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MPPM-Error packet. The receiver node on receiving the MPPM-Error packet discards all the
LUVs and does not generate any new MPPM. After the MPPM-timer expires, the multicast
source initiates a new global broadcast-based tree discovery procedure.
5. Simulation performance study of NR-MLPBR and R-MLPBR
The network dimension used is a 1000m x 1000m square network. The transmission range of
each node is assumed to be 250m. The number of nodes used in the network is 25 and 75
nodes representing networks of low and high density with an average distribution of 5 and
15 neighbors per node respectively. Initially, nodes are uniformly randomly distributed in
the network. We compare the performance of NR-MLPBR and R-MLPBR with that of the
minimum-hop based Multicast Extension of Ad hoc On-demand Distance Vector (MAODV)
routing protocol (Royer & Perkins, 1999) and the minimum-link based Bandwidth Efficient
Multicast Routing Protocol (BEMRP) (Ozaki, et. al., 2001). We implemented all of these four
multicast routing protocols in ns-2. The broadcast tree discovery strategy employed is the
default flooding approach. The node mobility model used is the Random Waypoint model
with each node starts moving from an arbitrary location to a randomly selected destination
location at a speed uniformly distributed in the range [0,…,v
max
]. The v
max
values used are 10
m/s, 30 m/s and 50 m/s representing scenarios of low, moderate and high node mobility
respectively. Pause time is 0 seconds. Simulations are conducted with a multicast group size
of 2, 4 (small size), 8, 12 (moderate size) and 24 (larger size) receiver nodes. For each group
size, we generated 5 lists of receiver nodes and simulations were conducted with each of
them. Traffic sources are constant bit rate (CBR). Data packets are 512 bytes in size and the
packet sending rate is 4 data packets/second. The multicast session continues until the end
of the simulation time, which is 1000 seconds.

The performance metrics studied through this simulation are the following:
• Number of Links per Tree: This is the time averaged number of links in the multicast
trees discovered and computed over the entire multicast session.
• Hop Count per Source-Receiver Path: This is the time averaged hop count of the paths
from the source to each receiver of the multicast group and computed over the entire
multicast session.
• Time between Successive Broadcast Tree Discoveries: This is the time between two
successive broadcast tree discoveries, averaged over the entire multicast session. The
larger the time between successive broadcast tree discoveries, the lower is the number
of broadcast tree discoveries. This metric is a measure of the lifetime of the multicast
trees discovered and also the effectiveness of the path prediction approach followed in
NR-MLPBR and R-MLPBR.
The performance results for each metric displayed in Figures 20 through 22 are an average
of the results obtained from simulations conducted with 5 sets of multicast groups and 5 sets
of mobility profiles for each group size, node velocity and network density values. The
multicast source in each case was selected randomly among the nodes in the network and
the source is not part of the multicast group. The nodes that are part of the multicast group
are merely the receivers.
5.1 Number of links per multicast tree
R-MLPBR manages to significantly reduce the number of links (Figure 20) vis-à-vis the
MAODV and NR-MLPBR protocols without yielding to a higher hop count per source-
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receiver path. R-MLPBR is the first multicast routing protocol that yields trees with the
reduced number of links and at the same time, with a reduced hop count (close to the
minimum) per source-receiver path. However, R-MLPBR cannot discover trees that have
minimum number of links as well as the minimum hop count per source-receiver path.
BEMRP discovers trees that have a reduced number of links for all the operating scenarios.

However, this leads to larger hop count per source-receiver paths for BEMRP (Figure 21).


25 Nodes, v
max
= 10 m/s 25 Nodes, v
max
= 30 m/s 25 Nodes, v
max
= 50 m/s


75 Nodes, v
max
= 10 m/s 75 Nodes, v
max
= 30 m/s 75 Nodes, v
max
= 50 m/s
Fig. 20. Average Number of Links per Multicast Tree



25 Nodes, v
max
= 10 m/s 25 Nodes, v
max
= 30 m/s 25 Nodes, v
max
= 50 m/s

75 Nodes, v
max
= 10 m/s 75 Nodes, v
max
= 30 m/s 75 Nodes, v
max
= 50 m/s
Fig. 21. Average Hop Count per Source-Receiver Path for a Multicast Session
5.2 Hop count per source-receiver path
All the three multicast routing protocols – MAODV, NR-MLPBR and R-MLPBR, incur
almost the same average hop count per source-receiver path (refer Figure 21) and it is
considerably lower than that incurred for BEMRP. The hop count per source-receiver path is
an important metric and it is often indicative of the end-to-end delay per multicast packet
Mobile Ad-Hoc Networks: Protocol Design

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from the source to a specific receiver. BEMRP incurs a significantly larger hop count per
source-receiver path and this can be attributed to the nature of this multicast routing
protocol to look for trees with a reduced number of links. When multiple receiver nodes
have to be connected to the source through a reduced set of links, the hop count per source-
receiver path is bound to increase. The hop count per source-receiver path increases
significantly as we increase the multicast group size.
5.3 Time between successive broadcast tree discoveries
The time between successive broadcast tree discoveries (Figure 22) is a measure of the
stability of the multicast trees and the effectiveness of the location prediction and path
prediction approach of the two multicast extensions. For a given node density and node
mobility, both NR-MLPBR and R-MLPBR incur relatively larger time between successive
broadcast tree discoveries for smaller and medium sized multicast groups. MAODV tends

to be more unstable as the multicast group size is increased, owing to the minimum hop
nature of the paths discovered and absence of any path prediction approach. For larger
multicast groups, the multicast trees discovered using BEMRP are relatively more stable by
virtue of the protocol’s tendency to strictly minimize only the number of links in the tree.



