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					    Performance Studies of MANET Routing Protocols in the Presence of
             Different Broadcast Route Discovery Strategies

                                         Dr. Natarajan Meghanathan
                                        Department of Computer Science
                                           Jackson State University
                                               Jackson, MS 39217
                                        Email: nmeghanathan@jsums.edu

                                                  ABSTRACT
           Simulation studies for the Mobile Ad hoc NETwork (MANET) routing protocols have so
           far employed flooding as the default mechanism of route discovery. During flooding,
           each node broadcasts the packet exactly once, causing the broadcast storm problem [1].
           Several efficient broadcasting strategies [1][2] that reduce the number of retransmitted
           route query packets and the number of retransmitting nodes have been proposed in the
           literature. These include the probability-based, area-based and neighbor-knowledge
           based methods to reduce the retransmission overhead. Our contribution in this paper is an
           ns-2 simulation based analysis on the impact of employing these broadcasting strategies
           for route discovery on the hop count and stability of routes. We use the minimum-hop
           based Dynamic Source Routing (DSR) protocol [3] and the stability-based Flow-
           Oriented Routing Protocol (FORP) [4] as the routing protocols for our analysis. We
           compare the hop count and stability of DSR and FORP routes determined under
           conditions that guarantee at least 92-95% success in route discoveries and simultaneously
           minimize the number of retransmissions and retransmitting nodes.

               Keywords: Broadcasting, Routing, Stability, Hop count, Mobile Ad Hoc
               Networks


