Development of Hybrid Ad Hoc on Demand Distance Vector Routing Protocol in Mobile Ad hoc Network

Abstract

MANET include wirelessly in a self-configured, self-healing network while not having permanent communication that is linked in a collection of mobile networks. The network topology varies normally in MANET nodes and is free to stir erratically and individually. In the existing technique, Ad hoc On-Demand Distance Vector (AODV) was employed for node selection to attain the shortest path strategy. In this technique, huge amount of control messages are transferred which consumed bandwidth of the network and increase congestion. In the proposed system, the hybrid AODV technique incorporates the MFR (Most Forward within Radius) technique is utilizing to detect the shortest path routing algorithm. The MFR technique has been performed for the neighbor node selection whereas Hybrid AODV has been performed for the shortest path routing algorithm. Firefly algorithm is also incorporate in Hybrid AODV to find out the optimum path based on the updating equation. The performance analysis and the comparative analysis of this paper are measured by using End to End delay, Average Routing Overhead, Throughput. Proposed algorithm (HAODV) shows improvement in all these parameters.

Full text

Goyal et al., International Journal on Emerging Technologies 11(2): 135-139(2020) 135
International Journal on Emerging Technologies 11(2): 135-139(2020)
ISSN No. (Print): 0975-8364
ISSN No. (Online): 2249-3255
Development of Hybrid Ad Hoc on Demand Distance Vector Routing Protocol in
Mobile Ad hoc Network
Ankur Goyal1, Vivek Kumar Sharma2 and Sandeep Kumar3
1Research Scholar, Department of Computer Science Engineering,
Jagannath University, Jaipur (Rajasthan), India.
2Professor, Department of Engineering and Technology, Jagannath University, Jaipur (Rajasthan), India.
3Assistant Professor, Department of Computer Science Engineering, Amity University, Jaipur (Rajasthan), India.
(Corresponding author: Ankur Goyal)
(Received 09 December 2019, Revised 05 February 2020, Accepted 10 February 2020)
(Published by Research Trend, Website: www.researchtrend.net)
ABSTRACT: MANET include wirelessly in a self-configured, self-healing network while not having permanent
communication that is linked in a collection of mobile networks. The network topology varies normally in
MANET nodes and is free to stir erratically and individually. In the existing technique, Ad hoc On-Demand
Distance Vector (AODV) was employed for node selection to attain the shortest path strategy. In this
technique, huge amount of control messages are transferred which consumed bandwidth of the network and
increase congestion. In the proposed system, the hybrid AODV technique incorporates the MFR (Most
Forward within Radius) technique is utilizing to detect the shortest path routing algorithm. The MFR
technique has been performed for the neighbor node selection whereas Hybrid AODV has been performed
for the shortest path routing algorithm. Firefly algorithm is also incorporate in Hybrid AODV to find out the
optimum path based on the updating equation. The performance analysis and the comparative analysis of
this paper are measured by using End to End delay, Average Routing Overhead, Throughput. Proposed
algorithm (HAODV) shows improvement in all these parameters.
Keywords: AODV, End to end delay, Firefly algorithm, Hybrid AODV, MFR, MANET, Routing overhead, Throughput.
I. INTRODUCTION
A MANET can be described as a system that includes
wirelessly connected hosts. A gathering of more
terminals with wireless interactions along with network
capability is referred in MANET [1, 2]. That
communicates with each other without any consolidated
supervisor. Wireless links are free changeable and also
occasionally acts as a router at the similar time are
linked with mobile hosts [3]. In MANET, it is a sovereign
methodology along with the nodes is shared in wireless
standard. The concern of the network varies arbitrarily
as well as actively. A communication link is frequently
busted in MANET because the nodes are liberated to
move wherever [4].
The most popular routing protocol is AODV and it is also
simple along with a well-organized on-demand MANET
routing protocol [5, 6]. To supports unicast along with
multicast routing and routes to destinations on demand
recognized in the protocol. The MANET routing protocol
urbanized because of particularly in AODV [7]. The
route discovery methodology operation and therefore
the route maintenance operation is the two various
operations to seek out and maintain in AODV. It’s a
desired algorithm for MANET also further as acquires
the routes strictly on-demand [8].
