Modified Route Request Broadcasting for Improving Multipath Routing Scheme Performance in MANET

International Journal of Computer Networks & Communications (IJCNC) Vol.16, No.4, July 2024
DOI: 10.5121/ijcnc.2024.16407 131
MODIFIED ROUTE REQUEST BROADCASTING FOR
IMPROVING MULTIPATH ROUTING SCHEME
PERFORMANCE IN MANET
Priyanka Pandey1
and Raghuraj Singh2
1,2
Department of Computer Science and Engineering, Harcourt Butler Technical
University, Kanpur, India.
ABSTRACT
Mobile Ad Hoc Network (MANET) is growing in popularity with the advent of 5G wireless network and
Internet of Things. In this type of peer to peer network, nodes are self-configurable and communicate
among themselves wirelessly. Typically, these nodes are powered by batteries and move continuously
within the specified region. In order to provide efficient communication between these devices, several
routing protocols have been designed. However, most of the schemes focus on construction ofshortestroute.
With this approach, it is not always possible to provide reliable and efficient path in highly dynamic
environment to carry out data transmission process. In this paper, a novel Adaptive and Stable Multipath
Routing Scheme (ASTMRS) has been proposed in which only peer nodes with good fitness values are
allowed to process route request packet. This fitness value is estimated based on node mobility, residual
energy and distance metrics. Further, each node updates its next hop information on the basis of node
degree and received signal power. Simulation has been conducted under various network scenarios such
as packet rate and pause time. Under different scenarios, an average improvement of 15.82% and 14.38%
has been seen in packet delivery ratio(PDR) and throughput respectively; other performance metrics such
as normalized routing load (NRL) and delay have been reduced to 15.58% and 13.95% respectively
against AOMDV. Similarly, as compared to AODV, the scheme shows 15.96% and 15.78% improvement in
terms of PDR and throughput respectively. Moreover, NRL and delay are reduced by33.04% and 38.92%
respectively against AODV.
KEYWORDS
Multipath, Routing, MANET, AOMDV, RWP, Reactive.
1. INTRODUCTION
MANET [1] is a wireless network which provides an instant and peer to peer communication.
Lightweight mobile devices such as PDA’s, palmtop, laptop etc. is very popular in a realm of
wireless ad hoc network. In MANET, mobile devices move continuously and communicate
among themselves through wireless channel. Two nodes that are nearest to the communication
range of each other can directly transmit data whereas devices that are not inside the transmission
range of one another require intermediary nodes for performing routing operation. However, due
to continuous node movements and limited battery power, providing efficient routing operation is
one of the major challenging tasks in this environment. In order to cope with this issue, there is a
need to examine conditions of quality of participating nodes and links during route searching
procedure.
Quality of nodes can be measured through factors such as distance and node mobility. Similarly,
during route establishment process, examination of node battery capacity can help in providing