1   INTRODUCTION                                          called flooding to discover the routes. Whenever a
                                                          source node has data to send to a destination node,
    A Mobile Ad hoc NETwork (MANET) is a                  but does not have the route to the same, it will
dynamic distributed system of autonomously moving         initiate a broadcast route-query process. In the case
wireless nodes (such as laptops, personal digital         of flooding, the source node broadcasts a Route-
assistants, etc) and lacks a fixed infrastructure. The    Request-Query (RREQ) packet to its neighbors. Each
network has limited bandwidth as the wireless             node in the network will broadcast this RREQ packet
medium is shared and is prone to transmission             exactly once when they see it the first time. The
interference. Nodes are battery-powered and               destination node receives the RREQ packets along
operated with a limited transmission range. As a          several paths, chooses the best route according to the
result, routes in MANETs are often multi-hop in           route selection principles of the particular routing
nature and have to be discovered by the nodes             protocol and notifies the source node about the
themselves. There is no centralized administration        selected route using a Route-Reply (RREP) packet.
like in cellular networks. Several unicast and                 Flooding is a very expensive process with respect
multicast MANET routing protocols have been               to the bandwidth and energy usage. With resource-
proposed in the literature. The route discovery could     constrained environments like those of MANETs,
be either proactive or reactive. In the proactive         employing flooding for on-demand route discovery
approach, nodes determine and maintain routes for         will be very costly. Flooding also introduces lot of
every possible source-destination pair, irrespective of   redundancy in the packet retransmission process. In
their requirement. Reactive or on-demand MANET            [1], it has been observed that with flooding, when a
routing protocols determine a route only when             node receives a packet for the first time, at least 39%
required. It has been observed [5][6] that with a         of the node’s neighborhood would have also received
dynamically changing network topology where route         the message simultaneously and on average only
accuracy and routing overhead are crucial, on-            41% of additional area could be covered with a
demand routing protocols are to be preferred over the     rebroadcast. In general, when a node rebroadcasts a
proactive protocols. We will focus only on on-            message after hearing it k times, the expected
demand routing for the rest of this paper.                additional coverage decreases exponentially with
    Currently, all the on-demand MANET routing            increasing values of k [1]. These observations
protocols employ a simple form of broadcasting            motivated researchers to introduce several efficient
broadcasting strategies that will minimize the            study the impact on two principal routing metrics,
number of redundant retransmissions and at the same       viz., the stability and hop count. We compare the
time maximize the chances of the broadcasted              stability and hop count of DSR and FORP routes
message reaching all the nodes in the network.            chosen with these broadcasting techniques with those
    The techniques for efficient broadcasting can be      discovered using flooding. Flooding helps to
grouped into three families [1][2]: probability-based     discover the minimum hop routes for DSR and the
methods, area-based methods and the neighbor              most stable routes for FORP. But, these efficient
knowledge-based methods. In probability-based             broadcasting techniques may not yield the minimum
methods, each node is assigned a probability for          hop routes for DSR or the most stable routes for
retransmission. In area-based methods, a common           FORP.
transmission range is assumed and a node will                 The rest of the paper is organized as follows: In
rebroadcast if only sufficient new area can be            Section 2, we briefly discuss the DSR and FORP
covered with the retransmission. In neighbor-             protocols. Section 3 discusses the different
knowledge based methods, each node stores                 broadcasting techniques that have been published in
neighborhood state information and uses it to decide      the literature. Section 4 describes the simulation
whether to retransmit or not. One or more                 environment, illustrates the results and interprets
broadcasting techniques have been proposed under          them. Section 5 concludes the paper. Note that we
each of the above three families. The objective of all    use the words ‘route’ and ‘path’, ‘message’ and
these broadcasting techniques is to minimize the          ‘packet’,      ‘rebroadcast’     and     ‘retransmit’
number of retransmitted messages and the number of        interchangeably in this paper.
nodes retransmitting the message. More information
on the different broadcasting techniques can be           2   REVIEW   OF            MANET         ROUTING
found in Section 3.                                           PROTOCOLS
     The performance of the different efficient
broadcasting techniques under different conditions of        In this section, we briefly review the minimum-
topology changes and offered broadcast traffic has        hop based Dynamic Source Routing (DSR) protocol
been studied in [2]. As the number of retransmitting      [3] and the stability-based Flow-Oriented Routing
nodes and the retransmitted messages get reduced          Protocol (FORP) [4] – the two protocols we use for
when using these broadcasting techniques for RREQ         our simulation analysis.
propagation, the quality of the routes chosen may be
different compared to those routes discovered using       2.1 Dynamic Source Routing (DSR) Protocol
simple flooding. This formed the motivation for us to
implement these broadcasting techniques and use               The unique feature of DSR [3] is source routing:
them for route discovery in on-demand MANET               data packets carry the route from the source to the
routing protocols.                                        destination in the packet header. As a result,
     On-demand MANET routing protocols can be             intermediate nodes do not need to store up-to-date
classified into two broad categories [7]: minimum-        routing information. This avoids the need for beacon
weight based routing protocols and stability-oriented     control neighbor detection packets that are used in
routing protocols. The Dynamic Source Routing             the stability-oriented routing protocols. Route
(DSR) protocol [3] is a well-known minimum-               discovery is by means of the broadcast query-reply
weight based protocol that selects routes with the        cycle. A source node s wishing to send a data packet
minimum hop count. The Flow-oriented Routing              to a destination d, broadcasts a Route-Request
Protocol (FORP) [4] was observed to discover the          (RREQ) packet throughout the network. The RREQ
most stable routes within the class of stable path        packet reaching a node contains the list of
routing protocols [8]. The stability of routes selected   intermediate nodes through which it has propagated
by a routing protocol is quantified in terms of the       from the source node. After receiving the first RREQ
number of route transitions incurred by the protocol      packet, the destination node waits for a short time
for a source-destination (s-d) session. More              period for any more RREQ packets and then chooses
information on DSR and FORP is provided in                a path with the minimum hop count and sends a
Section 2.                                                Route-Reply Packet (RREP) along the selected path.
     In this paper, we implement the probability-         If any RREQ is received along a path whose hop
based method, the distance-based technique (area-         count is lower than the one on which the RREP was
based method), the Multi-Point Relaying (MPR) and         sent, another RREP would be sent on the latest
the Minimum Connected Dominating Set (MCDS)               minimum hop path discovered.
based techniques (neighbor-knowledge based
method) as the route discovery strategies for DSR         2.2 Flow-Oriented Routing Protocol
and FORP and study the impact of these
broadcasting techniques on the quality of routes              FORP [4] utilizes the mobility and location
chosen by the two routing protocols. We specifically      information of nodes to approximately predict the
Link Expiration Time (LET) for each wireless link.          process continues until each node in the network has
FORP selects the route with the maximum Route               retransmitted the packet. As a result, all nodes
Expiration Time (RET), which is the minimum of the          reachable from the source receive the packet.
LET values of the constituent links of the route. Each      Flooding causes the broadcast storm problem [1]
node periodically sends a beacon control message to         which is characterized by redundant rebroadcasts,
its neighbors and the message includes the current          channel contention and collision of messages.
position of the nodes, velocity, the direction of
movement and the transmission ranges. Each node is          3.2 Probability-based Methods
assumed to be able to predict the LET values of each
of its links with the neighboring nodes based on the        3.2.1 Probabilistic Scheme
information collected using beacon packets. FORP                When a node receives a broadcast message for
assumes the availability of location identifying            the first time, the node rebroadcasts the message with
techniques like GPS (Global Positioning System) [9]         a probability P. If the message received is already
and also assumes that the clocks across all nodes are       seen, then the node drops the message irrespective of
synchronized.                                               whether or not the node retransmitted the message
   Given the motion parameters of two neighboring           when received for the first time. For sparse networks,
nodes, the duration of time the two nodes will remain       the value of P has to be high enough to facilitate a
neighbors can be predicted as follows: Let two nodes        higher packet delivery ratio. When P = 1, the scheme
i and j be within the transmission range of each other.     resorts to simple flooding.
Let (xi, yi) and (xj, yj) be the co-ordinates of the
mobile hosts i and j respectively. Let vi, vj be the        3.2.2 Counter-based Scheme
velocities and Θi, Θj, where (0 ≤ Θi, Θj < 2π) indicate         A broadcast message received for the first time is
the direction of motion of nodes i and j respectively.      not immediately retransmitted to the neighborhood.
The amount of time the two nodes i and j will stay          The message is queued up for a time called the
connected, Di-j, can be predicted as follows:               Random Assessment Delay (RAD) during which the
                                                            node may receive the same message (redundant
           − (ab + cd ) +   (a 2 + c 2 )r 2 − (ad − bc) 2   broadcasts) from some of its other neighbors. After
Di − j =
                             a 2 + c2                       the RAD timer expires, if the number of times the