Briefly, the main contributions of this paper are as
follows:
– Proposing a Hybrid AODV routing algorithm based on
shortest path selection strategy.
– It improves end to end delay, throughput and routing
overhead with the traditional AODV.
Section I talks about the introduction and the research
study and survey of the work have been written in
section II. Section III discusses about the related work
used in proposed method. Section IV discusses the
proposed technique and Section V discusses the
performance investigation and result. Finally, in section
VI, the conclusion of the paper is given.
II. LITERATURE SURVEY
The AODV routing protocol creates the shortest path
which depends on the best signal as well as strength
quality. The routing process is happening when the path
attain to best signal strength will leads to increasing in
the Packet delivery ratio (PDR). The foremost concept
of this network is to deliver packets with minimum
losses which lead to improved Quality of Service (QoS).
The minimization of link failure for routing is very difficult
in this technique. The minimum losses and minimum
link failure was explained by Devika and Sudha (2019)
[1].
AODV and DSR are the on-demand unicasting routing
protocols to evaluate their performance based on
Quality of Service (QoS). For MANETs, together AODV
and DSR routing algorithms are executed on the root of
an on-demand gateway discovery algorithm anywhere
every other through the entry and exit point of a system
and where required. Through simulation with increasing
the node density using the ns-2 network simulator, we
perceive that the performance of AODV and DSR
routing protocols are varying according to the situation
as directed to premier the performance level for both of
these protocols is produced by Robinson et al., (2019)
[4]. The consequences give out in this paper decorate
the significance of carefully assessing and executing
both of these protocols for MANETs.
e
t

Goyal et al., International Journal on Emerging Technologies 11(2): 135-139(2020) 136
The hybrid Ant Colony Optimization (ACO) along with
Firefly optimization technique along with swarming
algorithm (FA) is used in Ad-Hoc On-Demand Distance
Vectoring (AODV) routing protocol to transmitted of
signals in a MANET model to increase the efficiency
along with decreasing the losses to overcomes the
drawbacks of ACO based AODV was described by Rath
et al., (2017) [6]. The execution study of the hybrid
routing protocols was compared with the traditional ACO
and traditional AODV by ensuring a lessening of
network load by neglecting re-discovery endeavors
among the paths.
Reactive routing protocols are used, at the same time
source requirements to throw a packet to the destination
so the process of the searching route resolve initialize,
till it discovers the optimal path [7, 8]. Since it, a lot
concentrates on less reliable routes important to
elevated control overhead and packet loss.
Raw et al., (2015) was explained the MFR technique in
which the investigation of position-based routing in
vehicular ad hoc network (VANET) to attain the optimal
route amid the vehicles [10]. The node-based MFR has
been performed by the mathematical expression which
is mainly designed for avoiding the internal nodes
depend on the transmission assortment for
supplementary transferring the packets. The outcomes
of this technique explain the performance of the border
nodes which is advantage of the routing algorithm with
less delay.
III. RELATED WORK USED IN METHODOLOGY
The main purpose of the MANET is to diminish the link
breakage because of the mobility of paths in the
protocol. An acceptable time in favor of broadcast is
established in the stable route in MANETs. In the
traditional AODV, it won’t check the route in a periodic
manner. So that the transmission of data after discovers
the rate is taking more delay. The locally repair a busted
connection does not continue the routing mechanism.
Hence, the proposed HAODV based protocols; the route
detection process is on-demand, which is more efficient
in the dynamic nature of MANET. The rate is created
only when it is required. In table-driven protocols the
delay is advanced.
A. MFR
The MFR routing algorithm is accessible in an
investigative technique. The execution of the MFR
routing strategy is estimated. The amount of time in the
bond is offered for transmission is resulting in as the
lifetime of a wireless connection and also its unit is
seconds. The network maintains the random variable is
considering in the duration of a wireless connection
among bi nodes. From an origin device S to destination
device D are further considered which comprises of
series of m wireless connections form-1 midway nodes.