25 Nodes, v
max
= 10 m/s 25 Nodes, v
max
= 30 m/s 25 Nodes, v
max
= 50 m/s



75 Nodes, v
max
= 10 m/s 75 Nodes, v
max
= 30 m/s 75 Nodes, v
max
= 50 m/s

Fig. 22. Average Time between Successive Broadcast Tree Discoveries
6. Node-disjoint multi-path extension of LPBR (LPBR-M)
We define a multi-path between a source-destination (s-d) pair as the set of multiple paths
between the source s and destination d. We now propose a multi-path extension for LPBR to
discover node-disjoint multi-paths such that both the number of global broadcast multi-path

discoveries as well as the hop count per s-d multi-path (average of the hop count of all the
multiple node-disjoint paths of a multi-path) is simultaneously minimized. We assume that
the clocks across all nodes are at least loosely synchronized. This is essential to ensure
proper timeouts at the nodes for failure to receive a certain control message.
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6.1 Broadcast of route request messages
Whenever a source node has data packets to send to a destination and is not aware of any
path to the latter, the source initiates a broadcast route discovery procedure by broadcasting
a Multi-path Route Request (MP-RREQ) message to its neighbors. Each node, except the
destination, on receiving the first MP-RREQ of the current broadcast process (i.e., a MP-
RREQ with a sequence number greater than those seen before), includes its Location Update
Vector, LUV, in the MP-RREQ message. The LUV of a node (same as that in Figure 1)
comprises the following: Node ID, X, Y co-ordinate information, Current velocity and Angle
of movement with respect to the X-axis. The Node ID is also appended in the “Route
Record” field of the MP-RREQ message (refer Figure 23).


Fig. 23. Multi-path Route Request (MP-RREQ) Message
6.2 Generation of the route reply messages
When the destination receives a MP-RREQ message, it extracts the path traversed by the
message (sequence of Node IDs in the Route Record) and the LUVs of the nodes (including
the source) that forwarded the message. The destination stores the paths learnt in a set,
RREQ-Path-Set, maintained in the increasing order of their hop count. Ties between paths
with the same hop count are broken in the order of the time of arrival of their corresponding
MP-RREQ messages at the destination. The LUVs are stored in a LUV-Database maintained
for the latest broadcast route discovery procedure initiated by the source. The destination
runs a local path selection heuristic to extract the set of node-disjoint paths, RREQ-ND-Set,

from the RREQ-Path-Set. The heuristic makes sure that except the source and the destination
nodes, a node can serve as an intermediate node in at most only one path in the RREQ-ND-
Set. The RREQ-ND-Set is initialized and updated with the paths extracted from the RREQ-
Path-Set satisfying this criterion. In other words, a path P in the RREQ-Path-Set is added to
the RREQ-ND-Set only if none of the intermediate nodes in P are already part of any of the
paths in the RREQ-ND-Set. Once the RREQ-ND-Set is built, the destination sends a Multi-
path Route Reply (MP-RREP) message for every path in the RREQ-ND-Set. An intermediate
node receiving the MP-RREP message (refer Figure 24) updates its routing table by adding
the neighbor that sent the message as the next hop on the path from the source to the
destination. The MP-RREP message is then forwarded to the next node towards the source
as indicated in the Route Record field of the message.


Fig. 24. Multi-path Route Reply (MP-RREP) Message
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6.3 Multi-path acquisition time and data transmission
After receiving the MP-RREP messages from the destination within a certain time called the
Multi-path Acquisition Time (MP-AT), the source stores the paths learnt in a set of node-
disjoint paths, NDP-Set. The MP-AT is based on the maximum possible diameter of the
network (an input parameter in our simulations). The diameter of the network is the
maximum of the hop count of the minimum hop paths between any two nodes in the
network. The MP-AT is dynamically set at a node depending on the time it took to receive
the first MP-RREP for a broadcast discovery process.


Fig. 25. Structure of the Data Packet
For data transmission, the source uses the path with the minimum hop count among the
paths in the NDP-Set. In addition to the regular fields of source and destination IDs and the

sequence number, the header of the data packet (refer Figure 25) includes four specialized
fields: the ‘Number of Disjoint Paths’ field that indicates the number of active node-disjoint
paths currently being stored in the NDP-Set of the source, the ‘More Packets’ (MP) field, the
‘Current Dispatch Time’ (CDT) field and the ‘Time Left for Next Dispatch’ (TNLD) field. The
CDT field stores the time as the number of milliseconds lapsed since Jan 1, 1970, 12 AM.
These additional overhead (relative to the other routing protocols) associated with the
header is only 13 more bytes per data packet.
The source sets the CDT field in all the data packets sent. In addition, if the source has any
more data to send, it sets the MP flag to 1 and sets the appropriate value for the TLND field,
which indicates the number of milliseconds since the CDT. If the source does not have any
more data to send, it will set the MP flag to 0 and leaves the TLND field blank. As we
assume the clocks across all nodes are at least loosely synchronized, the destination uses the
CDT field in the header of the data packet and the time of arrival of the packet to update the
average end-to-end delay per data packet for the set of multi-paths every time after
receiving a new data packet on one of these paths. If the MP flag is set, the destination
computes the ‘Next Expected Packet Arrival Time’ (NEPAT), which is CDT field + TLND
field + 2*NDP-Set Size*Average end-to-end delay per packet. A timer is started for the
NEPAT value. To let the destination to wait until the source manages to successfully route a
packet along a path in the NDP-Set, the NEPAT time takes the NDP-Set Size into account.
6.4 Multi-path maintenance
If an intermediate node could not forward the data packet due to a broken link, the
upstream node of the broken link informs about the broken route to the source node
through a Multi-path-Route-Error (MP-RERR) message, structure shown in Figure 26. The
source node on learning the route failure will remove the failed path from its NDP-Set and
attempt to send data packet on the next minimum-hop path in the NDP-Set. If this path is
actually available in the network at that time instant, the data packet will successfully
propagate its way to the destination. Otherwise, the source receives a MP-RERR message on
the broken path, removes the failed path from the NDP-Set and attempts to route the data
packet on the next minimum hop path in the NDP-Set. This procedure is repeated until the
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source does not receive a MP-RERR message or runs out of an available path in the NDP-Set.
In the former case, the data packet successfully reaches the destination and the source
continues to transmit data packets as scheduled. In the latter case, the source is not able to
successfully transmit the data packet to the destination.