                                                            same message is received exceeds a counter
where,                                                      threshold, the message is not retransmitted and is
a = vi cosΘi – vj cosΘj; b = xi – xj; c = vi sinΘi – vj     simply dropped.
sinΘj; d = yi – yj
                                                            3.3 Area-based Methods
    Route discovery is accomplished using the
broadcast query-reply cycle with RREQ packets               3.3.1 Distance-based Scheme
propagating from the source node s to the destination            When a node receives a previously unseen
node d on several paths. The information recorded in        broadcast message, the node computes the distance
this case by a node i receiving a RREQ message              between itself and the sender. If the sender is closer
from a node j is the predicted LET of the link i-j. The     than a threshold distance, the message is dropped and
destination d will receive several RREQ messages            all future receptions of the same message are also
with the predicted LETs in the paths traversed being        dropped. Otherwise, the received message is cached
listed. The s-d path that has the maximum predicted         and the node initiates a RAD timer. Redundant
RET is then selected. If more than one path has the         broadcast messages received before the expiry of the
same maximum predicted RET, the tie is broken by            RAD timer are also cached. When the RAD timer
selecting the minimum hop path of such paths.               expires, the node computes the distance between
                                                            itself and the neighbor nodes that previously
3   REVIEW     OF                 BRAODCASTING              broadcast the particular message. If any such
    STRATEGIES                                              neighbor node is closer than a threshold distance
                                                            value, the message is dropped. Otherwise, the
   In general, the broadcasting strategies can be           message is retransmitted.
grouped into four families: Simple flooding,
Probability-based methods, Area-based methods and           3.3.2 Location-based Scheme
Neighbor knowledge based methods.                                Whenever a node originates or rebroadcasts a
                                                            message, the node puts its location information in the
3.1 Simple Flooding                                         message header. The receiver node calculates the
                                                            additional coverage area that would be obtainable if
    A source node initiates flooding by broadcasting        it were to rebroadcast. If the additional coverage is
a packet to all its neighbors. The neighbor nodes in        less than a threshold value, all future receptions of
turn rebroadcast the packet exactly once and the            the same message will be dropped. Otherwise, the
RAD timer is started. Redundant broadcast messages             The route discovery mechanism in each of DSR
received before the expiry of the RAD timer are also       and FORP is implemented with the following
cached. After the RAD timer expires, the node              broadcasting      strategies:     Simple      flooding,
considers all the cached messages and recalculates         Probabilistic      broadcasting,       Distance-based
the additional obtainable coverage area if it were to      broadcasting, MPR and MCDS-based broadcasting.
rebroadcast the particular message. If the additional      We choose the probabilistic scheme over counter-
obtainable coverage area is less than a threshold          based scheme as the range of counter values to
value, the cached messages are dropped. Otherwise          experiment with changes dynamically depending on
the message is rebroadcast.                                network density and node mobility. We choose the
                                                           distance-based scheme over the location-based
3.4 Neighbor Knowledge based Methods                       scheme because of the higher overhead in computing
                                                           the additional coverage area when a node receives
3.4.1 Multi-point Relaying                                 multiple broadcast messages from its neighbors. The
    Under this scheme, each node is assumed to have        probability of retransmission was varied from 0.1 to
a list of its 1-hop and 2-hop neighbors, obtained via      1. The threshold distance for triggering a broadcast is
periodic “Hello” beacons. The “Hello” messages             varied from 20m to 200m, in increments of 20m. We
include the identifier of the sending node, the list of    do not let any intermediate node to reply for the
the node’s known neighbors and the Multi-Point             RREQ packets and disable local route repairs as this
Relays (MPRs). After receiving “Hello” messages            may affect our goal on studying the effect of the
from all its neighbors, a node has the 2-hop topology      different broadcasting strategies on the routing
information centered at itself. Using this list of 1-hop   metrics. We do not expect much congestion in our
and 2-hop neighbors, a node selects the MPRs – the         network scenarios. Hence, the value of the RAD
1-hop neighbors that most efficiently reach all nodes      timers used for the distance-based scheme is 0.01
within its 2-hop neighborhood. Each node selects the       seconds, as suggested in [2].
set of MPRs using a greedy approach of iteratively
including the 1-hop neighbors that would cover the         4.2 Beacon Messaging
largest number of uncovered 2-hop neighbors.
                                                              Each node periodically broadcasts a “Hello”
3.4.2 Minimum Connected Dominating Set                     beacon message in its neighborhood. The “Hello”
    A Connected Dominating Set (CDS) is a set of           message contains the following information: the
nodes in the network such that all nodes in the            location of the node, its velocity and direction of
network are either in the CDS or directly attached to      moving, the 1-hop neighbor list of the node, and the
a node in the CDS. A Minimum Connected                     set of MPRs for the node. The “Hello” message is
Dominating Set (MCDS) is the smallest CDS, in              used by FORP and the MPR and MCDS based
terms of the number of nodes in the CDS, for the           broadcasting strategies. In the case of FORP, the
entire network. The size of the MCDS is the                clocks across all nodes are assumed to be
minimum number of retransmissions required in a            synchronized and each node also keeps track of the
broadcasting process so that all nodes in the network      previously advertised location of its neighbor nodes.
receive the broadcast message. Determining the             This helps to keep track of the direction in which the
MCDS for a given network graph is an NP-complete           neighbor node is moving.
problem and hence several heuristics have been
proposed to approximate the MCDS for a given               4.3 Simulation Models
network graph.
                                                               The physical, data link and MAC layer models
4   SIMULATIONS                                            are based on the multi-hop wireless network
                                                           extension [5] provided by the CMU’s Monarch
    We use ns-2 (version 2.28) [10] as the simulator       research group. The MAC layer uses the Distributed
for our study. The network dimensions are 1500m x          Coordinated Function (DCF) of the IEEE Standard
300m. The transmission range of each node is 250m.         802.11 [11] for wireless LANs. The radio model uses
These values are very commonly used in MANET               the standard channel bandwidth of 2Mbps. The
simulations. We vary the density of the network by         signal propagation model used is the two-ray ground
conducting simulations with 25 nodes (low density)         reflection model [5]. The interface queue stores both
and 50 nodes (high density). The simulation time is        the routing and data packets sent by the routing layer
1000 seconds. While we implemented the FORP                until the MAC layer is able to transmit them. We use
protocol, we used the implementation of DSR that           a FIFO-based interface queue of length 100.
comes with ns-2.                                              The node mobility model used is the Random
                                                           Waypoint model [12]. Each node starts moving from
4.1 Broadcasting Strategies                                an arbitrary location to a randomly selected
                                                           destination location at a speed uniformly distributed
in the range [vmin, …, vmax]. Once the destination is    discoveries increases as the probability of a
reached, the node may stop there for a certain time      retransmission increases. At high network density,
called the pause time and then continue to move by       one can obtain 100% success in route discoveries
choosing a different target location and a different     when the probability of a retransmission is beyond
velocity. In this paper, we set vmin = 0. The vmax       0.7. With 25 nodes in the network, the maximum
values are 5, 10 (low mobility), 20, 30 (moderate        achievable percentage of successful route discovery
mobility), 40 and 50m/s (high mobility). The pause       is only 95%. Such a limitation arises due to the poor
time is 0 seconds.                                       connectivity of the network at low density. For each
                                                         network density, we define a Threshold Probability,
4.4 Performance Metrics                                  ProbThresh, as the probability of retransmission that
                                                         results in 92-95% success in route discoveries and at
    We study the following performance metrics for       the same time the number of retransmitted messages
DSR and FORP:                                            and the number of retransmitting nodes is the
(i) Percentage of successful route discovery – ratio     minimum. For fixed probability of retransmission
(expressed as percentage) of the number of               values below ProbThresh, the percentage of success in
successful route discovery attempts to the total         route discoveries decreases with increase in node
number of route discovery attempts.                      mobility. This is due to the increase in the number of
(ii) Number of retransmitted messages – the number       route discovery attempts as the node mobility
of messages received at all the nodes in the network     increases. The value of ProbThresh was observed to be
per successful route discovery attempt, averaged         0.7 with a network of 25 nodes and 0.4 with a
over all s-d sessions for the entire simulation time.    network of 50 nodes. The percentage of successful
(iii) Number of retransmitting nodes – the number of     route discoveries for DSR under the probabilistic
nodes retransmitting the RREQ packet in the              schemes is shown in Figures 1.1 and 1.2. Similar
network per successful route discovery attempt,          results are obtained for FORP too.
averaged over all s-d sessions for the entire
simulation time.
 (iv) Number of route transitions – average of the
number of route discoveries required for all s-d
sessions.
(v) Hop count per route – average of the number of
hops in routes, time-averaged over all s-d sessions.