The duration of the ݅௧௛ link in the route is X୰. The
lifetimes of ܺ௥, ݅ = 1,2,… …. ,݉ − 1 are identically
disseminated (iid) arbitrary variables, each within rate μ
are implicit [9, 10]. The path fails among the origin S
along with destination D when any link of the route
breaks. Therefore it consists of m links is a arbitrary
variable articulated as follows in the duration of this
route r.
X୰= min൫X୪భ,X୪మ, … … X୪ౣ൯ (1)
Where Xr is identically distributed arbitrary variable with
rate m µ. The life span of utilizing a solitary route r is a
random variable R within the rate m µ, where R = X୰
During a lifetime L, the clear successful message
delivery may terminate. The probabilities Q that
communication delivery terminates within L are
consequent. The duration of message rescue is an
identically distributed arbitrary variable D within rate λ is
implicit. D and L are separately sustained via
unsystematic variables the probability of successful
message delivery is articulated [6, 8].
The analysis has been examined by MFR routing
algorithm and also considering the probability of
flourishing message delivery. This analysis indicates the
duration of a path is superior to the duration of message
delivery.
Initially, the AODV defines a route which has less
number of hops to accomplish the target. Due to the
execution elapse mobility, the optimal path converted to
suboptimal paths. Hence, the essential nodes have turn
into relay nodes. The AODV cannot believe
supplementary optimal routes dynamically it accessible
only smaller hop calculations. Hence, the relay nodes
determine per hop delay and depletion of nodes energy
and bandwidth. To overcome the drawbacks of the
AODV, the proposed hybrid AODV routing procedure
has been designed for the dynamic routing algorithm.
By utilizing dynamic and optimal routing protocol, the
unwanted relay nodes get eradicated from the energetic
path and shortcut discovery is agreed.
IV. PROPOSED METHODOLOGY
A hybrid AODV protocol of the MANET is based on the
boundary nodes of the network. The dimension of the
boundary is computed by means of the radius of the
boundary B, where B is the perimeter of the region.
There are overlapping nodes between the nodes and
each node is different in dimension.
In the proposed methodology, each interior node is
communicating with its boundary node using MFR
protocol and the nodes are clustered between the
cluster head by utilizing optimal AODV protocol. The
central node is accurately equivalent to zone radius with
the minimum distance of the nodes which is the
peripheral nodes of the individual boundary. If the nodes
minimum distance is less than the radius of the interior
nodes, then the nodes is said to be exterior nodes. The
cluster boundary routing is done by utilizing the
gateway.
In the proposed hybrid routing algorithm, the MFR
incorporate with optimal AODV routing beneath dynamic
cluster head path for the distributed networks, the
primary issues of the distributed network is the
occurrence of the shortest path and it depend on
chosen neighbors in the network. The information is
transferred to the destination based on the neighbor
nodes and each data packet must have a destination
identifier and it will continue still it’s accomplishing the
target. After receiving the packet, to attain the common
purpose of routing packets along the optimal path so
that the routing tables are constructed, maintained and
updated. Routing table update and path finding are the
two main sections in the hybrid routing methods.

Goyal et al., International Journal on Emerging Technologies 11(2): 135-139(2020) 137
A. Calculation of fireflies count
In the proposed HAODV, the firefly optimization
technique is used for the HAODV routing protocol in
which the optimal shortest path has been selected to
transmit the packets from source to the destination to
avoid the routing overhead and increase in packet
deliver ratio.
Fig. 1. Flow chart of the optimization algorithm.
B. Routing Process
In the projected hybrid routing algorithm, the procedure
of routing comprises of six sections. They are route
demand initialization method, route demand forwarding
method; route demand receives method, route respond
sending method, route respond forwarding method
along with route respond receiving process. When the
node desires to transfer the packets from starting place
to target, it will initially verify the available path. If it is
available, the information is transferred from source to
the target if not the route discovery process is activated.
