Battery life is a key issue for an elongated life in WSN. Clustering of nodes is done to achieve the energy conservation in LEACH algorithm. The main objectives of clustering are equal distribution of energy and equal distribution of nodes in space so that less energy is consumed and early deaths of nodes can be delayed. In LEACH both of these objectives can’t be achieved. Further Max-Energy LEACH is able to achieve energy equi-distribution but not the space equi-distribution because CH can be selected from one region only leading to large energy consumption by nodes to send data to CHs. The clustering algorithm while doing its work should pay attention toward the number of nodes a cluster is having. If we can equi-distribute all nodes to cluster then we assume that it may lead to better energy efficiency. This paper discusses the recent developments in WSN in this direction.

1. IJSRD - International Journal for Scientific Research & Development| Vol. 2, Issue 07, 2014 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 594
Recent Developments in Routing Algorithms for Achieving Elongated
Life in WSN
Richa Budhiraja1
Saranjeet Singh2
1,2
Department of Electronics Engineering
Abstract— Battery life is a key issue for an elongated life in
WSN. Clustering of nodes is done to achieve the energy
conservation in LEACH algorithm. The main objectives of
clustering are equal distribution of energy and equal
distribution of nodes in space so that less energy is
consumed and early deaths of nodes can be delayed. In
LEACH both of these objectives can’t be achieved. Further
Max-Energy LEACH is able to achieve energy equi-
distribution but not the space equi-distribution because CH
can be selected from one region only leading to large energy
consumption by nodes to send data to CHs. The clustering
algorithm while doing its work should pay attention toward
the number of nodes a cluster is having. If we can equi-
distribute all nodes to cluster then we assume that it may
lead to better energy efficiency. This paper discusses the
recent developments in WSN in this direction.
Keywords: WSN, LEACH, CH, GCEDA
I. INTRODUCTION
The protocol plays important role, which can minimize the
delay while offering high energy efficiency and long span of
network lifetime. LEACH (Low Energy Adaptive Clustering
Hierarchy) and PEGASIS (Power-Efficient Gathering in
Sensor Information System) are such typical hierarchical-
based routing protocols.LEACH protocol is achieved base
on many assumptions, such as assuming that all nodes in the
network have the same structure and start with the same
energy, and nodes can be aware of their residual energy, and
so on. The LEACH improves a lot as compared to direct
transmission of data but there remain several problems in
this algorithm. Because the election strategy of cluster head
is random, it may lead to misdistribution of cluster head and
imbalanced clusters. Thus cluster head load is not balanced
consequently this may lead to high energy consumption and
early death of individual cluster head.Clustering is the main
factor responsible for the energy conservation in LEACH
algorithm. Main objectives of clustering are equal
distribution of energy and equal distribution of nodes in
space so that less energy is consumed and early deaths of
nodes can be delayed. In LEACH both of these objectives
can’t be achieved. Further to achieve these objectives a
Max-Energy LEACH was proposed, in which CHs are
chosen based on residual energy instead of random
selection. Max-Energy LEACH is able to achieve energy
equi-distribution but not space equi-distribution because CH
can be selected from one region only leading to large energy
consumption by nodes to send data to CHs. The clustering
algorithm while doing its work should pay attention toward
the number of nodes a cluster is having. If we can equi-
distribute all nodes to cluster then we assume that it may
lead to better energy efficiency. In [28] and [29], the cluster
head is elected by obtaining the energy consumption in
Intra-cluster and Inter-cluster, and then we could find the
average energy of overall network. Finally, we proposed the
re-electing cluster heads method for balancing local clusters.
This method uses the information which the cluster heads
have. This information is the number of member nodes and
distance between the member nodes and the cluster head.
II. RELATED WORKS
Recently there has been increased interest in studying
energy-efficient clustering algorithms in the context of both
ad hoc and sensor networks. The main aim of clustering
protocols in ad hoc networks is to generate the minimum
number of clusters while maintaining network connectivity.
In these algorithms the election of CHs is based mainly on
the identity of nodes, the degree of connectivity or the
connected dominating set. These techniques are discussed in
depth in. In the case of WSNs, the main objective of
clustering protocols is to minimize energy consumption by
the network in order to extend the network lifetime. The
surveys dealing with WSN clustering protocols can be found
in [11].This is called balanced energy based clustering. The
next section discussesthe recent developments in the field of
clustering for better routing algorithms in WSN.
