AN IMPROVED ROUTING PROTOCOL SCHEME IN ADHOC NETWORKS

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International Journal of Advanced Research in Engineering and Technology (IJARET)
Volume 10, Issue 2, March-April 2019, pp. 254-262. Article ID: IJARET_10_02_025
Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=02
ISSN Print: 0976-6480 and ISSN Online: 0976-6499
© IAEME Publication
AN IMPROVED ROUTING PROTOCOL
SCHEME IN ADHOC NETWORKS
Syeda Kausar Fatima
Associate Prof, Shadaan College of Engineering, Prof., DCET, Hyderabad, Principal
NSAKCET, research Scholar JNTUH, India.
Dr. Syeda Gauhar Fatima
Dr. Syed Abdul Sattar
Syed Mohd Ali
ABSTRACT
Nowadays, with the rapid development of science and technology and the ever-
increasing demand in every field, wireless sensor networks are emerging as a necessary
scientific achievement to meet the demand of human in modern society. The wireless
sensor network (WSN) is designed to help us not lose too much energy, workforce, avoid
danger and they bring high efficiency to work. Various routing protocols are being used
to increase the energy efficiency of the network, with two distinct types of protocols,
homogenous and heterogeneous. In these two protocols, the SEP (Stable Election
Protocol) is one of the most effective heterogeneous protocols which increase the
stability of the network. In this paper, we propose an approaching the εFCM algorithm
in clustering the SEP protocol which makes the WSN network more energy efficient.
The simulation results showed that the SEP-εFCM proposed protocol performed better
than the conventional SEP protocol
Keywords: Wireless sensor network (WSN), Insensitive Fuzzy C-Means, Stable
Election Protocol (SEP), SEP Insensitive Fuzzy C-Means.
Cite this Article: Syeda Kausar Fatima, Dr. Syeda Gauhar Fatima Dr. Syed Abdul
Sattar and Syed Mohd Ali, An Improved Routing Protocol Scheme in Adhoc Networks,
International Journal of Advanced Research in Engineering and Technology, 10(2),
2019, pp. 254-262.
http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=2

Syeda Kausar Fatima, Dr. Syeda Gauhar Fatima Dr. Syed Abdul Sattar and Syed Mohd Ali
1. INTRODUCTION
The WSN is a network of interconnected sensor nodes. Sensor nodes are designed compactly
and low cost. The nodes are responsible for sensing ambient conditions such as temperature,
sound, vibration, humidity, pressure, etc. Sensor nodes send their sensed data to the aggregation
node and transmit data to Sink (transceiver). As shown in Figure 1, Sink is transmitted over the
internet or satellite to the user. In this process, we see that the CH (Cluster Head) not only listen
to the signals from the nodes not also synthesize data, then transmit data on Sink so that more
energy is consumed, so the routing, specifying the path of this data stream is very important.
Figure 1 The basic structure of wireless sensor networks
The routing protocols are divided into two types that are homogeneous and heterogeneous.
Homogeneous routing protocols are nodes with the same energy level as the protocols: LEACH,
TEEN, HEED, PEGASIS, APTEEN. The heterogeneous protocol is a protocol where nodes
have different energy levels and are divided into two node types: The Advance node and the
Normal node. In that, the Advance node has more energy and the probability of becoming a
node is more than the remaining node. Popular protocols in this type of protocol are SEP [1-5],
DEEC, EDEEC. SEP protocol consider the energy levels in the CH selection process and
improves the stability of the hierarchical clustering process using characteristic parameters of
heterogeneity, adding energy between the advance node and the normal node. In order to
prolong the stabilization time, SEP strives to maintain limited energy consumption. The
advance nodes will become CH more than normal nodes and will be powered more than normal
nodes. However, the selection of Cluster Head in the SEP protocol has a disadvantage which
from the two types of node Advance node and Normal node is not flexible, therefore, that
remote nodes will die first. To solve this problem, we conducted our research about SEP and
evaluated some well-known clustering algorithms such as K-Means, Fuzzy CMeans,
Insensitive Fuzzy C-Means in WSN clustering. Based on the learning theory, we propose a new
approach which combines the Insensitive Fuzzy C-Means algorithm into the SEP protocol
which can make the WSN network more energy efficient. Additionally, we used Matlab to
simulate for the new algorithm, for 140 nodes in a network 500x500, with uneven energy
between nodes to show unequal influence among nodes in the network. 10% of the nodes have
1 Joule energy and 90% of nodes have 0.5 Joules energy. The position of the sink is set at
(250,250) and the length of each message is 500bytes. The simulation results show that the
proposed SEP-εFCM protocol performed better than the conventional SEP protocol.
Our paper consists of five parts: Part 1 is introduction, Part 2 shows the related works, Part
3 proposal, Part 4 simulation results and Final Part is the conclusion.
2. RELATED WORK
If the LEACH was Malik M.et al. [6] gave as a basic protocol for routing and values that are
effective for WSN networks, Smaragdakis has introduced a revolutionary SEP routing