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stable route. Routing protocols such as DSR [2], AODV [3], AOMDV [4], TORA [5] etc. focus
on making shortest path on the basis of mainly hop count metric during route discovery process.
Among these protocols, DSR and AOMDV are popular multipath routing protocols. In case of
route failure, these protocols do not require initiation of re-route discovery process instead
backup routes are utilized for data transferring. However, they suffer to achieve high performance
due to avoidance of consideration of link and node qualities at the time of final path
establishment.
To address this problem, this paper presents an Adaptive and Stable Multipath Routing Scheme
(ASTMRS) which is a modified version of existing AOMDV to minimize the frequent
occurrences of route breakage. The scheme considers important parameters such as residual
energy, node speed and distance to estimate node quality and link quality during route discovery
operation. It allows only those peer nodes to process route request packets which have good link
and node conditions.Incorporation of aforementioned factors during route establishment process
makes the path more stable and thus reduces the chances of frequent route breakage. Moreover,
each node updates its list of neighbours on the basis of signal quality and node degree factors.
This strategy helps in selection of efficient neighbour nodes that further contributing in
construction of overall stable route. Simulation results show that PDR and throughput
performance has been improved significantly. Furthermore, as compared to other schemes such
as AODV and AOMDV, the proposed approach ASTMRS requires less number of control
packets during whole routing process and transmits data packets with less delay. From the
simulation results it can be concluded that the proposed approach provides more efficient and
stable path to perform routing operation.
The rest of this paper is structured as mentioned: Section 2 describes related work; Section 3
illustrates the methodology adopted for construction of stable routes by selecting efficient peer
nodes. In Section 4, performance and comparative analysis of proposed scheme with other
scheme has been discussed and in the last section conclusion with future direction has been
given.
2. LITERATURE REVIEW
MANET contains set of mobile nodes that move continuously in the network. In this
environment, data forwarding from source to destination is one of the major challenging issues.
In order to perform smooth data packets transmission, several routing protocols i.e. DSR, AODV,
and AOMDV etc. have been proposed. The main objective of these routing protocols is to
recognize a reliable path that can transmit data more efficiently. There are number of routing
schemes have been anticipated to improve the stability of route. This section discusses about the
works related to the improvement of routing protocol performance.
In [6]WesamAlmobaideenet. al. proposed improved SPDA in which stability of an intermediate
node is examined by comparing the number of times each node has been appeared in different
routes and the last time the nodes has been participated in the routing operation. Apart from this,
as soon as the destination node receives the first route request packet, it sends an RREP message
to the source to start data transfer right away. When it receives another RREQ packet, the hop
count metrics is compared with previous one. If newly received RREQ packet has less hop count,
the data packets are transferred through second route. Findings indicate that the suggested
method is able to transmit data packet with less overhead and takes minimum time. However, in
less dynamic environment, throughput has not much improvement.
P. Periyasamyet. al. [7] proposed LR-EE-AOMDV multipath scheme which finds multiple
reliable links and energy efficient multiple routes on the basis of factors such as estimators of

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path link (PLQE )and node (PNEE ) qualities and path length. PLQE is determined using
cumulative Expected Transmission Count (ETX) and PNEE is determined using Cumulative
Expected Transmission Energy (CETE) and path length is the total hop count of a route. Findings
indicate improvement in PDR, routing overhead and throughput performance. However, there is
slight increase in delay with higher network flow.
Stability Enhanced AOMDV [8] considers received signal strength parameter to find more stable
route. It examines signal quality after traversing certain range. During route discovery operation,
an intermediate node forwards an RREQ packet further only when the received signal strength is
above certain threshold. The scheme show significant improvement in performance in terms of
throughput, PDR and NRL. However, delay is higher.
Y. Harold Robinson et. al [9] proposed FD-AOMDV for increasing the scalability. It utilizes the
factors such as average remaining energy of a group of routes and node connectivity. During
route discovery, the scheme removes nodes that have more routing overhead and less battery
backup. Simulation has been conducted on varying pause time, node speed and number of nodes.
Results show improvement in performance. However, slight improvement in delay is seen while
varying number of paths.
Peng Li et. al. [10] proposed an improved routing protocol. On receiving RREQ packets, the
protocol examines queue length of an intermediate node, if it is above threshold, then the scheme
estimates residual energy and updates it in RREQ packet field. Moreover, during receiving hello
message from the sender, it examines residual energy and queue length. If a criterion is satisfied,
the neighbour node list is updated. Simulation results show performance improvement in terms of
route discovery occurrence, delay and amount of energy exhausted nodes. However, there is no
improvement in routing overhead performance.
Multi Objective AOMDV (MO-AOMDV) [11] focuses on selection of route based on node and
link quality. After receiving RREQ packets from multiple paths, the destination node selects final
route on the basis of residual energy and hop count metrics. If during data transmission
congestion occurs at any point, the scheme reduces the speed of data transfer. Simulation results
show improved PDR and network lifetime. However, delay has not been analyzed.
The AEQAOMDV [12] constructs the route on the basis of fitness value. This value is estimated
using average node residual energy and buffer queue length. Final route is selected on the basis of
highest fitness value. The protocol is able to minimize delay and route discovery frequency, and
maximizing PDR. However, there is slight improvement in routing overhead performance.
Pravin R. Satav [13] presented an energy efficient route selection approach in which energy level
parameter is considered. During route discovery operation, current energy level of an
intermediate node is estimated to compute overall energy of trajectory. The scheme considers the
path with highest energy level as final route to start data transmission process. Results show that
the scheme maximizes overall network lifetime. However, PDR, delay and throughput
performance metrics have not considered for analysis.
Fitness Function AOMDV [14] (FF AOMDV) focuses on establishment of stable route for data
transmission process. The scheme selects the neighbour nodes on the basis of their energy
efficiency. In this scheme, link quality is estimated using signal strength, delay and queue length
metrics. During route discovery operation, these metrics are considered and the best route is
chosen from multiple routes. Results show that the scheme achieves higher throughout and PDR,
and minimizes delay and energy consumption. However, routing overhead is not considered
while analyzing results.