Authors in [10] presented a Simulation of
Improved Routing Protocols LEACH of Wireless Sensor
Network which introduces compression ratio and takes the
surplus energy of nodes as a pivotal factor in cluster-head
node selection. It proposes an improved algorithm of the
optimal number of cluster heads with the minimum energy
consumption and provides the computational formula for
obtaining the optimal number of cluster heads, and proves
by mathematical reasoning and by simulation experiments.
The improved algorithm is a success in terms of balancing
energy consumption of the system and prolonging the
network life cycle, thus leaving the network more of
robustness.Dnyaneshwaret al [18] presented Grouping of
Clusters for Efficient Data Aggregation (GCEDA) in
Wireless Sensor Network. wheredata aggregation at the sink
by individual node causes flooding of the data which results
in maximum energy consumption. To minimize this
problem they proposed and evaluate the group based data
aggregation method, where grouping of nodes based on
available data and correlation in the intra-cluster and
grouping of cluster heads at the network level help to reduce
the energy consumption. In addition, proposed method uses
additive and divisible data aggregation function at cluster
head (CH) as in-network processing to reduce energy
consumption. Cluster head transmits aggregated information
to remote sink and cluster head nodes transmit data to CH.
Cluster based data aggregation improves the scalability and
reduces the energy consumption in aggregation of data.
Result shows, grouping of the number of clusters together in
the second level of aggregation reduces energy consumption
to 14.94 % (with a group of three clusters heads). Also, if
the network diameter increases, then energy consumption
increases approximately by 1%. This causes due to the same
number of optimal cluster heads with an increase in the

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distance between them. Optimal number of cluster head has
a direct effect on energy consumption. Reduced energy
consumption in transmission of aggregated data indicates
benefit of the increase in a lifetime of the network.
Yunjie et al [16] proposed an improved routing
algorithm LEACH-KED to improve the performance of the
network by the optimal number of cluster head and the
mechanism of cluster head selection, making node energy
consumption reduced and extending the network life cycle.
The simulation results show that LEACH-KED have
obvious advantages over LEACH and LEACH-C agreement
in overall performance.Zhao et al [38] in their research
article, presented an overview of the original LEACH and
LEACH-C protocols and a new version of hierarchical
protocol is proposed. The proposed protocol obtains energy
efficiency by the modification to choosing of cluster heads
formula and the steady-state phase. The modification to the
choosing of cluster heads formula makes the sensor nodes
which have more energy and play less role in making the
CH or VCH have more opportunity to act as CHs in the
coming round. So the total energy of the whole network has
more even distribution among different nodes. The
introduction of VCH makes the frequency of re-clustering
more lowly and prolongs the time of being in steady-state
phase; thus the energy used for calculating the formula on
every nodes reduces. Through the modification and
simulation, we can conclude that our proposed protocol
performs better than LEACH and LEACH-C protocols.
EbinDeni Raj [23] suggested new protocol
EDRLEACH based on clustering with maximum lifetime
for wireless sensor networks. It improves LEACH by using
a very equally distributed cluster and decreasing the unequal
topology of the clusters. The new network protocol can be
built on the shortcomings of Leach to try and rectify them.
The applications of the new algorithm are immense as the
life period has increased considerably.Li et al [15] presented
the LEACH algorithm based considering the residual energy
of each node in each round inconsistencies, selected path is
not the most energy-efficient path and proposed the concept
of the energy threshold and distance factor, energy threshold
and distance factors to determine the preferred cluster head
collection selected on the basis of the cluster head node.
Optimization algorithm selected by the head of such a
cluster, and extends the network lifetime, improve node
energy utilization.
Huo Shi et al [24] presented an Energy-Efficiency
Optimized LEACH-C for Wireless Sensor Networks.
LEACH-C is a cluster algorithm in which cluster heads are
randomly selected from the nodes with energy above the
average, and the simulated annealing algorithm is utilized to
find the optimal solution with better position to reduce the
energy loss of cluster heads. It provided an energy-
efficiency optimized LEACH-C through a modified model
of the cluster head energy consumption considering
retransmission and acknowledgment, and the secondary
simulated annealing algorithm is utilized to get a better
solution. An appraisal system which focuses on energy-
efficiency is created to judge whether the performance of
optimized LEACH-C is better. This paper presents an
energy-efficiency Optimized LEACH-C. First, it selects a
group of cluster heads using LEACH-C. Next, taking
retransmission and acknowledgment into consideration, it
creates a model of cluster head energy consumption. It will
calculate the quadratic sum of the distances from each
cluster head to its member nodes in the optimal solution.
