An enhanced energy-efﬁcient routing protocol for wireless sensor network

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 10, No. 5, October 2020, pp. 5462∼5469
ISSN: 2088-8708, DOI: 10.11591/ijece.v10i5.pp5462-5469 Ì 5462
An enhanced energy-efficient routing protocol for wireless
sensor network
Ikram Daanoune, Abdennaceur Baghdad, Abdelhakim Ballouk
Department of Electrical Engineering, Laboratory of Electronics, Energy, Automatics and Data Processing,
Faculty of Sciences and Techniques of Mohammedia, Hassan II University of Casablanca, Morocco
Article Info
Article history:
Received Feb 22, 2020
Revised Apr 25, 2020
Accepted May 7, 2020
Keywords:
Clustering
Current energy
LEACH
Network lifetime
WSN
ABSTRACT
Recent few years, Wireless Sensor Network (WSN) has been an increasingly important
technology that has been applied in almost all domains, even in complex environments
where human activity is impossible. In WSN, various factors are impacted energy
consumption, such as communication protocols, packet data transmission, and limited
battery. So, the lifespan of the WSNs is limited. In this context, energy efficiency is
the factor most attracted by many researchers. In this paper, we proposed a new im-
proved LEACH routing protocol. This proposed protocol based on the current energy
to select cluster-heads, and it uses a root cluster-head with more current energy and
low distance to the sink to gather all data, then sends it to the sink. The simulation
results in MATLAB confirmed that the proposed algorithm performed better than the
conventional LEACH protocol, and increased the network lifetime in WSN.
Copyright c 2020 Insitute of Advanced Engineeering and Science.
All rights reserved.
Corresponding Author:
Ikram Daanoune,
Department of Electrical Engineering,
Laboratory of Electronics, Energy, Automatics and Data Processing (EEA&TI), Hassan II University,
FST Mohammedia-Casablanca (B.P. 146 Mohammedia 20650 Morocco).
Email: daa.ikram@gmail.com
1. INTRODUCTION
In the last few years, WSN recognizes an increased interest through its use in different domains such
as military, medical, environment, etc. [1, 2]. The WSN consists of a large number of low power micro-
sensor nodes deployed in a large space with at least one BS [3]. Every micro-sensor monitors physical or
environmental conditions such as pressure, temperature, humidity, etc. [4] then dispatch the collected data back
to the BS. In WSN, the positions of the nodes are not predetermined, which allows an autonomous organization
of the network [5, 6]. As shown in Figure 1 WSN includes sensor nodes distributed randomly, a BS receives
all data that was collected from the environment, and the user that gathered data through the internet.
Each sensor node in the network has four units: sensing, treatment, wireless transmission and power
unit (generally are batteries) [7] as presented in Figure 2. One of the most important units is the power
unit. Sensor nodes in such an environment are energy-constrained since the batteries can not be recharged or
replaced [3]. Consequently, designing an energy-aware protocol got an interest to prolong the network
lifetime [8]. Thus, energy consumption is the major important factor in most applications where all sensor
nodes are constrained with energy which related to the lifetime of the network. The restricted power of nodes
needs the design of a protocol of communication that conserves energy [9]. The restricted power of nodes
needs the design of a protocol of communication that conserves energy [9]. In this way, many kinds of research
are focused on routing protocols, which is one of the most technologies in WSNs.
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Int J Elec & Comp Eng ISSN: 2088-8708 Ì 5463
Figure 1. WSN architecture
Figure 2. Sensor node units in WSN
In the literature, many routing protocols have designed to arrange the transmission of data from nodes
to the sink [10], and most of them are based on the hierarchical clustering mechanism [11]. The Low Energy
Adaptive Clustering Hierarchical (LEACH) protocol [12] is the famous and the popular hierarchical clustering
routing protocol, which will be described in the next section [13]. In order to prolong the network lifetime
and reduce energy consumption in LEACH, various protocol are proposed, such as DMR [14], MH-LEACH
[15], MHT-LEACH[16], O-LEACH [17], etc. In this work, we are based on the LEACH protocol to develop
a new enhanced LEACH protocol, which improves the energy consumption in WSNs. The present paper aims
to propose energy-efficiency, stability, residual energy, distance, and the multi-hop technique based clustering
routing protocol. This protocol uses these metrics to minimize the energy consumption in the network and
extend the network lifespan in WSNs.
The remaining of the paper is orderly as follows: Section 2 presents the LEACH protocol.
The proposed protocol will be described in section 3. Section 4 covers results and analysis. Finally, the
last section concludes the paper.
2. LEACH (LOW ENERGY ADAPTIVE CLUSTERING HIERARCHY)
LEACH [12] is the most popular and the most famous clustering hierarchical protocol designed for an
energy economy of the network [18]. It uses the clustering technique which divides the network into clusters,
and through clustering mechanism, the nodes organize themselves into a hierarchical organization. Every round
in the LEACH algorithm consists of two main phases: set-up phase and steady phase[19].
In the first phase, CHs are elected and clusters are formed. At the beginning of each round, every
sensor node produces a random value between 0 and 1 [20]. If this value is lower than the probability function
T(n) defined in the equation (1), this node selected as CH. Even if, it becomes a normal node [21].
T(n) =
P
1−P ∗(r mod(1/P )) , n ∈ G
0 else
(1)
Where p concerned the percentage of the number of clusters in the network. r is the current epoch, and G is a
group of nodes that have not been selected as CHs in epoch r.
Afterward, the CHs are selected, they diffuse information to the network. Therefore, each normal node
chooses its CH belongs depending on the strength of the received signal. In the second phase, when clusters are
configured and each node knows its time slot in TDMA. The normal nodes transmit their collected data to their
CHs by their time slots in the TDMA schedule. The TDMA schedule is used to adjust the channel of internal
An enhanced energy-efficient routing protocol for wireless sensor network (Ikram Daanoune)

