Approach for Improvement in LEACH Protocol for Wireless Sensor Network

Abstract

This paper studies the problems with LEACH protocol and presents improved ideas to select the cluster head node. The main problem with the LEACH lies in the random selection of cluster heads. There exists a probability that cluster heads formed are unbalanced and may remain in one part of network making some part of network unreachable. Here our main purpose is to select a cluster head depending upon its current energy level and distance from the sink node. This increases the energy efficiency and hence network lifetime.

Full text

Approach for Improvement in LEACH Protocol for
Wireless Sensor Network
Reetika Munjal Bhavneesh Malik
ECE Deptt, NCCE, Israna ECE Deptt, VCE
Panipat, India Rohtak, India
reetika.munjal04@gmail.com
B.malik7@gmail.com
Abstract— This paper studies the problems with LEACH
protocol and presents improved ideas to select the cluster head
node. The main problem with the LEACH lies in the random
selection of cluster heads. There exists a probability that cluster
heads formed are unbalanced and may remain in one part of
network making some part of network unreachable. Here our
main purpose is to select a cluster head depending upon its
current energy level and distance from the sink node. This
increases the energy efficiency and hence network lifetime.
I. INTRODUCTION
Wireless sensor networks (WSN) consist of a huge number
of small self-contained devices with computational, sensing
and wireless communication capabilities. These sensors [1]
measure ambient conditions e.g. speed, temperature, pressure,
humidity etc. and transform the data into electrical signals
which can be processed to reveal some characteristics about
the phenomena. These analog signals are then converted into
digital signals which are further processed in processing unit.
Transmission between the sensor nodes is wireless which is
the most power consuming activity in the sensor networks. [2]
Fig.1 Communication in a Sensor network
For this, clustering of the sensor nodes is done. Cluster-based
routing algorithm has a better energy utilization rate compared
with non-cluster routing algorithm. The basic idea of
clustering routing is to use the information aggregation
mechanism in the cluster head to reduce the amount of data
transmission, thereby, reduce the energy dissipation in
communication. In clustering, every node sends data to its
selected cluster head & this cluster head further sends data to
the sink node or say base station. Hence energy consumption
is reduced in comparison to the case where each node would
have send data directly to the base station as the radio activity
consumes more energy.
Routing or Data Transmission in Clusters:
From routing perspective, clustering allows to split data
transmission into intra-cluster (within a cluster) and inter
cluster (between cluster heads and every cluster head and the
sink) communication.
a) Intra-cluster Routing:
Most of the earlier works on clustering assume direct (one-
hop) communication between member nodes and their
respective cluster heads. All the member nodes are at most
two hops away from each other (Figure 2(a)). One-hop
clusters makes selection and propagation of cluster heads
easy, however, multi-hop intra-cluster connectivity is
sometimes required for large radio ranges [3][4].
Fig.2(a) Intra-Cluster communication
b) Inter-cluster Routing:
Earlier cluster-based routing protocols such as LEACH
(Energy-efficient communication protocol for wireless sensor
networks, 2000) assume that the cluster heads have long
communication ranges allowing direct connection (single hop)
between every cluster head and the sink.