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Anuradha Banarjeeet. al. [15] presented an approach based on expected residual lifetime (ERL-
AOMDV). During route discovery operation the protocol examines expected residual lifetime
and completion time of communication session and stores the first three optimum routes for data
transmission. Simulation results show improved PDR, throughput and reduction in frequency of
link breakage and delay. However, routing overhead is not considered for performance analysis.
Binuja Philomina Marydasanet. al. [16] presented a reliable and stable TA-AOMDV protocol that
constructs an efficient route by considering two metrics i.e. Destination Region Selection (DRS)
and Weighted Closeness and Connectivity (WCC) metrics. Results show improved PDR, NRL,
throughput and delay in highly dynamic environment. However, it does not work well in less
dense network.
Energy based AOMDV (E-AOMDV) [17] aims to increase network lifetime by considering
energy level of intermediate nodes. During route discovering, each intermediate node has to go
through a check to become a next hop. Through this approach, load balancing among
neighbouring nodes can also be achieved. Simulation results show improved performance in
terms of PDR, throughput and NRL. However, delay is not considered for analysis.
Mani Bushan Dsouzaet. al. [18] proposed an Energy and Link Quality Aware AOMDV (ELQ-
AOMDV) to improve routing performance. During route discovery operation, the scheme
estimates Expected Transmission Count (ETX) metrics to measure link quality and current
residual energy and average residual energy of a path. Based on these factors, it selects the final
route. Results show improved PDR, throughput, delay and NRL. However, there is slight
improvement in PDR as the number of nodes increases.
The work proposed in [19] estimates reward factor using node lifetime and signal power metrics
during route discovery operation. Moreover, local information is updated on the basis of distance
metrics. Findings indicate improvement in PDR, delay and throughput. However, there is slight
improvement in NRL performance. Summary of related works has also been represented in the
Table 1.
Table 1. Summary of Related Work
Ref. Protocol Factors and Mechanism Advantages Remarks
[6]
Improved Stability
based on Partially
Disjoint AOMDV
(ISPDA)
Hop count, Number of times
node appears in different
routes and last occurrence
time of a node
Significant improvement in
routing overhead and delay
performance.
Slight improvement
in throughput and
delay performance.
[7] LR-EE-AOMDV
Reliable energy efficient
path is obtained using path
length, path link and path
node energy estimators.
Improvement in PDR,
throughput and routing
overhead performance.
Slight increase in
delay with higher
network flow.
[8]
Stability Enhanced
AOMDV
Received Signal power is
examined after certain
distance to find more stable
route.
Performance in terms of
PDR, throughput and NRL
is improved.
Delay is higher.
[9]
Fault Tolerant Disjoint
AOMDV (FD-
AOMDV)
Nodes with less battery
backup and extra routing
overhead are removed
during route searching
Improvement in PDR,
overhead.
While varying
number of paths
slight improvement
in delay is seen.