5464 Ì ISSN: 2088-8708
access in every cluster and reduce the interference between clusters [22]. Therefore, each CH aggregates and
compresses the received data from its members with its own. Thus, the cluster’s information is routed directly
in a single hop to the BS through the CHs.
2.1. Radio energy consumption model
In each node, the transmitter consumes ET x deﬁned in the equation (2) to transfer n bits remote
receiver di meters. There are two different radio models: (1) the free space (fs) that it is adopted when the
distance between the transmitter and the receiver is less than the threshold distance di0; (2) the multi-path (mp)
which it is used when the distance is greater than di0. Then, the receiver consumes ERx described in the (4) to
receive n bit of packet.
ET x(n, di) =
n.Eelec + n. fs.di2
, di < di0
n.Eelec + n. mp.di4
, di >= di0
(2)
di0 =
fs
mp
(3)
ERx(n) = n ∗ Eelec (4)
Where the energy consumption of the transmitter or the receiver is introduced by Eelec, fs and mp present
the energy consumption factor of ampliﬁcation in the free space and the multi-path respectively.
LEACH is designed to decrease energy consumption. It has some advantages, such as every node
can equally divide the charge imposed at CHs to a certain extent because any sensor node that was selected as
a CH in some epoch can not be reselected as a CH yet [23]. Besides, the exploitation of the TDMA avoids
the collision between CHs. Nonetheless, it has some disadvantages as it affects the single-hop while CHs
communicate directly to the sink. Furthermore, for long-distance betwixt CH and the BS can produce more
energy consumption that makes LEACH not apt for large networks. Moreover, the random selection of CHs
leads to not giving all nodes the possibility to become CHs. Thereby, if a node with less current energy is
elected as CH would die rapidly, which affects the network life cycle.
3. THE PROPOSED PROTOCOL
In this document, our contribution is an enhanced LEACH algorithm. The overall purpose of the
proposed protocol is selecting CH according to the residual energy of nodes to avoid the participation of nodes
with less energy as CH. To prevent that all CHs communicate with the BS, it picks out a CH with the greatest
residual energy and the smallest distance to the sink as a parent CH. Then, it uses the multi-hop between CHs
to reach the parent CH as we can see in Figure 3. The multi-hop technique is used to improve the transmission
distance betwixt CHs and the sink. It includes two principal phases as mentioned below. Set-up phase where
we form clusters and we select CH of each cluster. The steady phase that contains three sub-phases.
Figure 3. The proposed protocol architecture
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 5462 – 5469