Fig. 26. Multi-path Route Error (MP-RERR) Message
Before initiating another broadcast route discovery procedure, the source will wait for the
destination node to inform it of a new set of node-disjoint routes through a sequence of MP-
LPBR-RREP messages. The source will run a MP-LPBR-RREP-timer and wait to receive at
least one MP-LPBR-RREP message from the destination. For the failure of the first set of
node-disjoint paths, the value of this timer would be set to the multi-path acquisition time
(the time it took to get the first MP-RREP message from the destination since the inception
of route discovery), so that we give sufficient time for the destination to learn about the
route failure and generate a new sequence of MP-LPBR-RREP messages. For subsequent
route-repairs, the MP-LPBR-RREP-timer will be set based on the time it takes to get the first
MP-LPBR-RREP message from the destination.
6.5 LPBR-M: Multi-path prediction
If a destination node does not receive the data packet within the NEPAT time, it will attempt
to locally construct the global topology using the location and mobility information of the
nodes learnt from the latest broadcast tree discovery. The procedure to predict the location
of a node (say node u) at a time instant CTIME based on the LUV gathered from node u at
time STIME is the same as that explained in Section 2.3. The destination locally runs the
algorithm for determining the set of node-disjoint paths (Meghanathan, 2007) on the
predicted global topology. The algorithm is explained as follows: Let G (V, E) be the graph
representing the predicted global topology, where V is the set of vertices and E is the set of
edges in the predicted network graph. Let P

N
denote the set of node-disjoint s-d paths
between source s and destination d. To start with, we run the O(|V|
2
) Dijkstra algorithm
(Cormen, 2001) on G to determine the minimum hop s-d path. If there is at least one s-d path
in G, we include the minimum hop s-d path p in the set P
N
. We then remove all the
intermediate nodes (nodes other than source s and destination d) that were part of the
minimum-hop s-d path p in the original graph G to obtain the modified graph G’ (V’, E’). We
then determine the minimum-hop s-d path in G’ (V’, E’), add it to the set P
N
and remove the
intermediate nodes that were part of this s-d path to get a new updated G’ (V’, E’). We repeat
this procedure until there exists no more s-d paths in the network. The set P
N
contains the
node-disjoint s-d paths in the original network graph G. Note that when we remove a node
from a network graph, we also remove all the links associated with the node.
6.6 MP-LPBR-RREP message propagation and handling prediction failure
The destination d sends a MP-LPBR-RREP message (refer Figure 27) to the source s on each
of the predicted node-disjoint paths. Each intermediate node receiving the MP-LPBR-RREP
message updates its routing table to record the incoming interface of the message as the
outgoing interface for any new data packets received from s to d. The MP-LPBR-RREP
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message has a “Number of Disjoint Paths’ field to indicate the total number of paths
predicted and a ‘Is Last Path’ Boolean field that indicates whether or not the reported path is

the last among the set of node-disjoint paths predicted. If the source s receives at least one
MP-LPBR-RREP message before the MP-LPBR-RREP-timer expires, it indicates that the
corresponding predicted s-d path on which the message propagated through does exists in
reality. The source creates a new instance of the NDP-Set to store all the newly learnt node-
disjoint s-d routes and sends data on the minimum hop path among them.


Fig. 27. Structure of the MP-LPBR-RREP Message
The source node estimates the Route-Repair Time (RRT) as the time that lapsed between the
reception of the last MP-RERR message from an intermediate node and the first MP-LPBR-
RREP message from the destination. An average value of the RRT is maintained at the
source as it undergoes several route failures and repairs before the next broadcast route
discovery. The MP-LPBR-RREP-timer (initially set to the multi-path acquisition time) will be
then set to 1.25*Average RRT value, so that we give sufficient time for the destination to
learn about the route failure and generate a sequence of MP-LPBR-RREP messages.
If an intermediate node attempting to forward a MP-LPBR-RREP message of the destination
could not successfully forward the message to the next node on the path towards the source,
the intermediate node informs the absence of the route through a MP-LPBR-RREP-RERR
message sent back to the destination. If the destination receives MP-LPBR-RREP-RERR
messages for all the MP-LPBR-RREP messages initiated or the NEPAT time has expired,
then the node discards all the LUVs and does not generate any new MP-LPBR-RREP
message. The destination waits for the source to initiate a broadcast route discovery. After
the MP-LPBR-RREP-timer expires, the source initiates a new broadcast route discovery.
7. Simulation performance study of LPBR-M
We study the performance of LPBR-M through extensive simulations and also compare its
performance with that of the link-disjoint path based AOMDV (Marina & Das, 2001) and the
node-disjoint path based AODVM (Ye et. al., 2003) routing protocols. We implemented all
these three multi-path routing protocols in ns-2. We use a 1000m x 1000m square network.
The transmission range per node is 250m. The number of nodes used in the network is 25, 50
and 75 nodes representing networks of low, medium and high density with an average

distribution of 5, 10 and 15 neighbors per node respectively. For each combination of
network density and node mobility, simulations are conducted with 15 source-destination
(s-d) pairs. Traffic sources are constant bit rate (CBR). Data packets are 512 bytes in size and
the packet sending rate is 4 data packets/second. Simulation time is 1000 seconds. The node
mobility model used is the Random Waypoint model (Bettstetter, 2004). During every
direction change, the velocity of a node is uniformly and randomly chosen from the range
[0,…,v
max
] and the values of v
max
used are 10, 30 and 50 m/s, representing node mobility
levels of low, moderate and high respectively. The Medium-Access Control (MAC) layer
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model used is the IEEE 802.11 model (Bianchi, 2000) involving Request-to-Send (RTS) and
Clear-to-Send (CTS) message exchange for coordinating channel access.
The performance metrics studied are the following:
• Time between Successive Broadcast Multi-path Route Discoveries: This is the time
between two successive broadcast multi-path route discoveries, averaged for all the s-d
sessions over the simulation time. We use a set of multi-paths as long as at least one path
in the set exists, in increasing order of their hop count. We opt for a broadcast route
discovery when all paths in a multi-path set fails. Hence, this metric is a measure of the
lifetime of the multi-path set and a larger value is preferred for a routing protocol.
• Control Message Overhead: This is the ratio of the total number of control messages
(MP-RREQ, MP-RREP, MP-LPBR-RREP and MP-LPBR-RREP-RERR) received at every
node to that of the total number of data packets delivered at a destination, averaged
over all the s-d sessions for the entire simulation time. In a typical broadcast operation,
the total amount of energy spent to receive a control message at all the nodes in a

neighborhood is greater than the amount of energy spent to transmit the message.
• Average Hop Count of all Disjoint-paths used: This is the time-averaged hop count of
the disjoint paths determined and used by each of the multi-path routing protocols.
Each data point for the performance metrics in Figures 28 and 29 is an average of the results
obtained from simulations conducted with 5 sets of mobility profiles of the nodes and 15
randomly picked s-d pairs, for each combination of node mobility and density.