Finally, the largest energy consumption for a single cluster
head in the next round will be estimated, and all nodes with
residual energy larger than the calculated consumption will
be taken to a new round of simulated annealing to find a
better solution. Thus, loss of the cluster head for each round
can be minimized, and the WSN lifetime can be extended
ultimately. Simulation results show that the Optimized
LEACH-C can minimize the total energy consumption of
the whole network to achieve energy-saving, and the
lifetime of the network is prolonged.
Further a paper [25] presented a new version of
LEACH protocol called VLEACH which aims to reduce
energy consumption within the wireless network. The
proposed protocol uses simulation model. The simulation
tool used for the purpose is MATLAB. Simulation results
show that the New Improved V LEACH routing protocol
reduces energy consumption and increases the total lifetime
of the WSN compared to the LEACH protocol.Stefanoset al
[27] presented ECHERP, an energy efficient protocol for
WSNs. ECHERP considers the current and the estimated
future residual energy of the nodes, along with the number
of rounds, that can be cluster heads in order to maximize the
network lifetime. The protocol computes the energy
consumed using the Gaussian elimination algorithm in order
to minimize the overall network energy consumption at
every single round. Therefore, it elects as a cluster head the
node that minimizes the total energy consumption in the
cluster and not the node with the higher energy left, as in
many other protocols. ECHERP also adopts a multi-hop
routing scheme to transfer fused data to the base station.
Therefore, ECHERP achieves substantial energy efficiency,
as shown through simulation tests, which indicates that
ECHERP outperforms several previously proposed
protocols, namely LEACH, PEGASIS and BCDCP. In
future work, ECHERP can be further enhanced by taking
into consideration metrics related to QoS and time
constraints.
Anitha andKamalakkannan [3] presented Energy
Efficient Cluster Head Selection Algorithm in Mobile
Wireless Sensor Networks. In Wireless sensor networks,
existing energy efficient routing algorithms assumed that the
sensor nodes are stationary. Some of the applications in
WSN must combine with both mobile sensor nodes and
fixed sensor nodes in the same networks. When mobility is
functioned there should be performance degradation.
Because these nodes are equipped with a lesser amount of
memory, restricted battery power, little computation
capability, and small range of communication. So there is a
need for energy efficient routing protocol to forward the
incoming packet. Ahlawat and Malik [1] presented an
extended vice-cluster selection approach to improve v leach
protocol in WSN. The paper presents a new version of leach
protocol called Improved VLEACH which aims to increase
network life time. In this paper we first completely analyzed
the typical clustering Routing Protocol-LEACH and its
deficiencies and proposed improved v-leach. The work to be
done in improved v-leach protocol on selection of vice
cluster head. The Vice Cluster head is that alternate head
that will work only when the cluster head will die. The

3. Recent Developments in Routing Algorithms for Achieving Elongated Life in WSN
(IJSRD/Vol. 2/Issue 07/2014/135)
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process of vice cluster head selection on the basis of three
factors i.e. Minimum distance, maximum residual energy,
and minimum energy. The proposed approach will improve
the network life as never the cluster head will die. As a
cluster head will die it will be replaced by it’s vice Cluster
head. After a number of simulations, it was found that the
new version of improved v- LEACH outperforms the
original version of leach protocol by increasing the network
life time 49.37%.
Park et al [20] presented A Novel Cluster Head
Selection Method based on K-Means Algorithm for Energy
Efficient Wireless Sensor Network. In this paper we propose
an efficient cluster head selection method using K-means
algorithm to maximize the energy efficiency of wireless
sensor network. It is based on the concept of finding the
cluster head minimizing the sum of Euclidean distances
between the head and member nodes. . This is mainly due to
effective selection of the CHs such that the distances
between the CH and the member nodes become minimal.
We have proposed to group the sensor nodes into several
clusters by using K-means algorithm in this paper. Authors
in [8] presented an optimal Algorithm based on gridding and
clustering for decrease energy consumption in WSN. This
proposed approach emphasizes on increasing network
lifetime which reduces data redundancy via clustering
algorithms and gridding. The proposed algorithm was
derived from clustering and the grid- based routing
protocols. It follows the clustering routing protocol in data
gathering and tries to optimize energy consumption with
identifying sensors that sense same data besides integrating
gridding and clustering protocols.Messai[13] presented a
new clustering scheme for wireless sensor networks. In this
paper, it proposed a novel Energy-Aware Clustering
algorithm (EAC) for prolong the wireless sensor network
lifetime. EAC achieves a good performance in terms of
lifetime by balancing the energy load among all the sensor
nodes in the network. In EAC scheme, the cluster heads and
their members are selected according to two parameters: the
remaining residual energy and the distance of member’s
sensor nodes to theirs cluster heads sensor nodes. This
parameters conduct to select the appropriate sensor nodes as
cluster heads and nearest sensor nodes as members. By this
way the lifetime of WSNs is extended.EAC introduces the
energy factor for cluster head selection and distance factor
for non-cluster heads to select its cluster head. Simulation
results show that the proposed algorithm increases the
network lifetime in compare of the well-known LEACH
protocol.
