," IETF INTERNET
DRAFT, 24 February 2003.
[5] V. Park and M. Corson, "A Highly Adaptive Distributed Routing
Algorithm for Mobile Wireless Networks," Sixteenth Annual Joint
Conference of the IEEE Computer and Communications Societies.
Driving the Information Revolution (INFOCOM '97), pp.1405, 1997.
Fig. 6. Time delay versus number of nodes
RIZVI ET AL. 274
... Source Routing (DSR) [24], and Temporarily Ordered Routing Algorithm (TORA) [25]. Hybrid protocols are a mix between the previous types where routes are kept proactively for nearby nodes and reactively 2.2. ...
Article
Wireless networking is one of the most challenging networking domains with unique features that can provide connectivity in situations where it is difficult to use wired networking, or when node mobility is required. However, the working environment usually imposes various constrains, where wireless devices face various challenges when sharing the communication media. Furthermore, the problem becomes worse when the number of nodes increase. Different solutions were introduced to cope with highly dense networks. On the other hand, a very low density can create a poor connectivity problem and may lead to have isolated nodes with no connection to the network. It is common to define network density according to the number of direct neighboring nodes within the node transmission range. However, we believe that such metric is not enough. Thus, we propose a new metric that encompasses the number of direct neighbors and the network performance. In this way, the network response, due to the increasing number of nodes, is considered when deciding the density level. Moreover, we defined two terms, self-organization and self-configuration, which are usually used interchangeably in the literature through highlighting the difference between them. We believe that having a clear definition for terminology can eliminate a lot of ambiguity and help to present the research concepts more clearly. Some applications, such as In-Flight Entertainment (IFE) systems inside the aircraft cabin, can be considered as wirelessly high dense even if relatively few nodes are present. To solve this problem, we propose a heterogeneous architecture of different technologies to overcome the inherited constrains inside the cabin. Each technology aims at solving a part of the problem. We held various experimentation and simulations to show the feasibility of the proposed architecture. Furthermore, we introduced a new self-organizing identification protocol that uses smart antennas to help the Display Units and their Remote Controls, of the IFE system, to identify each other without any preliminary configuration. The protocol was firstly designed and verified using UML language, then, a NS2 module was created to experiment with different scenarios. The experimentation and simulation results proved that such heterogeneous architecture can provide a solution for the constrained wireless communication inside the cabin.
Conference Paper
Full-text available
The emergence of the Mobile Ad Hoc Networking (MANET) technology advocates self-organized wireless interconnection of communication devices that would either extend or operate in concert with the wired networking infrastructure or, possibly, evolve to autonomous networks. In either case, the proliferation of MANET-based applications depends on a multitude of factors, with trustworthiness being one of the primary challenges to be met. Despite the existence of well-known security mechanisms, additional vulnerabilities and features pertinent to this new networking paradigm might render such traditional solutions inapplicable. In particular, the absence of a central authorization facility in an open and distributed communication environment is a major challenge, especially due to the need for cooperative network operation. In particular, in MANET, any node may compromise the routing protocol functionality by disrupting the route discovery process. In this paper, we present a route discovery protocol that mitigates the detrimental effects of such malicious behavior, as to provide correct connectivity information. Our protocol guarantees that fabricated, compromised, or replayed route replies would either be rejected or never reach back the querying node. Furthermore, the protocol responsiveness is safeguarded under different types of attacks that exploit the routing protocol itself. The sole requirement of the proposed scheme is the existence of a security association between the node initiating the query and the sought destination. Specifically, no assumption is made regarding the intermediate nodes, which may exhibit arbitrary and malicious behavior. The scheme is robust in the presence of a number of non-colluding nodes, and provides accurate routing information in a timely manner.