v
max
= 10 m/s v
max
= 30 m/s v
max
= 50 m/s
Fig. 28. Time between Successive Broadcast Multi-path Route Discoveries
7.1 Time between successive multi-path route discoveries
LPBR-M yields the longest time between successive broadcast multi-path route discoveries
(refer Figure 28). Thus, the set of node-disjoint paths discovered and predicted by LPBR-M
are relatively more stable than the set of link-disjoint and node-disjoint paths discovered by
the AOMDV and AODVM routing protocols respectively. As we increase node mobility, the
difference in the time between successive multi-path route discoveries incurred for AOMDV
and AODVM vis-à-vis LPBR-M increases. Also, for a given level of node mobility, as we
increase the network density, the time between successive route discoveries for LPBR-M
increases relatively faster compared to those incurred for AOMDV and AODV-M.
7.2 Control message overhead
For a given level of node mobility and network density, LPBR-M incurs the lowest control
message overhead (refer Figure 29). For a given level of node mobility, AOMDV and
AODVM respectively incur 4%-16% and 14%-34% more control message overhead than
LPBR-M when flooding is used. In networks of moderate node mobility, the control

message overhead incurred by the three multi-path routing protocols while using flooding
is 2.1 (high density) to 3.4 (low density) times more than that incurred in networks of low
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node mobility. In networks of high node mobility, the control message incurred by the three
multi-path routing protocols while using flooding is 3.0 (high density) to 3.7 (low density)
times more than that incurred in networks of low node mobility.


v
max
= 10 m/s v
max
= 30 m/s v
max
= 50 m/s
Fig. 29. Control Message Overhead for LPBR-M, AOMDV and AODVM
7.3 Average hop count per multi-path
For a given routing protocol and network density, the average hop count of the disjoint-
paths used is almost the same, irrespective of the level of node mobility. As we add more
nodes in the network, the hop count of the paths tends to decrease as the source manages to
reach the destination through relatively lesser number of intermediate nodes. With increase
in network density, there are several candidates to act as intermediate nodes on a path. The
average hop count of the paths in high and moderate density networks is 6%-10% less than
the average hop count of the paths in networks of low density. The average hop count for all
the three multi-path routing protocols is almost the same.
8. Conclusions
This chapter discusses the design of a location prediction based routing protocol (LPBR) and
its extensions for multicast and multi-path routing in mobile ad hoc networks (MANETs).

The aim of each category of the LPBR protocols is to simultaneously minimize the number
of times the underlying communication structures (single path, tree or multi-paths) are
discovered through a global broadcast discovery as well as the hop count of the paths
and/or the number of links that are part of these communication structures. Simulation
performance results indicate that the number of broadcast route discoveries incurred with
LPBR is significantly lower than that incurred with the best stable path routing protocol
(FORP) known in the literature and at the same time, the hop count per path is only at most
12% more than that of the most commonly used minimum-hop based routing protocol
(DSR). The time between successive LPBR route discoveries can be as large as 50-100% and
120-220% more than that incurred with FORP and DSR respectively. The receiver-aware
multicast extension of LPBR (R-MLPBR) manages to significantly reduce the number of
multicast tree discoveries with very minimal increase (as large as only 20%) in the hop count
per source-receiver path and the number of links per multicast tree. The non receiver-aware
multicast extension of LPBR (NR-MLPBR) determines multicast trees that have hop count
very close to that of the minimum-hop based MAODV protocol, albeit with a reduced
number of broadcast tree discoveries. The node-disjoint multi-path extension of LPBR
(LPBR-M) reduces the number of multi-path broadcast route discoveries to as large as 44%
compared to AOMDV and AODVM and at the same time, incurs a hop count that is very
much the same as these two multi-path routing protocols.
All of these performance results indicate the effectiveness of the location prediction approach
in LPBR. The rationale behind the success in re-discovering routes and trees (using location
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prediction) without often going through a broadcast discovery process is that two nodes that
form a link in the actual network may not exactly be positioned at the location predicted; but
the predicted locations are close enough to include the a link in the global topology locally
predicted at the destination node. Another notable characteristic of LPBR and its extensions is
that the location information of the nodes is not periodically disseminated offline through a

location service mechanism; instead, the location information is disseminated along with the
route discovery control messages. As there exist no single unicast single path or multi-path/
multicast routing protocol that can simultaneously minimize the number of route discoveries
as well as the hop count per path and/or the number of links per tree, LPBR and its multicast
and multi-path extensions are a valuable addition to the MANET literature.
9. Acknowledgments

The research on the multicast and multi-path extensions of the Location Prediction Based
Routing Protocol was sponsored by the Army Research Laboratory and was accomplished
under Cooperative Agreement Number W911NF-08-2-0061. The views and conclusions in
this document are those of the authors and should not be interpreted as representing the
official policies, either expressed or implied, of the Army Research Laboratory or the U.S.
Government. The U.S. Government is authorized to reproduce and distribute reprints for
Government purposes notwithstanding any copyright notation herein.
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00104620.
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9781424444731, September 2009, Omaha, NE, USA.
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13
An Adaptive Broadcasting Scheme in