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process
[10]
Improved Routing
Protocol
Consider queue length of a
node and residual energy for
route selection
Reduction in delay, route
discovery occurrence and
number of energy
exhausted node.
No improvement in
routing overhead
performance
[11]
Multi Objective
AOMDV (MO-
AOMDV)
Selects the route on the
basis of node and link
quality.
Increased PDR and
network lifetime
Delay has not been
analyzed.
[12] AEQAOMDV
Fitness is calculated using
load and energy.
Improved PDR and delay
Slight reduction in
routing overhead.
[13]
Energy Efficient
Protocol
Energy level parameter is
considered during route
discovery operation.
Improved lifetime of the
network
Delay and PDR has
not been discussed.
[14]
Fitness Function
AOMDV(FF AOMDV)
Neighbour with efficient
energy and less load is
selected as next hop.
Increase in PDR,
throughput with minimized
delay and consumed
energy.
Performance in
terms of routing
overhead has not
been considered for
analysis.
[15]
Expected Residual
Lifetime based
AOMDV (ERL-
AOMDV)
Residual lifetime of a route
is taken into account.
Increased PDR,
Throughput, route lifetime
with minimized delay and
link breakage
Routing overhead
performance has
not been considered
during analysis.
[16]
Reliable and Stable
TA-AOMDV (RSTA-
AOMDV)
Routes are constructed on
the basis of Destination
Region Selection (DRS) and
Weighted Closeness and
Connected (WCC) metrics.
Improved PDR, delay,
overhead.
Not effective in less
dense network.
[17]
Energy based
AOMDV(E-AOMDV)
Node with highest energy
level is selected as next hop.
Improved PDR, NRL and
routing overhead.
Delay is not
considered during
analysis.
[18]
Energy and Link
Quality Aware
Multipath Routing
Protocol (ELQ-
AOMDV)
Factors such as Expected
Transmission Count (ETX),
residual energy of current
route and average residual
energy of a route are
considered for route
selection.
Improvement in PDR,
throughput, routing
overhead and delay.
Slight improvement
in PDR in dense
network.
[19]
Intelligent and Adaptive
Multipath Routing
Scheme (IAMRS)
Reward factor is estimated
using node lifetime and
signal power.
Improved PDR, delay,
NRL and throughput.
Slight improvement
in NRL.
In the literature review, many works have been suggested to provide stable route . In these works,
apart from hop count and sequence number, other metrics such as node lifetime, residual energy,
signal quality, ETX, DRS etc. have been considered. Nevertheless, in some schemes, there is
either a greater delay [7-8] or very little improvement [6], [9]. The delay metrics have not been
taken into account for analysis in [11], [17]. The entire performance of routing is impacted by
ignorance of this measure. Furthermore, excessive uses of control packets cause a reduction in
channel utilisation. In [10] and [12] no or slight reduction in routing overhead is seen. While in
[14] and [15] this important metrics has not been considered during analysis. In some works,
PDR [18] and NRL [19] have shown very less improvement. This work's main objective is to
lower the frequency of route breaking while taking into account the shortcomings of earlier
efforts. During the route creation process, the scheme takes residual energy, node speed, and
distance into consideration. The effectiveness of the scheme has been validated through
simulation. Following the simulation, all performance indicators that have been taken into

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consideration showed improvement, particularly in terms of throughput and PDR. Additionally,
other metrics like routing overhead, NRL, and delay have also improved.
3. PROPOSED WORK
This paper presents an Adaptive and Stable Multipath Routing Scheme (ASTMRS) for MANET.
The objective of work is to discover a route which can provide an efficient communication
between pair of nodes. Selection of stable path increases the throughput and PDR and decreases
the delay, NRL and control overhead. During route discovery operation, whenever an RREQ
packet arrives at an intermediate node, the node goes through a check. If it satisfies a selection
criterion, then only the intermediate node can send the packet to its next hops. Furthermore, each
node updates its neighbour table list on the basis of node degree and link quality.
3.1. Parameters and Notations
To avoid frequent route breakage, the scheme selects only those intermediate nodes that have
good fitness value. This fitness value is estimated using factors such as node speed, residual
energy and distance. Moreover, during local connection update, each node considers any node as
its next hop which has sufficient number of neighbours and strong link quality between the next
hop and itself. The notations used in the proposed approach have been mentioned in Table 2.
Table2. Notations Used
So
Source Node
Do Destination Node
Io Intermediate Node
NDIS Distance between two nodes
SP Node Speed
NREN Residual energy of a node
FVo Fitness value of a node
SSQ Signal Strength
ND Degree of Node
NDMIN Minimum node degree threshold
NDMAX Maximum node degree threshold
SSQTH Signal Strength threshold
𝑠1, 𝑠2, 𝑡1, 𝑡2 Coordinate positions