Article
Full-text available
ns on the underlying trust, network size, and membership. SRP discovers one or more routes whose correctness can be verified from the route "geometry" itself. Route requests propagate verifiably to the sought, trusted destination. Route replies are returned strictly over the reversed route, as accumulated in the route request packet. In order to guarantee this crucially important functionality, the interaction of the protocol with the IP-related functionality is explicitly defined. An intact reply implies that (i) the reported path is the one placed in the reply packet by the destination, and (ii) the corresponding connectivity information is correct, since the reply was relayed along the reverse of the discovered route. The securing of the route discovery deprives the adversarial nodes of an "effective" means to systematically disrupt the communications of their peers. Despite our minimal trust assumptions, attackers cannot impersonate the destination and redirect data traffic, cann
Conference Paper
Full-text available
Secure operation of the routing protocol is one of the major challenges to be met for the proliferation of the mobile ad hoc networking (MANET) paradigm. Nevertheless, security enhancements have been proposed mostly for reactive MANET protocols. The proposed secure link state routing protocol (SLSP) provides secure proactive topology discovery, which can be beneficial to network operation in a number of ways. SLSP can be employed as a stand-alone protocol, or fit naturally into a hybrid routing framework, when combined with a reactive protocol. SLSP is robust against individual attackers, is capable of adjusting its scope between local and network-wide topology discovery, and is capable of operating in networks of frequently changing topology and membership.
Conference Paper
Full-text available
With on-demand routing, a router maintains routing information for only those destinations that need to be reached by the router. The approaches used to date to eliminate long-term or permanent loops in on-demand routing consist of obtaining complete routes to destinations dynamically, or obtaining only the next hops to destinations and validating the information using sequence numbers or internodal synchronization. We present a new approach to on-demand routing, which we call the DST (dynamic source tree) protocol. To eliminate looping, routers in DST communicate paths to destinations; however, only incremental updates to such paths are communicated by specifying the second-to-last hop and distance to each node in the subpath to the destination that must be updated. Simulation experiments are used to show that, in terms of control packet overhead, DST outperforms substantially the dynamic source routing (DSR) protocol which is arguably one of the most efficient on-demand routing approaches to date, while achieving similar performance in terms of the average delay and throughput of data packets
Conference Paper
Full-text available
We introduce WRP-Lite, which is a table-driven routing protocol that uses non-optimal routes, and compare its performance with the performance of the dynamic source routing (DSR) protocol, which is an on-demand routing protocol for wireless ad-hoc networks. We evaluate the performance of WRP-Lite and DSR for varying degree of mobility and traffic in a 20-node network. The performance parameters are end-to-end delay, control overhead, percentage of packets delivered, and hop distribution. We show that WRP-Lite has much better delay and hop performance while having comparable overhead to DSR
Conference Paper
We present a new distributed routing protocol for mobile, multihop, wireless networks. The protocol is one of a family of protocols which we term “link reversal” algorithms. The protocol's reaction is structured as a temporally-ordered sequence of diffusing computations; each computation consisting of a sequence of directed link reversals. The protocol is highly adaptive, efficient and scalable; being best-suited for use in large, dense, mobile networks. In these networks, the protocol's reaction to link failures typically involves only a localized “single pass” of the distributed algorithm. This capability is unique among protocols which are stable in the face of network partitions, and results in the protocol's high degree of adaptivity. This desirable behavior is achieved through the novel use of a “physical or logical clock” to establish the “temporal order” of topological change events which is used to structure (or order) the algorithm's reaction to topological changes. We refer to the protocol as the temporally-ordered routing algorithm (TORA)
Article
We present a new distributed routing protocol for mobile, multihop, wireless networks. The protocol is one of a family of protocols which we term "link reversal" algorithms. The protocol's reaction is structured as a temporally-ordered sequence of diffusing computations; each computation consisting of a sequence of directed l i nk reversals. The protocol is highly adaptive, efficient and scalable; being best-suited for use in large, dense, mobile networks. In these networks, the protocol's reaction to link failures typically involves only a localized "single pass" of the distributed algorithm. This capability is unique among protocols which are stable in the face of network partitions, and results in the protocol's high degree of adaptivity . This desirable behavior is achieved through the novel use of a "physical or logical clock" to establish the "temporal order" o f t opological change events which is used to structure (or order) the algorithm's reaction to topological changes. We r...