Mobile Ad Hoc Networks
Dimitrios Liarokapis, and Ali Shahrabi
Glasgow Caledonian University
United Kingdom
1. Introduction
Mobile and static nodes in battlefields or within the vicinity of disaster areas may not
depend on fixed infrastructure for communication. To rapidly provide the required
communication between the nodes in such environments, a Mobile Ad hoc Network
(MANET) is the only available platform. With no fixed infrastructure, the efficient use of
MANETs resources is highly crucial for the successful communication between mobile
nodes. In situations where both the transmitting and the receiving nodes are placed within
the transmission range of each other, communication is possible through a single-hop
connection. In all other scenarios where the nodes are distanced, the exchange of packets is
possible as long as a multi-hop path is available between them. Despite the unique
characteristics of MANETs, they share many attributes and operations with other traditional
networks. DNS lookups, exchange of control packets for management purposes and routing
discovery requests are some examples of common operations, which all require
broadcasting pieces of information across the network. However, due to lack of a centralised
administrative and hardware, some modification is required to adopt broadcast operation
for MANET environment.
The most straightforward broadcast mechanism used in MANETs is Simple Flooding (SF).
The algorithmic procedure followed in SF is very simple, thus making its implementation
and integration inside more complex operations fairly undiscomforting. In SF, upon
reception of a broadcast packet the receiver will check whether or not this is a duplicate
packet. If it is a new packet it will immediately retransmit it to all of its neighbouring nodes.
Simply flooding the entire network may be the fastest and easiest way for a node to
broadcast information over the network but it has been found to be a very unreliable and
resource inefficient mechanism leading to the Broadcast Storm Problem (Ni et al., 1999)
especially in highly populated and dense networks.
Over the past few years many studies (Leng et al., 2004), (Zhu et al., 2004), (Qayyum et al.,

2002), (Hsu et al., 2005), (Purtoosi et al., 2006), (Barrit et al., 2006), (Bauer et al., 2005) have
proposed novel broadcast mechanisms to alleviate the effects of SF. Early works were
focused on developing schemes where the rebroadcast decision is made based on fixed and
pre-determined threshold values. Probability-Based (PB), Counter-Based (CB) and Distance-
Based (DB) are three schemes which have been proposed based on the concept of
introducing a threshold value. PB bases it rebroadcasting decision on a fixed probability
value, CB decides it by counting the number of received duplicate packets and finally the
Mobile Ad-Hoc Networks: Protocol Design

244
rebroadcasting in DB is based on the distance between sender and receiver (Ni et al., 1999).
All of these schemes were found to considerably improve the performance of the broadcast
operation in various network topologies but they also introduced a new dependency. The
threshold value to be selected in order to reach optimum overall network performance
highly depends on traffic load volume and node population. The degree of dependency is
such that in certain network topologies SF performs better than these schemes (Williams et
al., 2002).
The development of threshold-based adaptive broadcast schemes has consequently been
considered to alleviate these dependencies. According to their algorithmic procedures, these
schemes adaptively adjust the threshold value to be used depending on local information
with regards to the density of the network within the transmission range of the sender
(number of one-hop neighbours) or within a broader network area (number of two- hop
neighbours) or even within the entire topology. Hence, all the schemes can be categorized
based on the mechanism used in order to implement adaptivity. The most commonly used
mechanism implies all nodes to periodically exchange HELLO packets with their
neighbouring nodes in order to calculate density (Ryu et al., 2004), (Lee et al., 2006), (Chen et
al., 2002), (Colagrosso 2007), (Chen et al., 2003), (Kyasanur et al., 2006), (Tseng et al., 2003).
Alternatively, the other group of adaptive broadcast schemes utilise a positioning system,
e.g. GPS, resulting in the construction of a network map for every mobile node, calculating
in that way a very precise value for the density of the network (Deng et al., 2006). These

schemes either introduce more overhead traffic to the network or demand the existence of
expensive and fairly unreliable positioning systems.
In this chapter, a novel Distance-Based Adaptive (DibA) scheme is proposed. Based on the
Distance-Based broadcast scheme, DibA implements adaptivity by dynamically adjusting
the distance threshold value for every rebroadcast operation independently. Knowledge on
local network densities is created on demand, without relying on HELLO packets or GPS
systems, thus making DibA highly reliable avoiding at the same time the introduction of
extra overhead traffic.
The remainder of this chapter is organised as follows. In Section 2 we overview related
work. DibA as an adaptive broadcast mechanism is introduced in Section 3. In Section 4 the
process of building a highly diverse network topology, where the performance of adaptive
schemes can be evaluated appropriately is explained. The performance study is presented in
Section 5. Finally, we make concluding remarks in Section 6.
2. Related works
In this section the Distance-Based scheme will be presented in detail, as our proposed
scheme enhances this algorithm in order to make it locally adaptive. We will also discuss the
general characteristics of other adaptive schemes and their methods.
2.1 Distance-Based scheme
DB is a broadcast mechanism that uses the distance between sender and receiver to make
the decision whether to rebroadcast or not (Ni et al., 1999). The power of the received signal
is a parameter that can be used to calculate the distance. GPS can also be used for that
purpose. The specific algorithm for DB is presented in Fig. 1.
An Adaptive Broadcasting Scheme in Mobile Ad Hoc Networks

245

Fig. 1. DB Algorithm
The distance threshold used in DB, is a parameter valued by default. This value is fixed and
does not change unless there is administrative intervention. This is the major drawback of
DB, as a static threshold may be appropriate for a network of specific density under