4.5 Percentage of Successful Route Discovery

    We refer to a “successful route discovery” as the
scenario when at least one RREQ packet broadcast                  Figure 1.1: Network of 25 Nodes
by the source reaches the destination. The flooding,
MPR and MCDS approaches guarantee successful
route discovery if the underlying network is
connected. With the probability and distance-based
broadcasting techniques, there is always a chance
that the RREQ packet does not reach its intended
destination, even though the underlying network may
be connected. The network density plays a huge role
in determining the minimum value for the probability
of retransmission and the maximum threshold
distance value for retransmission that would
maximize the number of successful route discoveries.
Larger the network density, the lower the minimum                 Figure 1.2: Network of 50 Nodes
probability of retransmission and larger the
maximum threshold distance for retransmission that            Figure 1: Percentage of Successful Route
would maximize the chances of a successful route               Discoveries with Probabilistic Scheme
discovery. In this paper, we set ourselves a target of
“92-95%” successful route discoveries for each s-d           Similarly, to obtain 92-95% success in route
session.                                                 discovery attempts, we choose DistTresh = 100m as
   For a given probability of retransmission, the        the maximum threshold distance value for
percentage of successful route discoveries increases     retransmission in a network of 25 nodes and DistTresh
as the network density increases. For a given            = 180m as the maximum threshold value in a
network density, the percentage of success in route      network of 50 nodes. The percentage of successful
route discoveries for DSR under the distance-based      increases, the number of retransmitting nodes
scheme is shown is shown in Figures 2.1 and 2.2.        increases. The destination node gets the RREQ
                                                        message through several paths and thus can choose
                                                        the best path depending on the route selection
                                                        principles of the protocol employed. The route is
                                                        learnt with the least possible route-acquisition delay,
                                                        but with the maximum message retransmission
                                                        overhead.
                                                            On the other hand, the number of retransmitting
                                                        nodes in the case of MCDS based route discovery is
                                                        the minimum since the RREQ message is
                                                        retransmitted only by nodes that are part of the
                                                        approximate MCDS. But, the MCDS approach tends
         Figure 2.1: Network of 25 Nodes                to increase the route-acquisition delay, as prior to
                                                        route discovery, the MCDS itself needs to be
                                                        determined. We run a distributed version of the
                                                        Kou’s heuristic [13] in the network to approximate
                                                        the MCDS. Each node then learns the set of its
                                                        MCDS neighbors and the presence/absence of the
                                                        node in the MCDS.