An Improved Routing Protocol Scheme in Adhoc Networks
protocol. SEP is a heterogeneous routing protocol and has proven to be more effective than
the LEACH protocol. In SEP protocol, the node sensors are divided into two types of nodes:
the advance node and the normal node in which the advance node is designed to have a higher
energy level and the probability becomes CH node than the normal node. As shown in Figure
2
Figure 2 Flow chart of CH Selection in SEP protocol
Where:
➢ G’: Normal node does not become CH.
➢ T (S’) is the threshold applied to normal node.
➢ G”: advanced node does not become CH.
➢ T(S”) is the threshold applied to advanced node.
If the K-Means algorithm [5] is a well-defined clustering algorithm, it means that one node
belongs only to one cluster, which is only suitable for discovering high density and isolated
clusters and must define the boundary. However, in practice when deploying WSN, the
boundary between clusters may be blurry, clusters may overlap, meaning that some nodes
belong to different clusters. So, with this case, using the K-means algorithm will limit the
functionality of the wireless sensor network, so the Fuzzy c-means (FCM) algorithm [7-9] was
born to solve this problem. FCM is a fuzzy clustering algorithm developed by Dunn in 1973
and later improved by Bezděk in 1981. This technique divides a set of n-vector data objects X
= {x1, ..., xn} ϵ Rs into the fuzzy groups which are based on the minimization of the objective
function to measure the quality of the partition and find the cluster centers in each cluster, so
that the cost of the nonsimilarity measure is minimal.

By 1998 Vapnick proposed using the parameter ε is called a noise-sensitive parameter to
resolve high-density clusters that overlap, where one node is not only attached to a cluster but
can belong to one cluster or many different clusters. Since then, εFCM[10-14] has always been
a top choice for fuzzy clustering.
In this article the simulated results show that the selection of CH node by εFCM algorithm
reduces the energy consumption of the WSN.
3. PROPOSED ALGORITHM
Heterogeneous protocol SEP has been proven by Smaragdakis's to provide stability and longer
lifetimes than unified protocols. However, they still contain a number of limitations, including
limited clustering for high node density clusters and complex multi-dimensional distribution,
clustering that leads to uneven clusters. (Less node clusters and multiple node clusters) that
cause network load balancing.
In this paper, we propose using the εFCM algorithm to select CH nodes for the SEP
protocol, and selecting this node initially gives priority to the nodal node to take advantage of
this additional energy source as CH Node to create the most stable time for the network. After
the advance nodes consume the remaining energy and energy equal to the normal node, then
εFCM will proceed to select CH node over the entire network, preferring that node which has
more energy will be made CH node. The target function of the εFCM algorithm is defined as
follows:
∑ ∑ ‖ , ‖ (1)
Where ‖ , ‖ = ∑, is non-sensitive to noise are Vapnick proposed in 1998 as
follows:
The steps of the εFCM algorithm:
Input: The number of clusters c and the parameter m, ε for the objective function J;
Output: The cluster data so that the objective function (1) reaches the minimum value;
Begin 1. Input parameter c (1∞) and ≥ 0;

1. Repeat
2. J: =j+1;
3. Calculate fuzzy partition matrix U(j)
according to the formula (2);
4. Update center clusters V(j)(j)
= [ 5,T5, … …, 5] according to the
5. Until V 5W − 5 X ≤ Y; formula (3) and U
6. Demonstrate result of clusters;
7. End
The SEP protocol [10-12] takes into account the energy level in the main node selection
process. SEP improves the stability of the hierarchical clustering process using the
characteristic parameters of the heterogeneous, additional energy between the advanced node
and the normal node. To prolong the stabilization time, SEP strives to maintain its energy
consumption limit. Advanced nodes become CH more often than normal nodes. Advanced
nodes usually have more power than the normal node. The total energy of the system varies.
Assuming Eo is the initial energy of the normal node, the energy of the advanced node is set to
Eo * (1 + α). The total energy needed to set up (new) is equivalent to n * (1-m) * Eo + n * m *
Eo (1 + α) = n * Eo (1 + αm). Thus, the total energy of the system is increased (1 + αm) times.
We can increase the stability of the sensor network (1 + αm) times.
The probability that the normal node becomes CH is 1 and the advanced node becomes CH
is 1 + α. If the threshold T (n) is set to normal and the advanced node differs in that the normal
node of G becomes the first cluster once times and the advanced node of G becomes the first
cluster 1 + α times. Pnrm is defined as the probability of selecting weights for normal nodes
and the probability of selecting weights for advanced nodes. So, the weight probabilities for
normal node and advanced node nodes are:
Pnrm =W]
W]
Z [ Z [ α
Padv = (1+)
The function T (n) is replaced by Popt by the weight probability to obtain the selection
threshold CH in each round.
The threshold for normal node: T(Snrm) =another case
Where:
➢ r: current loop
➢ G’: Normal node does not become CH with 1 / Pnrm last cycle per phase.
➢ T (Snrm) is the threshold applied to n (1 - m) normal node. This ensures that each
normal node becomes CH once time in Z[ (1+αm) per phase and that is the average
of the normal nodes becoming CH each round is n (1-m) * Pnrm
-
The Threshold for advanced node
T(Sadv) = ^ Z@’r y
Where
G”: advanced node does not become CH CH in Z@’rlast cycle per phase.
T(Sadv) is the threshold applied to n*m advanced node.