particular circumstances. It could potentially cause poor network performance when the
density or other network conditions greatly differ (Williams et al., 2002).
2.2 Adaptive schemes
Over the past few years, a growing number of studies have been trying to develop adaptive
versions of DB. In order to achieve this, having the instantaneous knowledge of network
configuration (in particular, the number of mobile nodes placed within the transmission
range of each sender) is required. Currently, there are only two methods used to determine
the local density for every individual node.
The first mechanism makes use of a positioning system such as Global Positioning Systems
(GPS) (Deng et al., 2006). Mobile nodes periodically exchange messages including their exact
coordinates. When a mobile node receives these coordinates it can calculate the distance
from its current position and decides if the transmitting node is placed inside the
transmission radius. In case that is true, the node increases its neighbours counter and
therefore it can determine the level of network density locally. The use of expensive
positioning systems, such as GPS, is the limitation of this approach.
According to the second mechanism (Ryu et al., 2004), (lee et al., 2006), (Chen et al., 2002),
(Colagrosso 2007), (Chen et al., 2003), (Kyasanur et al., 2006), (tseng et al., 2003) the mobile
nodes need to periodically send HELLO packets to all their neighbouring nodes and
consequently count the number of responses they receive to measure the local density. It is
obvious that this approach introduces a significant amount of overhead traffic in the
network that could negatively affect the overall network performance, especially in cases
where the network is highly populated and already overwhelmed with other types of traffic.
In addition, one also needs to decide on the frequency of this procedure to take place. It
should be remembered that although an increase in performance is the net result of
introducing overhead (i.e. HELLO packets) and reducing overhead (i.e. fewer
rebroadcasting), a frequent transmission of HELLO packets in static networks only increases
the amount of overhead.
Algorithm: DB
Input: broadcast message (msg)
Output: decides whether to rebroadcast or not

S1. When a broadcast message, msg, is heard for the first time, initialize d
min
to the
distance of the broadcasting node. If d
min
< D (where D is the distance threshold),
proceed to S5. In S2, if msg is heard again, interrupt the waiting and perform S4.
S2. Wait for a random number of slots. Then submit msg for transmission and wait until
the transmission actually starts.
S3. The message is on the air. The procedure exits.
S4. Update d
min
if the distance to the host from which msg is heard is smaller. If d
min
< D,
proceed to S5. Otherwise, resume the waiting in S2.
S5. Cancel the transmission of msg if it was submitted in S2. The host is inhibited from
rebroadcastin
g
the messa
g
e. Then exit.
Mobile Ad-Hoc Networks: Protocol Design

246
Although both supporting mechanisms exploit adaptivity, they also have significant
drawbacks that could produce additional constraints. In the next section, we propose a
novel broadcast algorithm which is neither relying on any positioning system nor
introducing overhead traffic.

3. Distance-based Adaptive scheme (DibA)
To perform adaptively without introducing any further constraints and in order to decide
whether or not to rebroadcast a message, any broadcast scheme requires to provide
information about the local density of network for every node.
In our approach, we make use of Step 2 (S2) of the DB original algorithm, presented in Fig.
1, and make minor changes to Step 4 (S4). According to DB in S2, the receiving mobile node
needs to wait for a random number of slots and remains in listening mode for duplicate
broadcast packets. During that period of time, upon reception of a duplicate packet, it
calculates the new distance and compares it with the distance threshold D.
We take advantage of this waiting period and calculate the number of duplicate packets
received, using a simple counter which is updated in S4. The number of identical packets
arriving at the mobile node is closely connected to the number of neighbouring nodes. Each
time the value of the counter increases, the distance threshold is tuned according to a
specific pattern.
The increase or decrease of the distance threshold is closely related to the potential additional
coverage area that could be achieved when the broadcast packet is transmitted. If a large extra
area is predicted to be covered by rebroadcasting of a packet, the distance threshold should be
set to a low value. That is the case when the counter value is low. On the contrary, if the
predicted coverage area is small, the distance threshold should be adjusted to a high value.
This is also the case when the counter value is high. It is obvious that counter value, distance
threshold and extra coverage area greatly affect one another in that order.
The DibA algorithm makes use of a scaled if statement for the adjustment of the distance.
This should lead to an exponential increase of the distance threshold depending on the
counter value. An example of the scaled if statement is as follows.

if(count = 1)
D = 50m;
else if(count < 4)
D = 125m;
else

D =200m;


Fig. 2. Extra Coverage Area Analysis
A
B
d
r
r
An Adaptive Broadcasting Scheme in Mobile Ad Hoc Networks

247
In order to justify the reason why this pattern is used, we need to take into consideration the
redundant rebroadcast analysis performed in (Ni et al., 1999). Consider the scenario in Fig.
2. Node A sends a broadcast packet and node B decides to rebroadcast it. Let S
A
and S
B

denote the circle areas covered by the transmission ranges of nodes A and B respectively.
The gray area represents the additional area that will be covered by B’s rebroadcast named
S
B-A
. We can derive that:
2
()
BA
SrINTCd
π
−

=−
where INCT(d) is the intersection area of the two circles centred at two points distanced by d.
22
/2
() 4
r
d
INTC d r x dx=−
∫

The extra coverage area gets the maximum value when r = d and is equal to:
22 2
3
( ) 0.61
32
rINTCrr r
π
π
π
⎛⎞
−=+≈
⎜⎟
⎜⎟
⎝⎠

Thus, B’s rebroadcast can cover an extra area of 61% of the area covered by the previous
transmission. The average extra coverage area can be obtained by integrating the above
value over the circle of radius x centred at A for x in [0, r]:
2
2

2
0
2()
0.41
r
xrINTCx
dx r
r
ππ
π
π
⎡⎤
⋅−
⎣⎦
≈
∫

A rebroadcast can cover an additional of 41% area in average. Following the same pattern,
the extra area covered can be calculated depending on the number of transmissions heard
for the broadcast packet. The result is shown in the graph of Fig. 3.