In the path finding procedure, initially the source nodes
verify the boundary nodes acknowledgement signal
strength is greater than or equal to the signal threshold
(SIGNAL_THR) [11, 12]. If it is greater than or equal to
the signal threshold, the boundary nodes find out the
RSSM esteem therefore the routing table calling of the
neighbors has been formed in addition to stored the
attained RSSM esteem in the RSSM field with respect
to the calling of the boundary nodes.
C. Optimal AODV routing process
Initially, the calling of the boundary nodes are set to 0
which is corresponding to the firefly counts, and demand
firefly message has been transferred to the boundary
nodes in which the initial firefly count set as 0. If the
respond node of the demand firefly is a destination, it
generate a access of demand fireflies designer in the
routing table and therefore it counts the firefly and
append it through the content of fireflies count field of
responded demand firefly. Finally, the outcome of the
firefly count is appended in the routing table entry.
The destination node might be retrieved multiple
demand fireflies after remaining from the particular
duration. It updates the firefly counts of the source
nodes in the routing table which has higher firefly count
esteem among multiple demand fireflies.
The nodes verify the reply firefly which is received from
some other nodes and it is verified the nodes which
beneath to destination node. If not, then it computes the
fireflies count with the content of firefly count field of the
reply fireflies and stored the count esteem in the routing
table access and also store the outcomes of firefly count
of reply fireflies. Finally, it forwards the reply fireflies to
the neighbor node to achieve the target.
The nodes verify the reply firefly which is received from
some other nodes and it is verified the nodes which
beneath to destination node. If it is a destination, then it
generates a routing table access of the reply fireflies’
designer and therefore it update the firefly count in the
routing table access. Finally, the information packet is
transferred from source to the destination.
In the proposed hybrid routing protocol, the MFR
incorporate with optimal AODV using firefly optimization
algorithm is computed to transfer the data packets
beginning source to the destination. The neighbor nodes
are computed based on the MFR techniques and the
overall routing protocol is generated based on the
optimal AODV using firefly optimization algorithm.
V. PERFORMANCE ANALYSIS
In the projected hybrid routing protocol, the throughput,
packet delivery ratio along with routing overhead has
been performed for the performance analysis. The
comparative analysis of the proposed routing procedure
comprises of traditional DSR and traditional AODV
protocols. The performance analysis has been
computed it for varying number of devices. The
simulation results have been designed by using
MATLAB 2016a version. Node velocity is taken as 10
m/s and data velocity as 16 kbps. The maximum
number of connections to CBR traffic is taken as 10.
In this study, the proposed system had shown good
results when compared with the previous technique.
Some of the initialization parameters of the node
selection process have been explained as follows
Table 1: Initialization Parameters.
Number of wireless
hosts 50 100 150 200
Mobility Model Random Walk
upper limit Channel
Power 2mW
Radio Bitrate 100kbps
Execution period(s): 3400
overall Packets
transmit: 3397
Execution Style: Cmdenv-fast-mode
– Routing Overhead: The average amount of
information packets might be transferred in single
information packet in this routing protocol which
consumes additional bandwidth by overhead to bring
information traffic.
Table 2: Routing Overhead with different amount of
nodes.
Technique N=50 N=100 N=150 N=200
HAODV 2.98 4.35 5.95 7.05
AODV 9.79 12.61 17.18 22.85
Table 2 demonstrates the routing overhead for the
different amount of nodes. The average value of
HAODV is of 5.082. The ADOV average value is
15.607. As a result, the HAODV obtained a better
performance measure than AODV technique.
Fitness
Calculation
Initialization
Best Storage
Updation

Goyal et al., International Journal on Emerging Technologies 11(2): 135-139(2020) 138
Fig. 2. Routing Overhead.
Fig. 2 illustrates the routing overhead of HAODV has
been diminish when compared with other routing
protocol. This data reflects that improvement of HAODV
in terms of Routing overhead is 67.43% with AODV.
Throughput (messages/second): The complete
amount of retrieved information packets separated by
overall duration of execution period. For the throughput
of this network, messages are delivered per one
second.