Chen et al [6] presented A Low-Energy Adaptive
Clustering Hierarchy Architecture with an Intersection-
based Coverage Algorithm in Wireless Sensor Networks. To
extend the system lifetime, it used the intersection-based
coverage algorithm (IBCA) to address lifetime; its
introduction causes sensor nodes to enter sleep mode when
not operating. This algorithm can achieve reduced energy
consumption in transmission. And then combine IBCA with
Low-energy adaptive clustering hierarchy (LEACH)
architecture to improve system performance. Simulation
results show that the performance of the proposed LEACH
architecture with IBCA perform better than LEACH
architecture with phase-based coverage algorithm (PBCA)
in terms of energy consumption, number of surviving nodes
and sensing areas. By using IBCA, the WSN’s sensor nodes
are classified into two types, i.e., active nodes, which
responsible for detecting data, and the sleep mode nodes,
which remain idle. Therefore, the entire system requires less
live sensor nodes to cover a sensor field. The nodes to enter
sleep mode are determined using IBCA, and do not perform
any functions, which reduces energy consumption. Finally,
the system is constructed by only active nodes, further
reducing the energy consumption of the WSN. On the other
hand, IBCA selected a greater number of redundant nodes
than did PBCA, the main reason being that, with IBCA, a
greater number of sensor nodes can be used for judgment.
For this reason, the application of IBCA to the LEACH
architecture improves the system lifetime.
Tyagi and Gupta [21] presented EHE-LEACH:
Enhanced heterogeneous LEACH protocol for lifetime
enhancement of wireless SNs. As SNs are battery operated,
so efficient utilization of energy during various operations in
WSNs is one of the major issues which requires special
attention. It has been observed in literature that Hierarchical
clustering and the node heterogeneity are the two parameters
by which the lifetime of WSNs can be enhanced. Keeping in
view of the above, in this paper, Enhanced Heterogeneous
LEACH (EHE-LEACH) Protocol is proposed for Lifetime
Enhancement of SNs. A fixed distance based threshold is
used for the bifurcation of direct communication and cluster
based communication in the proposed scheme. SNs near to
the BS communicate directly and those which are far away
from the BS use cluster based communication. To evaluate
the performance of the proposed scheme two key parameters
known as: Half Nodes Alive (HNA) and Last Node Alive
(LNA) are selected. By selecting the distance based
threshold with the ratio of 1:9 between direct
communication and cluster based communication it has been
observed that EHE-LEACH has better network lifetime with
respect to various parameters in comparison to the other
well-known proposals such as LEACH.
Mahmood et al 17] presented modified LEACH
(MODLEACH): A Variant of LEACH for WSNs. In this
work, MODLEACH is proposed, a new variant of LEACH
that can further be utilized in other clustering routing
protocols for better efficiency. MODLEACH tends to
minimize network energy consumption by efficient cluster
head replacement after very first round and dual transmitting
power levels for intra cluster and cluster head to base station
communication. In MODLEACH, a cluster head will only
be replaced when its energy falls below certain threshold
minimizing routing load of protocol. Hence, cluster head
replacement procedure involves residual energy of cluster
head at the start of each round. Further, soft and hard
thresholds are implemented on MODLEACH to give a
comparison on performances of these protocols considering
throughput and energy utilization. Ahmed and Qazi [2]
presented Cluster Head Selection Algorithm for Mobile
Wireless Sensor Networks. In this paper Basic LEACH
protocol has been modified with our proposed LEACH-
MAE (LEACH Mobile Average Energy based) protocol to
overcome its shortcomings to support mobility along with
the new average energy based Cluster Head selection
technique. Simulation in NS2 shows that proposed
algorithm improves network life time up to 25 % as well as
helps to maintain the equal distribution of energy resource

4. Recent Developments in Routing Algorithms for Achieving Elongated Life in WSN
(IJSRD/Vol. 2/Issue 07/2014/135)
All rights reserved by www.ijsrd.com 597
among the sensor nodes. It presents the performance
analysis of the modified LEACH algorithm i.e. LEACH-
MAE for mobile wireless sensor network. Here energy
resource and minimum link breakage have been focused.