         Figure 2.2: Network of 50 Nodes

     Figure 2: Percentage of Successful Route
     Discoveries with Distance-based Scheme

    Figure 3 shows the percentage of successful route
discoveries using the selected threshold values for     Figure 4: Average Number of Retransmitting Nodes
the probability and distance-based schemes and the                     per Route Discovery
other broadcasting techniques, including flooding.




     Figure 3: Percentage of Successful Route               Figure 5: Average Number of Retransmitted
Discoveries with Different Broadcasting Techniques                Messages per Route Discovery

4.6 Reduction in Retransmission Overhead                   For the MPR, the probabilistic and distance-based
                                                        schemes, the number of retransmitting nodes and the
    Since we did not let any intermediate node to       number of retransmitted messages is in between the
reply for RREQ messages, the number of                  two extremes set by simple flooding and MCDS. The
retransmitting nodes (Figure 4) and the number of       MPR approach is not scalable as it does not take into
retransmitted messages (Figure 5), depend only on       account the path taken by the RREQ message. The
the network density, node mobility and the              set of MPR nodes is selected statically using a
broadcasting strategy used. With simple flooding        greedy approach of choosing neighbor nodes that
(Figure 4), each node retransmits the RREQ message      covered the maximum number of 2-hop neighbors.
exactly once. Hence, as the network density             When a node receives a RREQ message, the node
                                                        does not remove from its MPR set the neighbor
nodes that might also have received the RREQ
message. The number of 1-hop and 2-hop neighbors
of a node is doubled as the network density is
doubled. As a result, the number of nodes
constituting the MPR set (the number of
retransmitting nodes) also doubles, when the number
of nodes in the network is increased from 25 to 50
nodes.
    When simulated under the probabilistic and
distance-based schemes using the threshold values                 Figure 6.1: Network of 25 Nodes
mentioned in Section 4.5, we observe that the
number of retransmitting nodes (Figure 4) required
in a network of 50 nodes is only 20% more than the
number of retransmitting nodes required in a network
of 25 nodes. Similarly, we observe that in a low-
density 25-node network operated at DistTresh = 100m,
the number of retransmitting nodes required to
guarantee a 92-95% success in route discovery is
only 40% more (and does not double) than that
required in a high-density 50-node network operated
at DistTresh = 180m.
     From Figure 5, we also observe that the number               Figure 6.2: Network of 50 Nodes
of retransmitted messages with flooding and MPR
quadruples as we double the network density. This          Figure 6: Average Hop Count per Path for DSR
illustrates that flooding and MPR are not scalable
broadcasting techniques. For the MCDS scheme, the            In the case of DSR (Figures 6.1 and 6.2), the hop
number of retransmitted messages just doubles as the     count of the routes chosen using MCDS and flooding
network density doubles. With the probabilistic          is the minimum. Routing through the nodes that form
scheme operated under the appropriate threshold          the minimum connected dominating set results in the
values, the number of retransmitted messages in a        message traversing the minimum number of
50-node network is 2.4 times to that incurred in a 25-   intermediate hops from the source node to the
node network. With the distance-based scheme             destination node. Figures 6.1 and 6.2 illustrate that
operated under the appropriate threshold values, the     flooding also discovers a similar route with the
number of retransmitted messages in a 50-node            minimum number of hops from the source node to
network is only 1.3 times to that incurred in a 25-      the destination node. With MPR, probability-based
node network. These two observations illustrate that     and distance-based schemes, the hop count of DSR
the probabilistic and distance-based schemes, when       routes increases by at most 15% compared to that
operated at the appropriate threshold values for         discovered using MCDS and flooding.
retransmissions, are scalable. This is one of the            The hop count of FORP routes (Figures 7.1 and
significant contribution and finding of our research.    7.2) is normally more than that of DSR routes.
                                                         Among a set of routes learnt, FORP selects the route
4.7 Average Hop Count per Path                           that has the largest predicted route expiration time.
                                                         For such routes, at the time of their selection, the
    From Figures 6 and 7, one can observe that the       average physical distance of the constituent nodes of
average hop count per path for both DSR and FORP         a hop is only 55-65% of the transmission range of
is not very much influenced by node mobility and is      the nodes. This results in the relatively larger hop
only affected by the broadcasting strategy used.         count for FORP routes.
When simple flooding is used as the route discovery
strategy, the destination node learns about several
routes from the source of the RREQ message to itself.
From this set, the destination node can then choose
the best route according to the route selection
principles of the routing protocol. When we employ
the different broadcasting strategies, we are reducing
the number of retransmitting nodes as well as the
number of retransmitted messages. Hence, the
destination node learns only relatively fewer routes
compared to the situation when flooding is used.
                                                                  Figure 7.1: Network of 25 Nodes
         Figure 7.2: Network of 50 Nodes                         Figure 8.2: vmax = 5m/s, 50 Nodes