Fig.2(b) One-Hop towards sink
II BACKGROUND
LEACH (Low Energy Adaptive Clustering Hierarchy) [5], [6]
is a distributed clustering protocol which utilizes randomized
rotation of local CHs to evenly distribute energy utilization
between the nodes of WSNs. It uses one-hop inter-cluster
communication towards sink. The whole operation of the
LEACH protocol is divided into rounds. Each round consists
of:
a) Set-up phase (clusters are organized)
Cluster Head Selection.
Cluster Formation.
b) Steady state Phase (data transmission)
Fig.3 Timeline diagram of leach protocol
The number of nodes that remain alive using LEACH is
significantly larger (four to eight times larger) than that using
static clustering or minimum transmission energy (MTE)
routing. But the main problem with LEACH protocol lies in
the random selection of cluster heads. There exists a
probability that the cluster heads formed are unbalanced and
may remain in one part of the network making some part of
the network unreachable. Also one-hop inter & intra-cluster
used in LEACH is not applicable for large region networks.
A new adaptive strategy is proposed known as LEACH-B to
choose cluster-heads and to vary their election frequency
according to the dissipated energy. However, the simulation
results divulge that there is some degree of improvement
using LEACH-B.
Moreover, an improved scheme of LEACH was proposed,
named LEACH-C. In LEACH-C, a centralized algorithm at
the base station makes cluster formation. However, LEACH-C
is not feasible for larger networks because nodes far away
from the base station will have problem sending their states
to the base station and as the role of cluster heads rotates so
every time the far nodes will not reach the base station in
quick time increasing the latency and delay.
Further, the clustering protocol known as LEACH-E was
proposed by Heinzelman et.al. In this protocol it is proposed
to elect the cluster-heads according to the energy left in each
node. The drawback of LEACH-E is that it requires the
assistance of routing protocol, which should allow each node
to know the total energy of network.
Distributed Efficient Clustering (DEEC) which is dedicatedly
designed for energy heterogeneous scenarios, where nodes are
initialized at various energy levels [7]. However neither of
them assures the selection of energy-rich cluster heads, or the
evenness of cluster head dispersion. Decentralized Energy
Efficient clustering Propagation (DEEP) prevents cluster
heads from being too close to each other, but ignores cluster
head’s energy qualifications.
Lindsey et al. proposed Power-Efficient Gathering in Sensor
Information Systems (PEGASIS). PEGASIS makes a
communication chain using a Traveling Sales Person
heuristic. Each node only communicates with two close
neighbors along the communication chain. Only a single
designated node gathers data from other nodes and transmits
the aggregated data to the sink node.
III PROPOSED WORK
A. Network Model:
WSN model [8] with the following properties has been
considered:
• All sensor nodes are immobile, homogeneous and
energy constrained and they can control their
transmit power for different transmission ranges.
• Besides, all nodes sense the environment at a fixed
rate and they always have data to send to the base
station. Moreover all nodes can operate as cluster
heads.
• Same energy dissipation in transmit and receive
circuitry.
• The location of the base station is fixed, which is
either inside the network or far from the sensors.

• Data fusion is used to reduce the total data sent, and
direct one hop transmission is used to send fused data
from each cluster head to the base station.
Fig.4 Radio Dissipation Model
Let us assume a simple model for the radio hardware energy
consumption where the transmitter dissipates energy to run the
radio electronics and the power amplifier, and the receiver
dissipates energy to run the radio electronics. For our
experiments, depending on transmission range we have
considered both free space and multipath fading channel
models.
If the distance is less than a threshold, d0, the free space
model (d
2
power loss) is used; otherwise, the multi path model
(d
4
power loss) is used. Or, for short distance transmission,
such as intra-cluster communication, the energy consumed by
a transmitting amplifier is proportional to d
2
and for long
distance transmission, such as inter-cluster communication,
the energy consumption is proportional to d
4
. The energy
consumption models of the transmitter and receiver separated
by distance d for an l-bit message are respectively given by:
E
TX
(l,d) =
E
RX
(l) = lE
elec
Where Eelec is the energy consumed per bit to run the
circuitry of transmitter and receiver. E
fs
and E
mp
are the power
loss of free space and multi path models used, which depend
on the acceptable bit-error rate, chosen. One suitable choice
for the threshold transmission distance do may be:
Do = √E
fs
/ E
mp
Furthermore, the cost of data aggregation is modeled by E
DA
.
B. Improvement on LEACH Protocol:
(1) The criterion of selecting cluster head node LEACH
protocol randomly selects cluster head at each round.
Therefore, some nodes may exhaust energy too
quickly. In this thesis, our modified protocol makes
the nodes with more residual energy have more
chance as cluster head and this will prevent the whole
network to die too early.
(2) Multi-hop communication among cluster heads.
Cluster heads directly communicate with sink in
LEACH protocol. The energy consumption between
cluster head and sink are greater than energy
consumption among cluster heads, so the cluster head
will exhaust energy soon. Multi-hop communication
can avoid the whole network from dying quickly and
prolong the network lifetime.
C. Proposed Algorithm:
LEACH has two phases: the set-up and steady-state. The set-
up phase is where cluster-heads are chosen and the steady-
state phase is where the data transfer occurs. In the set-up
phase the cluster heads are chosen stochastically, which is
randomly based on an algorithm. A threshold is determined
based on this algorithm:
1) The first round will be same as normal leach round.
2) In the second round, each node would send its residual
energy along with the sending time stamp T-S and remaining
lifetime of battery.
3) When the base station receives the packet, it will calculate:
T-R - T-S (difference between receiving timestamp and
current time stamp)
4) If difference > = remaining lifetime of node, the node will
be non-cluster head.
Else If remaining lifetime = max among all nodes of the
cluster; choose the node as cluster head.
D. Parameters for Simulation:
We use similar random 100-node networks and radio models
with LEACH.
1) Energy required in sending or receiving 1bit: Eelec =
50nJ/bit
2) The amount of data sent by nodes each time: k = 200bit.
3) The initial energy of every node: E = 0.5J
4) Energy consumed in every bit data fusion: EDA = 50pJ/bit
5) Area: 100*100
6) The location of Sink: (50, 50)
7) The percentage of cluster head: p = 0.1
8) The number nodes: n = 100
lE
elec
+ lE
fs
d
2
, if d <= d
o
lE
elec
+ lE
fs
d
4
, if d > d
o