Throughput = Number of bytes received × 8
execution time × 1024 Kbps
Table 3: Throughput with varying number of nodes
Technique N=50 N=100 N=150 N=200
HAODV 315.34 345.92 365.98 370.11
AODV 276.17 309.29 320.85 321.76
Table 3 demonstrates the throughput versus different
amount of nodes with the comparative analysis with
traditional AODV technique. HAODV shows 12.11%
increased the throughput as comparison to AODV. The
better outcomes of the HAODV are attained because of
the optimal path selection in the AODV routing network.
Fig. 3. Throughput.
Fig. 3 demonstrate the throughput of the network with
different amount of nodes. In the proposed HAODV, the
parallel computation of neighbor node selection along
with optimal path selection has been performed which
leads to less power consumption hence the throughput
of the proposed model provide the better outcomes.
End to End delay: It is the overall execution period for
the data transmission begins from source to destination
across MANET. The end to end delay has been
performed which is depend on routing finding latency,
queuing at the border queue along with retransmission
hindrance, broadcast and transmission period.
Table 4: End to End delay with number of nodes.
Technique N=50 N=100 N=150 N=200
HAODV 0.11 0.16 0.19 0.26
AODV 0.59 0.64 0.71 0.76
Table 4 explained the end to end delay with varying
number of nodes has been calculated. The average
esteem of the end to end delay of HAODV is 0.18. The
average esteem of traditional AODV is 0.67.
Fig. 4. End to End delay.
From the Fig. 4, the HAODV illustrate the lower end to
end delay when compared with traditional AODV
technique. Hence, the lesser end to end delay has been
attained for the proposed HAODV technique when
compared with other comparative analysis. Table 4
reflects that average End to end delay of HAODV has
decreased with respect to AODV. Average End to end
delay has reduced 73.13% with respect to AODV.
VI. CONCLUSION
In the proposed technique, the optimal HAODV
technique is used to found the shortest path from origin
to target place. As a result of the study, the proposed
technique illustrated the best performance measure
when compared to the other technique. The main
objective of the proposed system requires reliable,
scalable, and self-organizing, rapidly deployed and they
use a dynamic routing algorithm which leads to a better
increase in routing overhead, Average-End-to-end
Delay and throughput. This proposed technique was
implemented by MATLAB. It has been analyzed that the
proposed hybrid technique performs good quality as
compared to AODV routing protocol in terms of the
performance analysis. By comparing those protocols
performance measurements, it has been shown that
reactive topology-based algorithms are better than
proactive topology-based routing procedures.
0
5
10
15
20
25
N=50 N=100N=150N=200
Routing Overhead
No. of Nodes
No. of nodes Vs Routing Overhead
Hybrid
AODV
AODV
0
50
100
150
200
250
300
350
400
N=50 N=100 N=150 N=200
Throughput
No. of Nodes
No. of nodes Vs Throughput
Hybrid
AODV
AODV
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
N=50 N=100 N=150 N=200
End to end delay
No. of nodes
No. of nodes Vs End to end delay
Hybrid
AODV
AODV

Goyal et al., International Journal on Emerging Technologies 11(2): 135-139(2020) 139
VII. FUTURE SCOPE
The security in MANETs has also become more
important accordingly in future. Inherent characteristics
of MANET i.e. wireless medium, broadcast transmission
and lack of centralized administration render mobile ad
hoc networks vulnerable to security hazards. Security
aspects in the work have not been considered which
can be taken care of as future extension of the work.
Secondly, for the selection of the neighbor nodes; it may
be consider selecting energy efficient nodes in the
future work.
ACKNOWLEDGEMENTS
The authors would like to thank reviewers and editorial
boards for their valuable comments that improve the
quality of this manuscript.
Conflict of Interest. There is no conflict of interest for
any of the authors in this paper.
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How to cite this article
:
Goyal, Ankur, Sharma, Vivek Kumar and Kumar, Sandeep (2020). Development of Hybrid
Ad Hoc on Demand Distance Vector Routing Protocol in Mobile Ad hoc Network. International Journal on Emerging
Technologies, 11(2): 135–139.