 Figure 7: Average Hop Count per Path for FORP

   The protocols learn the maximum and minimum
number of source-destination (s-d) routes using
flooding and MCDS respectively. Thus, the average
hop count of FORP routes is 10-15% and 2-3% more
than that of DSR routes when the routes are learnt
respectively using flooding and MCDS.
    In a probability-based scheme (Figures 8.1
through 8.4), the number of retransmitting nodes                 Figure 8.3: vmax = 50m/s, 25 Nodes
decreases as the probability for retransmission is
reduced. At high network density, the dense
coverage of nodes within a neighborhood offsets for
the lower threshold probability of retransmission. At
low network densities, one has to adopt reasonably
high values for the threshold probability of
retransmission in order to guarantee a high
percentage of success in route discoveries.
    At high node mobility, the hop count of the
routes decreases drastically as the probability for
retransmission falls below 0.4 (for low density                  Figure 8.4: vmax = 50m/s, 50 Nodes
networks) and 0.2 (for high density networks). This
could be attributed to the loss of connectivity          Figure 8: Probability of Retransmission Vs Average
between the source and the destination for low                          Hop Count per Path
values of the probability of retransmission. The
network is partitioned into two or more segments.
There exists a path from the source to the destination
only if the two end nodes of the path are within the
same segment, thus accounting for the reduction in
the hop count when the network is partitioned. As
MPR incurs more message retransmissions, if we can
tolerate a 15% sub-optimality in the hop count, the
distance-based or probabilistic schemes, at the
appropriate threshold values, may be preferred as the
route discovering strategies for DSR.                            Figure 9.1: vmax = 5m/s, 25 Nodes




         Figure 8.1: vmax = 5m/s, 25 Nodes                       Figure 9.2: vmax = 5m/s, 50 Nodes
                                                         hop route among the set of routes discovered using
                                                         these broadcasting strategies. At the threshold values
                                                         for the probability of retransmission and the
                                                         threshold distance for retransmission, as indicated in
                                                         Figures 10.1 and 10.2, DSR incurs 20% less
                                                         transitions compared to routes discovered using
                                                         flooding.


        Figure 9.3: vmax = 50m/s, 25 Nodes




                                                                  Figure 10.1: Network of 25 Nodes


        Figure 9.4: vmax = 50m/s, 50 Nodes

Figure 9: Threshold Distance of Retransmission Vs
           Average Hop Count per Path

    In a distance-based scheme (Figures 9.1 through
9.4), a node rebroadcasts the RREQ message only if
no neighbor node within the area covered by the
threshold distance of retransmission has yet                      Figure 10.2: Network of 50 Nodes
broadcasted the message. In the case of DSR, even
though we may use several threshold distance values              Figure 10: Stability of DSR Routes
for retransmission, the protocol chooses only the
route that has the minimum hop count. Hence, the
hop count of DSR routes is not much sensitive
towards the threshold distance for retransmission,
except for high values of the distance. FORP is
slightly more sensitive to the threshold distance of
retransmission. Routes with physical hop distance
55-65% of the transmission range are more likely to
be found when the threshold distance for
retransmission of the RREQ messages is also only
55-65% of the transmission range of the nodes.