0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4

0.45
12
3
4
5
6
7
8
9
10 11 1
2
Num be r of T ransm is sions He ard
Percentage of Additional Coverage Area

Fig. 3. Analysis of Redundant Rebroadcasts
Mobile Ad-Hoc Networks: Protocol Design

248

Fig. 4. DibA Algorithm
The value of the distance threshold could change multiple times during the waiting period
and every time a duplicate broadcast packet is received, the distance between sender and
receiver is compared with the current value of the threshold. The details of DibA algorithm
are presented in Fig. 4, where D is the distance threshold, count is the counter described
above, D
1
, D
2
… D
n

are the predetermined threshold values and c
1
, c
2
… c
n
are
predetermined counter values.
DibA’s primary goal is not to calculate accurately the number of neighbouring nodes, but to
decide upon the density level of the network locally inside the transmission radius. This
feature gives an extra advantage to our approach in comparison to other adaptive schemes.
Let us consider part of a network topology as shown in Fig. 5. This is an extremely diverse
topology as in the right part of the network only 1 node is placed. The left part of the
network covers 12 nodes. All nodes have the same transmission range TR. The black node
(BN) sends a broadcast message that will be received by all of its neighbouring nodes. In this
example, the only neighbour of BN is the grey node (GN).
When we use one of the already existing adaptive schemes, GN will try to calculate the
exact number of nodes inside the transmission radius. Either using GPS or HELLO packets,
the end result of the calculation will be very close to 12, the total of all white nodes (WN)
and BN. As a result, GN will decide that the network is very dense locally and tune the
distance threshold to be high, in order to rebroadcast only if it is placed at the edge of BN’s
transmission range. In case that the distance between BN and GN is not large enough to
exceed the tuned distance threshold (Fig. 6), GN will not rebroadcast. None of the WNs will
receive the broadcast packet.
Algorithm: DibA
Input:
broadcast message (msg)
Output: decides whether to rebroadcast msg or not

S1.

When a broadcast message msg is heard for the first time, initialize d
min
to the
distance of the broadcasting node and the count to 1. If d
min
< D (where D is the
distance threshold), proceed to S5. In S2, if msg is heard again, interrupt the waiting,
increase count by 1 and perform S4.
S2.
Wait for a random number of slots. Then submit msg for transmission and wait
until the transmission actually starts.
S3.
The message is on the air. The procedure exits.
S4.
Update d
min
if the distance to the host from which msg is heard is smaller.
If count is less than c
1

then D ← D
1

else if count is less than c
2

then D ← D
2

else …

……
else if count is greater than c
n

then D ← D
n

If d
min
< D, proceed to S5. Otherwise, resume the waiting in S2.
S5.
Cancel the transmission of msg if it was submitted in S2. The host is inhibited from
rebroadcasting message. Then exit.
An Adaptive Broadcasting Scheme in Mobile Ad Hoc Networks

249

Fig. 5. Diverse Network Topology

Fig. 6. Existing Adaptive Schemes
In case that DibA is used as the broadcast scheme, after reception, GN will wait for a
random period of time counting duplicate packets. As BN is the only neighbour that has
broadcasted the packet, GN exits the listening mode with the counter value of 1. It then
assigns a very low value for the distance threshold. Now, it is highly possible at this point,
as the threshold is very low, that GN is placed outside the dotted circle, as shown in Fig. 7.
As a result, GN will rebroadcast the packet and all WNs will receive it.
In this example, we have shown that knowing the exact number of neighbouring nodes is
not always ideal when trying to decide upon the appropriate value for the distance
threshold. DibA measures the level of local density, depending on duplicate receptions and
not on the knowledge about the amount of neighbours. Thus, it is highly reliable for both

normal and extremely diverse network topologies.
BN T
R
GN T
R
BN T
R
GN T
R
Thr
Mobile Ad-Hoc Networks: Protocol Design

250

Fig. 7. DibA
4. Building a diverse network topology
Most of studies (Ni et al., 1999), (Leng et al., 2004), (Zhu et al., 2004), (Qayyum et al., 2002),
(Hsu et al., 2005), (Purtoosi et al., 2006), (Barrit et al., 2006), (Ryu et al., 2004), (Lee et al.,
2006), (Chen et al., 2002), (Colagrosso 2007), (Chen et al., 2003), (kyasanur et al., 2006),
(Tseng et al., 2003) are relying on a simple network topology consisted of nodes distributed
nearly evenly in an area when studying the performance of a broadcast scheme. However,
the performance of any adaptive scheme is more appropriately demonstrated when tested
on a diverse network topology, where part or parts of the network significantly differ in
mobile nodes population volumes. In this section, we present the implementation of an
automatic mechanism that can be used to create this kind of topologies.

The simulation tool that we use for our experiments is NS-2.30. NS-2 offers a single tool for
creating mobility files using the setdest command. The user has the options to select the
length and width of the topology, the number of nodes, pause time, maximum and
minimum speed and simulation time. Unfortunately, setdest does not provide options to

create more complex scenarios. However, the mobility files generated are of a simple text
format, which gives us the opportunity to manually intervene inside the files and make
appropriate changes.
The structure of the mobility file is as follows. Every node is assigned with its initial X, Y, Z
coordinates in a command line. For example:
at 0.0 (time) node(0) 2.345 4.123 0.0
After all nodes are assigned initial coordinates, setdest randomly selects the time point
where each node will change its direction and speed in order to reach a specific (X, Y, Z)
point inside the topology. An example of such a command line is:
at 3.4567 (time) node (0) 4.899 13.756 10.392
Where the first parameter after “node(0)” (4.899) is the X coordinate for the reaching point,
the second parameter (13.756) is the Y coordinate for the reaching point and the third
BN T
R
GN T
R
Thr
An Adaptive Broadcasting Scheme in Mobile Ad Hoc Networks

251
parameter (10.392) is the speed of the mobile node. We have not included other parameters
that are of no significance for the movement of the nodes in our examples.
We will explain how our mechanism works using a simple example. Let us consider the case
where we want to create the topology presented in Fig. 8.
The nodes need to move inside their own half of the network. The fact that there is
limitation of movement using borders helps to keep a balanced percentage of



Fig. 8. A Sample Diverse Topology

Fig. 9. Base Topology
250m 250m
500m
250m
500m
Mobile Ad-Hoc Networks: Protocol Design

252
differentiation. Simulation results are not affected, as the traffic generated is not unicast or
multicast but broadcast. Our main goal is for all the mobile nodes to receive the broadcast
packet.
In the above topology, 20% of the mobile nodes (4/20) are placed inside the right part of the
network and 80% of them (16/20) are placed inside the left part. In order to create this
topology, we need to start from a base topology as presented in Fig. 9.
The volume of diversity is then specified by selecting an appropriate percentage of the
mobile nodes, which in our example is 20%. These are the black nodes of Fig. 9. We
developed a simple software tool that scans the mobility file for all the command lines that
either initialize or change the movement of all 4 black nodes. The value of X in these
command lines is then increased by 250m, in order to migrate the black nodes over to a
topology of identical length and width that touches the base topology vertically. Fig. 10
shows the migration process.
The movement of the black nodes initially is limited with regards to the X coordinate
between 0m and 250m. Thus, after the modification of the mobility file, these nodes are
restrained to move inside the right half of the topology, with the X value varying between
250m and 500m.
As a result of the process described above we get the end result of Fig. 8.