E. Software Used:
The software tool used here to implement the above algorithm
is MATLAB.
IV RESULTS AND DISCUSSIONS
Fig.5(a) illustrates the graph that indicates statistics of alive
nodes with different number of rounds. In our proposed algo
i.e. in fig.5(a), all the 100 nodes are alive till 1500 rounds and
start dying thereafter. All the nodes completely die after 2700
rounds and the network works satisfactorily till then. While in
LEACH i.e. in fig.5(b), all the 100 nodes are alive till 1000
rounds only and then start dying. Only after 1400 rounds
performance of network starts degrading and all the nodes die
completely after 1400 rounds. Hence we can say that lifetime
of network is increased in our proposed algorithm.
(a)
(b)
Fig. 5 Total number of alive nodes in different number of rounds
(a) In our proposed scheme (b) In LEACH
Fig. 6 illustrates the graph that indicates total number of
Cluster Heads in different number of rounds. Fig (a) indicates
more number of cluster heads are present till 2800 rounds and
hence multi hop communication is possible. Therefore nodes
do not need to directly communicate with the base station
which is more energy consuming. Instead they communicate
with their nearest cluster head thereby decreasing the energy
& power consumption. While in LEACH number of Cluster
Heads formed are less.
(a)
(b)
Fig. 6 Total number of Cluster Heads formed in different
number of rounds (a) In our proposed scheme (b) In LEACH
V CONCLUSION & FUTURE WORK
Simulation results show that our algorithm is much more
efficient and indicate that this algorithm can balance nodes’
energy consumption and prolong the network’s life span. It
also has good stability and extensibility. Such results are

obtained under additional conditions, i.e., known location
information and ability to adjust data transmission power
based on distance. The algorithm can be easily implemented.
The factors affecting cluster formation and CH
communication are open issues for future research. Moreover,
the process of data aggregation and fusion among clusters is
also an interesting problem to explore.
Though the performance of the protocols discussed in this
paper is promising in terms of energy efficiency, further
research would be needed to address issues related to Quality
of Service (QoS) posed by video and imaging sensors and
real-time applications.
VI REFERENCES
[1] Sanjay Kumar Jha and N.P.Singh, “Performance Evaluation of Protocols
in Wireless Sensor Networks”, presented at 4
th
National Conference on
Machine Intelligence (NCMI), HEC Jagadhri, India, 2008.
[2] G. J. Pottie and W. J. Kaiser. Wireless Integrated Network Sensors.
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2000; Younis & Fahmy, 2004
[4] Bandyopadhyay & Coyle, 2003; Ding et al., 2005.
[5] N.M.A. Latiff, C.C. Tsimenidis, and B.S. Sharif, “Performance
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[6] Z. Zhang and X. Zhang., “Research of Improved Clustering Routing
Algorithm Based on Load Balance in Wireless Sensor Networks”, IET
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[7]
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