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NI Node’s initial energy
𝑁𝐶𝑂𝑁 Total energy consumed
The brief description about the parameters utilized while performing route discovery process
have been mentioned below.
3.1.1. Node Speed
A node's likelihood of experiencing frequent connection failure increases with its speed.
Therefore, nodes that are moving with low speed should be chosen as a part of a route for
forwarding packets. This is one of the parameters which have been taken into account to evaluate
an intermediate node's fitness value throughout the route creation process.
3.1.2. Distance
Distance between two nodes is calculated using Euclidean [20] formula. Let s1, t1 be the
coordinates of node n1and s2, t2 be the coordinates of node n2.Then the distance NDISbetween two
nodes can be calculated using Equation 1.
𝑁𝐷𝐼𝑆 = √(𝑠2 − 𝑠1)2 + (𝑡2 − 𝑡1)2 (1)
This is one of the important factors in determining link quality between two nodes during route
set up process.
3.1.3. Residual Energy (NREN)
In MANET, nodes have limited battery power. During whole routing operation nodes consumes
power. There are four states of energy consumption i.e. nodes consume energy during
transferring and receiving data packets, and during idle and sleep modes.
In sleep mode, no communication is possible and nodes consume very less power as compared to
other modes. During routeconstruction, residual energy of a node must be taken into account to
make route more reliable and stable. It is estimated using Equation 2.
𝑁𝑅𝐸𝑁 = 𝑁𝐼 – 𝑁𝐶𝑂𝑁 (2)
Where 𝑁𝐼 is initial energy and 𝑁𝐶𝑂𝑁 is total energy consumed in different modes i.e.
transfer, receive, idle and sleep mode.
3.1.4.Signal Strength
This metric is used to estimate link quality between two nodes. In the proposed approach, each
node calculates received signal power while receiving hello packet to estimate link quality
between sender and itself.
3.1.5. Node Connectivity Information

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In AOMDV when any node receives a hello packet, it adds sender’s node id and expiration time
information in its neighbour list. In the proposed approach, each node examines signal quality
and number of nodes in sender’s vicinity to make sender as its next hop. This strategy ensures
that each node forwards packets towards efficient neighbours.
3.2. Route Discovery Operation
ASTMRS is an on demand multipath on demand routing protocol and has similar working as
AOMDV. If a source node needs to deliver a data packet to a target node but doesn't have any
routing information for that node in the table, route discovery is started. The source node
broadcasts route request packet to its peer nodes to find the best path for data transmission. In this
work, two more fields have been added to route request packet. The modified RREQ packet
format is shown in Figure 1.
Figure1. Modified Route Request Packet Format
Apart from basic fields such as source sequence number (SSN), Source IP, Destination Sequence
Number (DSN), hop count, flag fields (J, R,G, D,U) etc., two additional fields in RREQ packet i.
e. S position and T position have been incorporated to determine distance between pair of nodes.
Figure 2 shows the block diagram of operation performed during route discovery process. An
intermediate node must undergo a check whenever it gets the route request packet. The scheme
examines fitness value of each node to allow it to further forward the RREQ packet. This fitness
value is estimated by considering important factors such as node speed, distance and residual
energy. Further, weights 𝑚1,𝑚2and 𝑚3have been assigned to each factor such that 𝑚1 + 𝑚2 +
𝑚3 = 1. Thus, when an intermediate node receives an RREQ packet, it estimates fitness value
𝐹𝑉𝑜 using Equation 3.
𝐹𝑉𝑜 = 𝑚1 ∗ 1/𝑆𝑃 + 𝑚2 ∗ 1/𝑁𝐷𝐼𝑆 + 𝑚3 ∗ 𝑁𝑅𝐸𝑁 (3)