4.8 Average Number of Route Transitions                           Figure 11.1: Network of 25 Nodes

    In the case of DSR (Figure 10), routes discovered
through flooding and MCDS have the minimum
number of hops. But such routes are very unstable as
observed in Figures 10.1 and 10.2. At the time of
route discovery, the average physical distance
between the constituent nodes of a hop is close to 70-
80% of the transmission range of the nodes. Such
hops are highly vulnerable to fail as the constituent
nodes of the hop are more susceptible to move away
quickly. The chance of link failure in the near future            Figure 11.2: Network of 50 Nodes
increases with increase in node mobility.
Broadcasting strategies like MPR also do not offer               Figure 11: Stability of FORP Routes
any improvement in the stability of the routes chosen.
The DSR protocol always targets for the minimum             In the case of FORP (Figures 11.1 and 11.2), the
routes are most stable when discovered using
flooding. This is because the targeted destination
node of the RREQ message receives the message
across several routes and selects the route with the
highest predicted route expiration time. When routes
are discovered using flooding, the number of route
transitions incurred by DSR is 70% and 125% more
than that incurred by FORP routes at low and high
network densities respectively.
     When route discovery is done using MCDS, the               Figure 12.3: vmax = 50m/s, 25 Nodes
RREQ messages are propagated only by the nodes in
the MCDS and hence, the routes learnt are very
likely to be of minimum hop paths. Such routes are
least stable. When routes are discovered using
MCDS, the number of route transitions incurred by
DSR is only 3-7% more than that incurred by FORP.
Thus, FORP routes selected using MCDS based
scheme are the most unstable of routes selected using
the broadcasting strategies.
    DSR routes are less stable in networks of high              Figure 12.4: vmax = 50m/s, 50 Nodes
density compared to networks of low density. This is
due to the “edge effect” problem [14]. In high
                                                        Figure 12: Threshold Distance of Retransmission Vs
density networks, the average physical distance of a
                                                               Average Number of Route Transitions
hop in a minimum-hop path during its discovery is
close to 80% of the transmission range of the node.
                                                            Compared to the distance-based scheme, FORP
While in low-density networks, the average physical
                                                        routes discovered using MPR and probability-based
distance of a hop is only 70% of the transmission
                                                        scheme are relatively more stable. The number of
range of the nodes. In high-density networks, when
                                                        transitions incurred by these routes is only 20-35%
we aim for minimum-hop, we can select the farthest
                                                        more than that incurred by routes discovered using
neighbor that is on the path towards the destination.
                                                        flooding. For low density networks and in networks
But, this results in routes that are highly unstable.
                                                        with high node mobility, the network connectivity is
    When operated at the threshold distance for
                                                        very limited when operated with low values for the
retransmission as shown in Figures 11.1 and 11.2,
                                                        probability of retransmission (Figures 13.1 through
the number of route transitions incurred for both the
                                                        13.4). Under such conditions, the number of
protocols when using threshold distance of 180m is
                                                        successful route discoveries and the number of route
at most 1.5 times to that incurred when using
                                                        transitions are low.
threshold distance of 100m. More detailed results are
shown in Figures 12.1 to 12.4.




                                                                Figure 13.1: vmax = 5m/s, 25 Nodes
        Figure 12.1: vmax = 5m/s, 25 Nodes




                                                                Figure 13.2: vmax = 5m/s, 50 Nodes
        Figure 12.2: vmax = 5m/s, 50 Nodes
                                                        itself will be a significant overhead.
                                                            When we employ the different broadcasting
                                                        strategies, we are reducing the number of
                                                        retransmitting nodes as well as the number of
                                                        retransmitted messages. The routing protocols learn
                                                        only relatively fewer routes compared to the situation
                                                        when flooding is used. With flooding, each node in
                                                        the network retransmits the RREQ packet exactly
                                                        once, thus resulting in the maximum number of
        Figure 13.3: vmax = 50m/s, 25 Nodes             retransmissions. Letting the RREQs propagate
                                                        through the nodes that form the minimum connected
                                                        dominating set results in the packet traversing the
                                                        minimum number of intermediate hops with
                                                        minimum number of retransmissions from the source
                                                        to the destination. So, we learn the maximum and
                                                        minimum number of routes using flooding and
                                                        MCDS respectively. The number of routes learnt
                                                        using the other broadcasting strategies is in between
                                                        these two extremes.
                                                            In the case of DSR, the hop count of routes
        Figure 13.4: vmax = 50m/s, 50 Nodes             chosen using the MCDS and flooding based route
                                                        discovery approaches is the minimum. Nevertheless,
    Figure 13: Probability of Retransmission Vs         since DSR opts always for the minimum hop routes,
       Average Number of Route Transitions              the hop count of DSR routes discovered using MPR,
                                                        probability-based and distance-based schemes is at
5   CONCLUSIONS                                         most 15% more than that discovered using flooding
                                                        and MCDS. This illustrates that routes having
    The high-level contribution of this paper is a      minimum hop or close to being minimum hop are
simulation-based analysis on the impact of the          very much discovered using the different
broadcast route discovery techniques on the stability   broadcasting strategies. If we can tolerate a 15% sub-
and hop count of routes discovered for the minimum-     optimality in the hop count, the distance-based or
hop based DSR and the stability-based FORP              probabilistic scheme at the appropriate threshold
protocols. We also showed that the probability-based    values (which yield the minimum number of
and distance-based schemes, when operated at the        retransmissions) may be preferred as the route
appropriate threshold values for retransmission, are    discovery strategies for DSR.
more scalable compared to the flooding and MPR              FORP targets stable routes and the hop count of
schemes. Future work will also involve studying the     such routes are usually more than that of minimum
impact of the broadcasting strategies on the link       hop routes. At the time of route selection, the
efficiency and stability of trees and meshes            average physical distance of the constituent nodes of
determined for the multicast routing protocols.         a hop in stable routes is only 55-65% of the
    For networks of low density and high density, we    transmission range of the nodes. Thus, FORP is more
identify the threshold values for the probability of    sensitive to the different broadcasting strategies. The
retransmission and the distance for retransmission,     average hop count of FORP routes is 10-15% more
using which we can obtain 92-95% success in route       than that of DSR routes when routes are learnt using
discoveries with the minimum number of                  flooding, MPR, distance-based and probabilistic
retransmissions, and below these threshold values,      approaches. While using MCDS, the hop count of
the percentage of success in route discoveries          FORP routes is only 2-3% more than that of DSR
decreases with increase in node mobility. When          routes.
operated at the threshold probability values for            The stability of DSR routes does not change much
retransmission, the number of retransmitting nodes in   with the broadcasting strategy used. This is because
a network of 50 nodes is only 20% more than the         the protocol always targets for minimum-hop routes
number of retransmitting nodes in a network of 25       and manages to discover routes with minimum hop
nodes. Also, when operated at the appropriate           count or routes close to minimum hop count
threshold distances for retransmission, the number of   irrespective of the broadcasting strategy used. With
retransmitting nodes decreases as the network           respect to FORP, the most stable routes are
density increases. The probabilistic and distance-      discovered using flooding. FORP routes discovered
based schemes require less overhead to implement        using the MCDS approach are the least stable as they
compared to the MPR and MCDS based schemes.             are more or less similar to DSR routes. FORP routes
Determining the MCDS in a highly mobile network         discovered using MPR and probability-based
schemes (operated at the threshold probability for       40-04, University of Texas at Dallas (2004).
retransmission) incur only 20-35% more transitions
compared to those routes discovered using flooding.      [8] N. Meghanathan: A Simulation Study on the
With regards to distance-based schemes, FORP             Stability-Oriented Routing Protocols for Mobile Ad
routes are more stable when discovered using             Hoc Networks, Proceedings of 3rd IEEE
moderate values for the distance of retransmission.      International Conference on Wireless and Optical
This is because, at the time of route discovery itself   Communications Networks (2006).
the physical distance between the constituent nodes
of a hop is at least the threshold distance of           [9] Kaplan ED (ed.), Understanding the GPS:
retransmission. In general, route discoveries with       Principles and Applications, Artech House: Boston,
less retransmission overhead yield less stable routes    MA (1996).
and vice-versa. We thus observe a tradeoff between
the number of retransmissions per stable route           [10] K. Fall and K. Varadhan: The ns Manual, The
discovery and the number of stable route discoveries     VINT Project, A Collaboration between researchers
needed for a source-destination session.                 at UC Berkeley, LBL, USC/ISI and Xerox PARC.