Comparison simulation result on the varying speed of sensor
nodes proved that maximum link maintenance and less
energy consumption improves the network lifetime and
prevents data loss. Network lifetime would be degraded if
there is random selection of CHs. Also as the speed of
sensor nodes increases there are more chances of frequent
link breakage which lead to quick power failure. Hence in
the proposed algorithm it has been observed from the above
results that even if the mobility is high there is minimum
data loss as compared to LEACH-M as well as the network
life time is greater with less energy dissipation. It is
concluded that by using some mobility pattern for WSNs,
energy dissipation can be minimized and network lifetime
can be optimized.Tripathi et al [22] presented Energy
Efficient Clustered Routing for Wireless Sensor Network.
This paper introduces a novel cluster based routing protocol
in which, the base station finds the highest energy node
among the cluster and mark it as a cluster head for the
current time. Thus in the proposed system the energy
consumption of various nodes becomes more uniform as
compared to LEACHC. The simulation results indicate that
the proposed method leads to efficient transmission of data
packets with less energy and therefore increases the network
longevity as compared to LEACH-C and LEACH.
A new class of algorithms, inspired by swarm
intelligence, is currently being developed that can
potentially solve numerous problems of modern WSNs
requirement. The latest work in this area is described below.
Latiff and others [14] presented an energy-aware cluster
based protocol for wireless sensor networks using particle
swarm optimization (PSO) algorithm. They have defined a
new cost function that takes into account the maximum
distance between the non-cluster head node and its cluster
head, and the remaining energy of cluster head candidates in
the cluster head selection algorithm. Results from the
simulations indicate that the proposed protocol using PSO
algorithm gives a higher network lifetime and delivers more
data to the base station compared to LEACH and LEACH-
C. Furthermore, the proposed protocol produces better
clustering by evenly allocating the cluster heads throughout
the sensor network area.Chakraborty et al [5] presented An
Energy Efficient Scheme for Data Gathering in Wireless
Sensor Networks Using Particle Swarm Optimization.
Thisnovel data gathering protocol was proposed for
enhancing the network lifetime by optimizing energy
dissipation in the nodes. To achieve the design objective it
uses applied particle swarm optimization (PSO) with
Simulated Annealing to form a sub-optimal data gathering
chain and devised a method for selecting an efficient leader
for communicating to the base station.
Singh andLobiyal [26] presented Particle Swarm
Optimization (PSO), a technique which is known for its easy
implementation and fast convergence. In this paper, it has
applied PSO for optimizing the cluster heads location. The
PSO ultimately reduces the communication distance by
locating optimal position of the cluster head nodes in the
cluster. The proposed technique is implemented within the
cluster rather than base station, which makes it a semi-
distributed approach. The proposed technique shows better
performance in terms of network lifetime, average number
of packets sent and energy consumption. M. Natarajan, R.
Arthi, K. Murugan [19] presented Energy Aware Optimal
Cluster Head Selection in Wireless Sensor Networks.
Wireless sensor network (WSN) consists of spatially
distributed autonomous sensors to monitor physical and
environmental conditions. Grouping sensor nodes into the
cluster can reduce the size of the routing table of the each
individual node and conserve communication bandwidth.
Sensors in such environments are energy constrained and
their batteries cannot be recharged. Therefore, designing
energy-aware algorithms becomes an important factor for
extending the lifetime of sensors. The proper organization of
nodes becomes one of the major techniques to expand the
life span of the whole network through aggregating data at
the cluster head. LEACH and PSO are applied for producing
energy-aware clusters with optimal selection of cluster head.
The work is simulated using NS-2 and the performance
metrics are analyzed. Energy aware cluster head selection
using LEACH and PSO are implemented in the wireless
sensor networks. The selection of a cluster head using PSO
minimizes the intra cluster distance between cluster head
and the cluster member, and the optimization of energy
management of the network. From the simulation results, it
is seen that Energy-aware Optimal cluster head selection
using PSO approach increases the network lifetime of the
cluster in such a way by reducing the total energy
consumption than LEACH implementation.
III. CONCLUSION
At present routing in routing in WSNs is a hot research
topic, with a limited but rapidly growing set of efforts being
published In this thesis we have conducted a survey of the
various latest routing protocols in WSNs assuming
underlying base of these protocol as LEACH and PEGASIS.
In this paper wediscussedvarious routing protocols in terms
of intra-cluster topology and cluster head selection.
Although the performances of these protocols are
encouraging for improving scalability of large-scale WSNs,
some issues remain to be considered. For clustering in data
mining several heuristic techniques can be effectively used
in clustering of nodes in WSN environment where equi-
distribution of space and energy and balanced nature of
clusters are the real concerns for enhancing the lifetime of
network. Embedding these algorithms in the routing design
is desirable.
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