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Figure 2. Route Discovery Operation
Detailed operation of an intermediate node after receiving route request packet has been
mentioned in Figure 3.
2=
13
12
8
15
10
6
7
3
9
5
S
1
4
16
D
14
11
Fitness value is less
than threshold RREQ
RREQ
RREQ
RREQ
RREQ
RREQ RREQ
RREQ
RREQ
RREQ
RREQ
RREQ
RREP
RREP
RREP
RREP
RREP
RREP
RREP
RREP
RREP

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Figure3. Route Request Packet Broadcasting
The technique uses the s and t coordinates to estimate the distance between the sender and
recipient when an intermediate node receives an RREQ packet. Following that, it examines speed
and residual energy of receiving node. Based on these factors, a fitness value 𝐹𝑉𝑜 is calculated
using equation 3. If the estimated 𝐹𝑉𝑜 is less than threshold𝐹𝑉𝑡ℎ, it means the node is not reliable
to participate in routing operation and thus the scheme discards that node by discarding the
packet. If value of 𝐹𝑉𝑜 is above threshold, the node is allowed to become a part of route and thus
forwards the route request packet.
End
Start
Estimates distance NDIS between
sender and receiver using
coordinates positions
Extract node speed Spand
residual energy NREN
Estimate the Fitness Value
FVousing Equation 3
Drop the Packet P Forward the
Packet P
FVo>FVth
Yes
No

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3.3. Local Connectivity Operation
Whenever a node receives a hello packet from a sender, it first examines the sender’s information
in its neighbour table, if the information is not available, the receiving node directly adds the
information such as sender’s ID, expiration time etc. in its neighbour table. If information is
already in the table, the receiving node updates expiration time of existing neighbour only if a
sender has sufficient number of nodes and strong link quality between sender and itself. The
whole sequence of steps performed by a node after receiving hello packet has been mentioned in
the Algorithm 1.
Algorithm 1:Operations performed during receiving Hello packet
1. A node 𝑁𝑜 receives hello packet from the sender𝑆𝐻.
2. Search the sender (𝑟𝑝 → 𝑟𝑝_𝑑𝑠𝑡) information in the neighbour list as follows
3. nb= nb_lookup(𝑟𝑝 → 𝑟𝑝_𝑑𝑠𝑡)
4. If 𝑆𝐻 information is present in the list.
5. Examine current signal strength 𝑆𝑆𝑄and node degree 𝑁𝐷
6. Compare the values of 𝑆𝑆𝑄and 𝑁𝐷against their respective thresholds as follows
7. If ((𝑆𝑆𝑄>𝑆𝑆𝑄𝑇𝐻) && (𝑁𝐷>𝑁𝐷𝑚𝑖𝑛&&𝑁𝐷<𝑁𝐷𝑀𝐴𝑋))
8. Then
9. Update the expiration time of sender in the neighbour table
10. Else
11. Drop the Packet P
When a node receives hello packet from existing sender, it checks the quality of link and number
of nodes in its vicinity. If the sender node has sufficient number of neighbours and good link
quality, the receiving node updates the neighbour table by increasing the expiration time. If the
criterion is not satisfied, the hello packet is dropped and consequently expiration time of the
sender is not updated.
4. PERFORMANCE EVALUATION
In order to comprehensively assess the performance of proposed scheme, several simulation runs
have been conducted under different network environment. This section describes the simulation
parameters considered during implementation and further brief definition of considered
performance metrics has been presented. Finally, results of proposed scheme has been analyzed
and represented through graphs.
4.1. Simulation Environment
The performance of proposed ASTMRS has been evaluated using NS2.35 [21]. Network
simulator is discrete event simulator which is widely used in research area related to networking.
In the proposed work, a total of 60 nodes are dispersed at random over a 900 x 1000 region. The
propagation model is the two-ray ground model [22], [25], whereas the mobility pattern is
determined by the random waypoint mobility model [23-24]. This model is based on two
parameters maximum speed and pause time. Maximum speed of the node in this approach is
considered as 30m/s. Packet size is of 512 bytes. The main simulation parameters taken into
account for implementation are shown in Table 3.