                                                         [11] IEEE Standards Department, Wireless LAN
6   REFERENCES                                           Medium Access Control (MAC) and Physical Layer
                                                         (PHY) Specifications, IEEE Standard 802.11-1997
[1] S. Ni, Y. Tseng, Y. Chen and J. Sheu: The            (1997).
Broadcast Storm Problem in a Mobile Ad Hoc
Network, Proceedings of the 5th ACM International        [12] C. Bettstetter, H. Hartenstein and X. Perez-
Conference on Mobile Computing and Networking,           Costa: Stochastic Properties of the Random-Way
pp.151-162 (1999).                                       Point Mobility Model, Wireless Networks, Vol. 10,
                                                         No. 5, pp. 555 – 567 (2004).
[2] B. Williams and T. Camp: Comparison of
Broadcasting Techniques for Mobile Ad Hoc                [13] L. Kou, G. Markowsky and L. Berman: A Fast
Networks, Proceedings of the 3rd ACM International       Algorithm for Steiner Trees, Acta Informatica, Vol.
Symposium on Mobile Ad Hoc Networking and                15, pp. 141 – 145 (1981).
Computing, pp. 194 – 205 (2002).
                                                         [14] G. Lim, K. Shin, S. Lee, H. Yoon and J. S. Ma:
[3] D. B. Johnson, D. A. Maltz and J. Broch: DSR:        Link Stability and Route Lifetime in Ad hoc
The Dynamic Source Routing Protocol for Multi-hop        Wireless Networks, Proceedings of International
Wireless Ad hoc Networks, Ad hoc Networking,             Conference on Parallel Processing Workshops, pp.
edited by Charles E. Perkins, Chapter 5, Addison         116 – 123 (2002).
Wesley, pp. 139 – 172 (2001).

[4] W. Su, S-J Lee and M. Gerla: Mobility Prediction
and Routing in Ad Hoc Wireless Networks,
International Journal of Network Management, Vol.
11, No. 1, pp. 3-30 (2001).

[5] J. Broch, D. A. Maltz, D. B. Johnson, Y. C. Hu
and J. Jetcheva: A Performance Comparison of
Multi-hop Wireless Ad Hoc Network Routing
Protocols, Proceedings of the 4th ACM Annual
International Conference on Mobile Computing and
Networking, pp.85 – 97 (1998).

[6] P. Johansson, T. Larson, N. Hedmanm B.
Mielczarek and M. DegerMark: Scenario-based
Performance Analysis of Routing Protocols for
Mobile Ad Hoc Networks, Proceedings of the 5th
ACM International Conference on Mobile
Computing and Networking, pp. 195 – 206 (1999).

[7] N. Meghanathan and A. Farago: Survey and
Taxonomy of 55 Unicast Routing Protocols for
Mobile Ad Hoc Networks, Technical Report UTDCS-

				
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About UBICC, the Ubiquitous Computing and Communication Journal [ISSN 1992-8424], is an international scientific and educational organization dedicated to advancing the arts, sciences, and applications of information technology. With a world-wide membership, UBICC is a leading resource for computing professionals and students working in the various fields of Information Technology, and for interpreting the impact of information technology on society.