We consider to this phase as the secondary stage. Each stage has 1 + α sub-stage and the
advanced node becomes CH exactly 1 + α times in phase. The average of advanced node
becomes CH for per cycle which has n * Padv.
So, the average number of CHs per round is n * (1-m) * Pnrm + n * m * Padv = n * Popt.
This is the desired number of CHs in per phase.
4. SIMULATION AND EVALUATION
In this paper, we use Matlab software (R2016a) to perform simulations, for 140 nodes which
have fixed coordinates in a network 500x500, with uneven energy between nodes to show
unequal influence among nodes in the network. 10% of nodes have 1 Joules energy (a = 1, Popt
= 0.1), 90% of nodes have 0.5 Joules energy. The position of the sink is set at (250,250), the
length of each message is 500bytes, the amplification coefficient efs = 10pJ / bit / m2 and e mp
= 0.0013pJ / bit / m4, the maximum number of loops is 6000.The input parameters are fixed,
the author will in turn put these parameters into running SEP protocol and proposed protocol
SEP_ εFCM. Then we compare between protocol combining SEP and SEP_ εFCM protocol
based on metrics such as: number of live nodes, number of Dead nodes and the remaining
energy of nodes.
PARAMETERS VALUE
Network size 500x500
BS (250,250)
Rounds 6000
Iteration 200
fs 10pJ/bit/m2
mp 0.0013pJ/bit/m4
EDA 5 nJ/bit/packet
E0 0.5J
N 140
A 1
K 15
Popt 0.1
4.1. RESULTS AFTER THE FIRST 1200 ROUNDS
In Figure 3, on the SEP protocol we see that after 1200 cycles the dead node has appeared,
while in the SEP_ εFCM association we see the result after 1200 cycles in Figure 4 shows no
dead node.

Figure 3 SEP protocol after 1200 rounds
Figure 4 SEP_ εFCM association protocol after 1200 rounds
4.2. NUMBER OF LIVE NODES
Figure 5 show the number of alive during the network lifetime. After 800 cycles, SEP appears
as the first dead node, after 2790 SEP_ εFCM loops appear. Proposed protocol is higher 21%
SEP of the number of rounds that the last node dies.
Therefore, the living nodes in the SEP_ εFCM combination protocol have more live nodes
than the SEP protocol. After a few initial rounds are unstable, but then the number of live nodes
starts to increase, this proves that the SEP_ εFCM combination protocol consumes more
efficient energy than the SEP protocol. Results for the SEP_ εFCM combination protocol have
improved more live nodes than the SEP protocol.

Figure 5 Alive Node comparison between the SEP protocol and SEP_ εFCM protocol
4.3. REMAINING ENERGY
In Figure 6 we find that, after 4985 round runs, the node in SEP died out and 5150 SEP_ εFCM
nodes. Proposed protocol is higher 3.3% SEP. The result shows that the Remaining energy of
the SEP_ εFCM matching protocol is greater than that of the SEP protocol. The results of the
SEP_ εFCM combination protocol have improved the residual energy of the SEP protocol.
Figure 6 Remaining energy comparison between the SEP protocol and SEP_ εFCM protocol
5. CONCLUSIONS
Designing WSN network with well-functioning, flexible and easy-to-deploy for real-world
applications is fraught with many difficulties, with the biggest difficulty now being the
limited node power and hard to reload. Therefore, utilizing available power resources on
nodes effectively reduces the energy consumption that extends the life of the entire network,
which increases the life of the network.We researched the routing protocols to propose the
new algorithm using the εFCM fuzzy algorithm in the selection of CH node into the SEP
protocol. Simulation results suggest that our improvement has lower power consumption and

longer network lifetime than the3.3% SEPprotocol. This helps the network extend the
lifespan.
REFERENCES
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