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Table 3. Simulation Parameters
Simulator NS 2.35
Simulation Area 900 x 1000
Traffic Type CBR
Packet Rate 2, 4, 6, 8 and 10 packet/sec
Pause Time 2, 4, 6, 8 and 10 seconds
Node Speed 30 m/s
Queue Type Drop tail
Mobility Model Random Way Point
Antenna Omni Directional
Number of Nodes 60
MAC Layer IEEE 802.11
Propagation Model Two Ray Ground
Initial Energy 50 J
Routing Protocols ASTMRS, AOMDV , AODV
4.2. Performance metrics:
The proposed approach has been evaluated by considering following performance metrics.
4.2.1. Packet Delivery Ratio
It can be defined as the fraction of total amount of packets received by the goal node to the total
number of data packets generated at initiator node.
4.2.2. Throughput
This metric depicts total number of bits received at destination within a certain period of time.
4.2.3. Delay
It is the average amount of time a packet needs to travel from its source to its destination.
4.2.4. Routing Overhead
It is total amount of control packets required to perform whole routing operation. It should be less
used.
4.2.5. Normalized Routing Load
It indicates how many control packets in total are needed to send a single data packet.

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4.3. Simulation Results and Analysis
This part addresses the performance of the proposed ASTMRS and presents the simulated results
received after implementation on varying packet rate and pause time. Network Animator (NAM)
views of proposed approach ASTMRS or snapshots obtained during simulation are shown in
Figure 4 and Figure 5.
Figure 4. Screenshot 1 taken during simulation
Figure 5. Screenshot 2 taken during simulation
Results obtained after simulation have been represented through graphs i.e. from Figure 6 to
Figure 17.

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4.3.1. Packet Delivery Ratio (PDR)
Figure 6 and Figure 7 show performance in terms of PDR on varying packet rate and pause time
respectively.
Figure 6. PDR Vs Packet Rate
Figure7. PDR Vs Pause Time
From the graphs, it is clear that the PDR of the proposed approach ASTMRS is significantly
improved in contrast with AOMDV and AODV. On varying packet rate, it is 15.42% and 17.33%
more as compared to AOMDV and AODV respectively. Similarly while varying pause time, the
PDR of proposed approach has shown 16.23% and 14.60% improvement against AOMDV and
AODV respectively. The algorithm is able to achieve this good result because during route
request broadcasting it considers residual energy, node mobility and distance for estimating

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fitness value of an intermediate node. Therefore, during data packet transmission only efficient
nodes are participating which consequently increases the PDR performance of routing protocol.
4.3.2. Packet Loss Ratio (PLR)
The performance in terms of PLR has been represented in Figure 8 and Figure 9.
Figure 8. PLR Vs Packet Rate
Figure 9. PLR Vs Pause Time
On varying packet rate, PLR of the proposed approach is reduced to 20.44% and 22.12% against
AOMDV and AODV respectively. Similarly, on varying pause time, it is reduced to 31.46% and
29.51% as compared to AOMDV and AODV respectively. This is because, the scheme focuses
on construction of stable route which results in reduction in occurrence of frequent route

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breakage and thus showing overall PLR performance improvement in different network
conditions.
4.3.3. Normalized Routing Load (NRL)
Normalized routing load is one of the important performance metrics. Reduction in NRL
increases channel utilization. The performance in terms of NRL has been evaluated under
different conditions and has been represented in Figure 10 and Figure 11.
Figure 10. NRL Vs Packet Rate
Figure 11. NRL Vs Pause Time
On varying packet rate, it has been observed that the scheme requires 14.22% and 37.10% less
control packets against AOMDV and AODV in transmitting single data packet. Similarly, on
varying pause time, NRL of the proposed approach has been reduced to 16.95% and 28.99%