3.1. Set-up phase
The random selection of CHs in LEACH leads to not giving all nodes the opportunity to become
CHs, also it results in the energy imbalance of sensor nodes. To guarantee the energy balance in the network,
the proposed algorithm selects CH according to the current energy. In every epoch, each node computes its
current energy applying the (5). This node can participate in the CH role if its current energy is superior to the
average current energy.
Ecur = Einit − Econ (5)
Where Econ= ET x + ERx
ET x and ERx are defined respectively in equation (2) and (4) in section 2.1., and Einit is the initial energy
provides to the nodes at the beginning.
Thus, based on [12, 24, 25] we defined a new threshold function as shown in (6).
Th(n) =
P E
1−Pr∗(t %(1/P r)) , n ∈ C , Where PE = Pr ∗ Ecur
Einit
0 else
(6)
Where the percentage of the number of CHs in the network is presented by Pr, t introduces the number of the
current turn, C presents the collections of the nodes that have not yet been CH in the last 1/Pr turns. Einit
represents the initial energy provides the nodes at the beginning whereas Ecur shows the current energy of
nodes at the t turn.
After the first condition, each node takes a random value between 0 and 1. This node will be elected
as a CH at the current turn if this value is inferior to the threshold function Th. On the other hand, it becomes
a normal node. Afterward, CHs broadcast information to the network. Each normal node determines its CH
belongs according to the strength of the received signal from CH.
3.2. Steady phase
3.2.1. TDMA (time divisionmultiple access) schedules
TDMA schedule is created by every CH after cluster configuration according to the distance and the
total number of nodes in each cluster [25, 26]. Each normal node has a TDMA time slot for sending its data to
its CH.
3.2.2. Root cluster head selection
In this phase, the proposed algorithm selects the root CH that has residual energy more than the
average residual energy of CHs and its distance to the sink is less than the average distance between CHs and
the sink, where are depicted in (7) and (8) respectively.
Eaverage =
CH
i=1 Ecur(i)
CH
(7)
daverage =
CH
j=1 d(j)
CH
(8)
Ecur offers the residual energy of CH at the current turn when d indicates the distance between every CH and
the sink.
3.2.3. Data transmission
When all components in the network know their roles in the previous phases, the normal nodes starting
to gather data from the environment then transfer it to their CHs corresponding. Afterward, each CH commu-
nique with the closest CH to reach the root CH applying the multi-hop technique. After receiving information
of all CHs, the root CH aggregates them with its own then sends them directly in a single hop to the sink as
shown in Figure 3.

5466 Ì ISSN: 2088-8708
4. RESULT AND ANALYSIS
In this section, we use simulation to analyze and emulate the performance of the proposed approach.
Simulations are performed in the Matlab 2016b platform. The simulation parameters of our proposed model are
mentioned in Table 1. We deployed randomly 200 nodes in area 200 *200 m2
, the sink was placed at position
(100,250).
Table 1. Parameters value
Parameter Symbol Value
Total number of nodes N 200
Total number of sinks S 1
Area M*N 200 * 200 m2
Initial energy Einit 1 Joule
The sink location (x,y) (100, 250)
The deployment of nodes deployment random
Energy consumed in the Radio module to transmit or receive the signal ET x = ERx 50 nJ/bit
Energy consumed by the ampliﬁer to transmit at a short distance fs 10 pJ/bit/m2
Energy consumed by the ampliﬁer to transmit at a longer distance mp 0.0013 pJ/bit/m4
Data aggregation energy EDA 5 nJ/bit
Packet size n 500 bytes
Number of rounds r 6000
The main purpose of the proposed algorithm is to extend the network lifetime by selecting CHs ac-
cording to the current energy and choosing a root CH. In the beginning, all nodes have the same initial energy
Einit =1 Joule. Each sensor node transmits a 4000 bits data packet per round to its cluster head. The percentage
of the total number of CHs in the network is 5%, while the simulation is repeated with 10% and 20% both for
the proposed algorithm and LEACH.
The simulation result that shows the relative performance of discussed protocols with parameter values
of Table 1, and Pr=20% are presented in Figure 4 (a). It provides dead nodes depending on rounds. Figure 4 (b)
compares the behavior of both LEACH and the proposed protocol for Pr=10%. Figure 5 illustrates the diagram
of comparative analysis of both discussed protocols for Pr=5%, while FND presents the First Die Node, and
HND indicates the Half Node Die. Figure 6 (a), Figure 6 (b), and Figure 7 illustrate the total current energy of
nodes in the network for 20%, 10%, and 5% respectively.
The obtained results from the tree cases exhibit the effectiveness of our method for optimizing the
energy consumption in WSNs. Thereby, it indicates that the proposed algorithm has performed better than the
original LEACH protocol in all cases by balancing the total energy consumption, increasing the stability period
and extending the network lifetime.
(a) (b)
Figure 4. Dead nodes in LEACH and the proposed protocol for 20% and 10%, (a) Dead nodes for 20%, and
(b) Dead nodes for 10%