Fig. 10. Migration Process
5. Performance analysis
We implemented Distance-Based Adaptive scheme (DibA) and Distance-Based scheme (DB)
using the network simulator NS2.30. We have used the NS2 code for DB provided by (Barrit
et al., 2006), (Williams et al., 2002).
5.1 Simulation set-up and parameters
Node mobility is simulated using mobility files that are generated by the NS2 mobility
generation feature setdest. Our experiments make use of both normal and diverse
250m250m
500m
An Adaptive Broadcasting Scheme in Mobile Ad Hoc Networks

253
topologies,

REACHABILITY
30
40
50
60
70
80
90
100
110
20 40 60 80 100 120 140 160 180 200
Number of Nodes
Percentage

%
DibA DB-10 DB-50 DB-90

Fig. 11. Reachability – Normal – BGR 5p/s

DELAY
0
0.02
0.04
0.06
0.08
0.1
0.12
20 40 60 80 100 120 140 160 180 200
Number of Nodes
Sec
DibA DB-10 DB-50 DB-90

Fig. 12. Delay – Normal – BGR 5p/s
in order to cover the majority of possible scenarios. The network area is of fixed size
500x500m
2
. The mobility files are created with zero pause time. Mobile nodes move with
maximum speed of 5m/sec. Each simulation has duration of 100secs and all mobile nodes
use a transmission range of 100m.
Each scenario is restricted to the transmission of broadcast traffic only. This is a common
strategy, especially when using very high broadcast generation rates (BGR). Combining
normal traffic with broadcast traffic is a step further for our work with the implementation
currently taking place. In order to avoid anomalies, we run three simulations for every
scenario using three different mobility files. Our research has found no work until this point,

where more than 3 or 4 repetitions are used. The final results are created as an average of
the three simulations.
Experiments where performed using 3 different distance thresholds for DB of 10m, 50m and
90m, in order to cover the two extremes and an intermediate value. DibA tunes the distance
Mobile Ad-Hoc Networks: Protocol Design

254
threshold to one of the 3 thresholds mentioned above, depending on the local level of
density. The number of nodes has a starting value of 20 and reaches a maximum of 200
nodes with a step of 20 (20, 40, 60, …, 200).
We first divide our simulations into two groups according to the broadcast generation rate.
BGR is set to 5packets/sec and 60packets/sec. Furthermore, we also divide the simulations
depending on whether a normal or a diverse topology is used.
The following performance metrics are considered:
• Reachability – The percentage of nodes that successfully receive the broadcast message.
• Delay – The time elapsed from the initiation of the broadcast process until no more
rebroadcasts take place.
• Average number of Packets transmitted per node (APT) – This is a self explained
performance metric which is closely related to energy efficiency.
5.2 Simulation results
Fig. 11, 12 and 13 present the performance of the 4 schemes, when normal scenarios are used
and BGR is set to 5packets/sec.
Fig. 11 shows that DB-90 performs very poorly due to the high threshold value, whereas all the
other schemes perform almost identical. Although DB-90 appears to be very fast in Fig. 12, that
is because of the very low level of reachability. DB-10 is the slowest, despite the fact that has
similar reachability with DB-50 and DibA. The latter two again perform in a similar way. Fig.
13 shows that DB-10 uses a significantly higher number of transmissions in order to achieve
the same level of reachability with DB-50 and DibA. Thus, it is the least energy efficient.
Fig. 14, 15 and 16 show how the 4 schemes perform when the topology is diverse and the
broadcast generation rate is low.

Fig. 14 reflects the performance of all schemes in terms of reachability. Although DibA, DB-
10 and DB-50 perform almost identical when the network is dense (120 nodes or more), for
sparse topologies DB-10 is slightly better than DibA and in turn that is better than DB-50.
DB-90 again performs poorly. DB-10’s slightly better performance for reachability, proves to
be extremely costly, as it is much slower than the rest and APT is almost double than the

Average Packet Transmission
0
20
40
60
80
100
120
140
160
20 40 60 80 100 120 140 160 180 200
Number of Nodes
Number of Packets
DibA DB-10m DB-50m DB-90m

Fig. 13. APT – Normal – BGR 5p/s
An Adaptive Broadcasting Scheme in Mobile Ad Hoc Networks

255
REACHABILITY
30
40
50

60
70
80
90
100
110
20 40 60 80 100 120 140 160 180 200
Number of Nodes
Percentage
%
DibA DB-10 DB-50 DB-90

Fig. 14. Reachability – Diverse – BGR 5p/s
following scheme. Energy efficiency is very poor in these conditions. DibA appears to be
better than DB-50 for sparse topologies and similar when density increases. Better
reachability usually comes with more latency and more APT. For DibA and DB-50 this is
reflected in Fig. 15 and 16.
Fig. 17, 18 and 19 present the performance of the 4 schemes when normal scenarios are used
and BGR is set to 60packets/sec.
Fig. 17 shows that for sparse networks (up to 60 nodes) DibA and DB-10 have the same
performance with DB-50 being slightly worse. For very dense networks, DibA is now
performing better than the rest. DB-90 is completely outperformed. Despite the fact that DB-
10 has lower reachability when compared to DibA, Fig. 18 and 19 show that it is
disproportionally slower and energy inefficient. DB-50 shows slightly better performance
for delay and APT, but that is due to its lower reachability.

DELAY
0
0.01
0.02

0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.1
20 40 60 80 100 120 140 160 180 200
Number of Nodes
Sec
DibA DB-10 DB-50 DB-90

Fig. 15. Delay – Diverse – BGR 5p/s