147
against AOMDV and AODV respectively. This is because; the scheme considers only efficient
nodes to broadcast RREQ packet further. Moreover, during receiving hello packet, it updates its
neighbour table on the basis of node degree and link quality.
4.3.4. Control Overhead (CO)
Performance of the proposed approach ASTMRS in terms of control overhead on varying packet
rate and pause time has been represented in Figure 12 and Figure 13.
Figure 12. CO Vs Packet Rate
Figure 13. CO Vs Pause Time
From the simulation results, it is clear that on varying packet rate, there is 8.76% and 27.30%
reduction in total number of control packets required by ASTMRS as compared to AOMDV and
AODV respectively. Similarly, on varying pause time, total 4.64% and 18.59% of reduction has

148
been seen in required number of control packets against AOMDV and AODV. This is because;
the scheme does not allow inefficient nodes to broadcasts RREQ packet further which results in
overall reduction in control packets.
4.3.5. Throughput
Figure 14 and Figure 15 represent throughput performance of the proposed approach.
Figure 14. Throughput Vs Packet Rate
Figure 15. Throughput Vs Pause Time
From the graphs, it is clear that the proposed approach achieves higher throughput as compared
to existing scheme in different network conditions. On varying packet rate, the ASTMRS
achieves 13.45% and 17.58% more throughput over AOMDV and AODV respectively. On
varying pause time, there is 15.32% and 13.98% increment obtained in throughput performance

149
by the scheme in comparison to existing AOMDV and AODV respectively. This is because, on
receiving hello packet from existing sender, the node updates its neighbour table on the basis of
signal quality and node degree. Consideration of signal quality ensures good amount of data
packet transmission without any loss and ultimately increases overall throughput performance.
4.3.6. End to End Delay
Performance in terms of end to end delay has been represented in Figure 16 and Figure 17 on
varying packet rate and pause time respectively.
Figure 16. End to end delay Vs Packet Rate
Figure 17. End to end delay Vs Pause Time
After simulation, it has been observed that on varying packet rate, the proposed approach
ASTMRS takes 13.63% and 24% less time against AOMDV and AODV. Similarly, on varying

150
pause time, 14.28% and 53.84% reduction is seen in delay as compared to existing AOMDV and
AODV schemes. Results are good because, the proposed approach selects an efficient route
which minimizes unnecessary delay required during re-route discovery process.
5. CONCLUSION
In this work, an adaptive and stable multipath routing scheme has been proposed in which during
route request broadcasting phase, nodes with good fitness values are allowed to further broadcast
RREQ packets. This fitness value is estimated on the basis of factors such as node speed, distance
and residual energy. Each node selects its neighbour nodes on the basis of received signal power
and node degree. The performance of the proposed approach has been evaluated using network
simulator which shows significant improvement in performance specifically in terms of packet
delivery ratio. Other performance metrics such as throughput, normalized routing load and delay
have also shown sufficient improvement.
In future, we will try to incorporate some other factors such as energy efficiency and security to
extend this protocol. Moreover, the scheme can be further implemented in complex environment
such as an IoT system to improve routing efficiency.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
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AUTHORS
PriyankaPandey, received her B. Tech. and M. Tech. degree in Computer Science and
Engineering from Dr. A.P.J. Abdul Kalam Technical University, Lucknow. She has
completed Ph.D. in Computer Science and Engineering from Harcourt Butler Technical
University, Kanpur, India. Her research area is Mobile Ad hoc Network and she has
published research papers in reputed journals and conferences.
RaghurajSingh, received his Ph.D. degree from U. P. Technical University, Lucknow,
India in 2006 and M. S. from BITS, Pilani, India in 1997. He has received B. Tech. in
Computer Science and Engineering from Harcourt Butler Technological Institute, Kanpur,
India in 1990. He is currently working as Professor at Computer Science and Engineering,
Harcourt Butler Technical University, Kanpur, India. His research interest includes
Software Engineering, Human-Computer Interaction and Mobile Ad hoc Networks. Dr.
Singh has published about 182 research papers in International Journals and Conferences.

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