TRANSMISSION EFFICIENT CLUSTERING METHOD USING
DECENTRALIZED ALGORITHM BYADAPTIVE GOSSIP
TECHNIQUE
M.Saranya, M. Sahinippriya, K.Pratheesha, P.M.Tamizh thendral
N.Pritha
Asst. Professor Department of ECE,
Panimalar Engineering College, Chennai
Abstract: Energy efficiency is the major consideration in advances of WSNs usefully designed for
low data rate, low power consumption, and low cost networking. Mindful of the above constraints,
selecting an appropriate routing protocol can significantly improve overall performance with limited
sensor network resources especially energy awareness in WSNs. We propose an energy aware routing
protocol improved by our adaptive gossip algorithm and decentralized clustering method. This
adaptive gossip algorithm provides the first hop neighbor nearest to the sink node and adapts to the
changes to varying neighbor node. It will also reduce the redundant routing messages and efficiently
compress data packets directed to the sink. In this proposed approach we also provided some of our
enhancement techniques. Here, we present both experimental and simulation results thoroughly to
evaluate our adaptive gossip proposal.
Index terms: MIMO, adaptive gossip technique, k-hop neighbor, master and slave.
1. INTRODUCTION
A wireless sensor network is an
infrastructure comprised of sensing
computing and communication elements
that gives us the ability to observe and
react to events in a specified environment.
In many densely deployed sensor network
applications such as environmental
monitoring systems, hospitals, disaster
management system sensor network has to
collect data periodically and transmit them
to the sink through multi-hops. According
to field experiment, data communication
contributes
majority
of
energy
consumption of sensor node. It has been
important issue to reduce the amount of
data transmissions in sensor network. The
emerging technology of compressive
sensing can substantially reduce the
amount of data transmission and balance
the traffic load throughout entire network.
2. ARCHITECTURE OF EXISTING
SYSTEM
In existing system the sensor nodes are
uniformly and independently distributed in
a sensor field. All sensor nodes have the
same fixed transmission power and
transmission rate. Each sensor node is
aware of its own geographic location,
which can be obtained via attached GPS or
some other sensor localization techniques.
Fig 1: Architecture of wireless sensor
network.
In our method, sensor nodes are
organized into clusters and each cluster
has a cluster head, represented by the solid
circles. Sensor nodes in each cluster
transmit their original data to the CH
without using CS. Due to this large
amount of power is consumed. Hence a
novel approach to use compressive
technique
3. LEACH-C PROTOCOL
energy constrained WSNs. In this
algorithm the node decides whether it
should participate in the communication or
not based on gossiping probability. If the
node participates in the communication it
judiciously selects a set of candidate nodes
for forwarding. Otherwise the node
decides whether it should sleep based on a
sleeping probability.
fig 3: sensor implementing adaptive gossip
algorithm.
fig 2: flowchart for proposed system.
The disadvantage of LEACH is that the
number of CH nodes is little ambiguous to
count. LEACH-C has been proposed to
clarify this problem. LEACH-C provides
an efficient clustering configuration
algorithm, in which an optimum CH is
selected with minimization of data
transmission energy between a CH and
other nodes in a cluster. In LEACH-C the
base station receives information about
residual node energy and node positions at
the setup phase of each node. The received
data can compute an average residual
energy for all the nodes. The nodes with
less than average energy are excluded in
selection of CH.
4. ADAPTIVE GOSSIP ALGORITHM
The adaptive gossip algorithm
improves the communication performance
in terms of packet delivery ratio, packet
latency, and energy consumption under the
Here the gossiping probability is
determined by the number of neighbor nodes
but the sleeping probability is determined by
both number of neighboring nodes and the
remaining of battery energy. Previous
experimental result tells that this algorithm can
save the energy consumption up to 12% and
reduce the packet latency 5 times compared to
flooding and gossiping techniques.
5. PROPOSED SYSTEM
In our proposed system we are enhancing
five methods in order to improve the
throughput and also to reduce the number
of transmissions, delay and packet loss
ratio respectively. These methods are
employed using the principle of
decentralized algorithm.
SINGLE INPUT SINGLE OUTPUT:
Here in this technique the process
takes place in a scheduled manner i.e. only
when one cluster head completes its
transmission, the other cluster head will
start its transmission. This method will
reduce the delay in transmission. It has to
be noted that only the cluster head can act
as source respectively.
MULTI INPUT MULTI OUTPUT
In multi input multi output method
other than the cluster head the other cluster
member’s acts as source. Since the name
indicates multi input there can be more
number of sources directly updates the
information to the sink the transmission
can occur simultaneously. All the sources
can send data at the same time to the sink
.This method can reduce the packet loss
ratio.
K-HOP NEIGHBOUR
In k-hop neighbor method, when a
particular cluster head can no more handle
more number of nodes due to its energy
loss, it can donate its
members to the
cluster loss; it can donate its members to
the cluster which is capable of holding
more number of nodes.
Fig 4: Cluster using K-hop neighbor.
their energy will form a new cluster. This
is known as master and slave technique.
The slave hosts primarily contribute to the
cluster by running virtual machines
locally. A master host can also run and
monitor virtual machines.
RE-ELECTION OF CLUSTER HEAD
When a cluster head loses its energy
re-election of cluster head takes place. Reelection occurs for the sake of giving equal
chance for every node in a cluster. Due to
this every node can get a chance of being a
cluster head at a given time period. Since
cluster heads are chosen at different time
slots TDMA methods is also employed in
this technique.
6. PERFORMANCE ANALYSIS
The various performances are analyzed
below:
LOSS RATIO
The data loss in the sensor network is
reduced to 22% compared to the existing
system. Since the cluster head is selected
nearer to the sink data losses in the
network is minimized.
DELAY
When packets reach the sink with some
delay then it leads to further delay of
successive packets. Since adaptive gossip
algorithm is employed each sensor node
can able to detect its first hop neighbor.
Thus the proposed system can reduce the
delay by 80%.
This technique is employed when a
cluster head loses its energy after all its
transmissions. The first K-hop clustering
algorithm in wireless sensor networks
adopts a stochastic approach, which has
very low traffic overload.
MASTER AND SLAVE
In master and slave method the
nodes which have rejected during previous
transmission after have rejected during
previous transmission after expending
Fig 5: graph for delay measurement.
THROUGHPUT
With our enhanced factors the overall
throughput of the network is increased to
22% compared to the proposed system.
PROTOCOL EFFICIENCY
The proposed protocol is much efficient
compared to the existing system. From the
simulation graph it is clearly proved that
the adaptive gossip algorithm is far better
than the existing protocol.
CHANNEL MEASUREMENT
The proposed system improves the channel
measurement to about 75% compared to
the existing system.
SOURCE FREQUENCY
The source frequency is improved to 75%
compared to the existing system.
DESTINATION FREQUENCY
Fig 7: graph for drop node measurement.
7. CONCLUSION AND FUTURE
WORK
In our proposed system we analyzed
that adaptive technique can efficiently
reduce the data redundant messages. We
have presented the simulation results and
proved that our proposed system can
significantly improve the throughput, loss
ratio, etc. Our proposed system improved the
overall system performance but it is not much
suitable only for mobile networks. It can be
applied to mobile network using the protocol
which suits it. Even then adaptive gossip
algorithm can be employed for all
protocols.
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Fig 6: graph for destination frequency.
The destination frequency is improved to
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BANDWIDTH
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DROP NODE
Since the nodes which are going to drop,
form a group and performs Master and
Slave concept, they are still in the
communication process.
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