Figure 5. Dead nodes in LEACH and the proposed protocol for 5%
(a) (b)
Figure 6. Total current energy in LEACH and the proposed protocol, (a) Total current energy for 20%, and
(b) Total current energy for 10%
Figure 7. Total current energy in LEACH and the proposed protocol for 5%
5. CONCLUSION
Presently, the major challenge faced for routing protocol in WSN is making an energy-efﬁcient design.
To solve this problem, it must make the sensor node working for a long period with less consumption of energy.
The sending data and reception present generally the major energy consumption in the network. To meet this
challenge several clustering routing protocols have been developed. This paper proposed a new approach for
hierarchical clustering routing protocol in WSN with energy-saving by the hierarchical and clustering method.
The ﬁrst purpose of the enhanced protocol is balancing the energy consumption of nodes. The second purpose
is prolonging the network lifetime and improving the stability period through: (1) taking into account the

5468 Ì ISSN: 2088-8708
current energy in CH selection, (2) consideration of current energy and the distance to the sink to pick a leader
CH that send aggregated data to the sink after receiving all collected data. The present study was designed to
evaluate the proposed protocol performance against the original LEACH algorithm.
Simulation results in MATLAB confirmed that the proposed algorithm enhances the stability period.
Hence, it extends the network lifespan more than the original LEACH protocol owing to the number of dead
nodes and the total current energy of the network. Thus, it indicates also that the proposed algorithm achieves
better results than the conventional LEACH protocol in all discussed cases.
As future research, it is destined to implement other QoS (Quality of Service).
ACKNOWLEDGEMENTS
The authors of this work would like to appreciate the excellent suggestions of the reviewers and editors
of the IJECE journal to improve the quality of this document.
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BIOGRAPHIES OF AUTHORS
Ikram Daanoune is born on December 29, 1993, in Beni Mellal, Morocco. She obtained her license
degree in electronic engineering and telecommunications, from Faculty of Sciences & Techniques
(FST) of Beni Mellal, Sultan Moulay Slimane University, in 2015, and an engineering diploma on
electrical & telecommunications at FST at Mohammedia, Hassan II University, in 2018. Presently,
she is a Ph.D. student, nominee in the Electronics, Energy, Automatic and Information Processing
(EEA&TI) laboratory at FST Mohammedia, Hassan II University Casablanca. Her study interests
include the development and simulation of classical and computational intelligence routing protocols
to optimize energy consumption in Wireless Sensor Network.
Abdennaceur Baghdad is a doctoral holder in Electronics from Lille University France in 1992.
Presently, He is a university professor with PES grade at FST Mohammedia, Hassan II University
Casablanca-Morocco whither he educates the hyper-frequencies, electronic engineering, antenna, and
systems of telecommunication. He is a participant of the EEA&TI laboratory at Hassan II University.
His researches focused on optical communication, electronic and embedded systems, telecommuni-
cation systems and information technology. He oversees and he co-supervises many doctoral theses.
He is a member of the organizing committees of several international congresses in the same research
area.
Abdelhakim Ballouk is a doctoral holder in Electronics from Bordeaux University France in 1992,
in the automatic domain. Presently, He is a university professor with PES grade at the FST Moham-
media, Hassan II University Casablanca-Morocco where he educates regulation & digital control, and
linear & non-linear automatic. He is a participant of the EEA&TI laboratory at Hassan II University.
He oversees and he co-supervises many doctoral theses. His researches concentrated on Automatic
(robust commands, predictive controls, etc.). His researches focused also in Telecommunication sys-
tems (Antenna, wireless sensor network, etc.).

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