Delay Constraint Network Structure with in-Network Data Fusion for Wireless Sensor Networks

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 08 | Aug -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 2104
DELAY CONSTRAINT NETWORK STRUCTURE WITH IN-NETWORK
DATA FUSION FOR WIRELESS SENSOR NETWORKS
1A.Rajasekaran , 2Dr V.Nagarajan
1Research Scholar. Dept of ECE, SCSVMV University, Enathur,Kanchipuram,
2Professor and Head, Department of ECE, Adhiparasakthi Engineering college,Melmaruvathur.
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ABSTRACT - A wireless sensor network (WSN) comprises a
large number of wireless sensor nodes Reduction in energy
consumption in WSNs involves effective techniques such as In-
Network data fusion and clustering. However, in a data
aggregation process clustering introduces bottlenecks to a
network which causes extra delay. In this paper, a delay-aware
network structure for WSNs with in-network data fusion is
proposed. To optimize intra-communication distance an
optimization process is also proposed. Simulation results show
that, when compared with other existing aggregation
structures, the proposed network structure can reduce delays
in data aggregation processes and keep the total energy
consumption at low levels provided that data are only partially
fusible.
Index Terms - Data aggregation, Data centric routing,
DED(Distance energy and degree),Wireless sensor
networks
I. INTRODUCTION
Wireless sensor networks is an emerging
technology that is gaining a lot of attention for applications
such as monitoring and data gathering. A survey Wireless
Sensor Networks (WSNs) consist of small nodes with
sensing, computation, and wireless communications
capabilities. [1]
LEACH-Low energy adaptive clustering hierarchy Networks
with LEACH were organized into multiple single-layered
clusters LEACH includes a new, distributed cluster formation
technique that enables self-organization of large numbers of
nodes, algorithms for adapting clusters and rotating cluster
head positions to evenly distribute the energy load among all
the nodes, and techniques to enable distributed signal
processing to save communication resources. In particular,
data aggregation techniques can be used to combine several
correlated data signals into a smaller set of information that
maintains the effective data. [2]
One drawback that occurs in the LEACH protocol is, the
election procedure (random) can lead cluster heads to have a
weak energy reserve, which can affect the data transmission
and can lead to a reconfiguration of the built structure.
The proposed network structure is a tree-based network. In
the proposed network structure, wireless sensor nodes are
organized into multiple single-layered clusters of different
sizes, such that clusters can communicate with the FC in an
interleaved manner
 In the proposed system by modifying the network
structure the extra delays that is caused in the data
aggregation process is highly reduced.
 The sensor nodes are organized into clusters of different
sizes by the proposed structure which enhances the
communication of every cluster with the fusion center.

 By the proposed structure the size of the outgoing data is
made equal or lesser than the size of the incoming data. The
delay is constrained by the proposed structure which
thereby reduces the power consumption.
 Data forwarding takes place only at the cluster heads since
the proposed system is organized with multiple single layer
clusters.
II. PROPOSED SYSTEM ARCHITECRE
The wireless sensor network architecture consists of sensor
nodes where random nodes form a cluster in which one of
the node is a cluster head and other nodes in the cluster are
cluster members. The process in a wireless sensor network
involves communication between the nodes by transmission
of data by the cluster heads from its cluster members to the
fusion center.

Fig 2.1 Network Model: Infrastructure Construction
1. Cluster head selection- LEACH
2. Data aggregation using the LEACH based CH
3. Cluster head selection- DED(Distance energy and
degree)
4. Data aggregation using the DED based CH
In a typical clustering algorithm, a number of nodes in
a network will be selected as the cluster heads (CHs). The
remaining nodes will be regarded as cluster members (CMs)
and form connections with the CHs. A CH will collect
information from its CMs. If the data obtained from the CMs
are fusible, a CH can perform data fusion on the incoming
data and reduce the size of its outgoing data. .
A’ A A”
Fig 2.2 Fig 2.3
In fig 2.2, The amount of delay to receive the data A
from both the members is more and hence the power
consumption is also more. Therefore, A’ > A.
In fig 2.3, The transmission of data from one the CM is done
directly with the fusion center. And from the other cm it is
done through the cluster through the cluster head. Here the
delay and the energy consumption is reduced wherein
A”< A’.
In LEACH there is a self organization of nodes for
cluster formation and data aggregation process. And the
selection of cluster head is rotated so that there is an even
distribution of energy throughout the network. LEACH
forms clusters by using a distributed algorithm, where nodes
make autonomous decisions without any centralized control.
In LEACH, the nodes organize themselves into local
clusters, with one node acting as the cluster head. All non-
cluster head nodes transmit their data to the cluster head,
while the cluster head node receives data from all the cluster
members, performs signal processing functions on the data
(e.g., data aggregation), and transmits data to the remote BS.
Therefore, being a cluster head node is much more energy
intensive than being a non cluster head node.
DED Clustering Algorithm which involves the
important features such as degree, energy and distance and
transmission range.Using this algorithm a node with higher
residual energy, higher degree and closer to the Fusion
center is more likely elected as a ClusterHead. The members
of each cluster communicate directly with their ClusterHeads
(CHs) and each CH aggregates the received messages and
transmits them directly to the Fusion center.
Clustering algorithm elects the sensor having high
connectivity, closer to destination and reduced power
consumption sensor as a cluster head (CH). Through the
election of high connectivity CH, the number of hops
involved between sensor and cluster head is reduced there
by reducing the energy. Through the election of CH closer to
destination, number of hops in the data transmission is
reduced. When the current CH runs out of energy, re-election
of CH is conducted to facilitate the balanced energy
consumption among the sensors in the network. Under the
condition of this procedure for joining to the new cluster is
also proposed. So this algorithm achieves balanced energy
consumption in the network by selecting energy efficient and
stable CH. Node which is having highest residual Energy and
highest degree will be elected as cluster head which implies
node having highest weight.
Weight = (Energy * Degree) / Distance - 2.1
III. PERFORMANCE EVALUATION
The proposed structure has an improved
performance by overcoming the drawbacks of the existing
system. An optimization process is designed to construct the
NETWORK
INFRASTRUCT
URE
FUSION
CENTER
FC
CH
CM
CM
CH
CM
FC
CM

proposed network structure, which helps maintaining the
total energy consumption at a low level. Simulation results
show that, when in-network data
Fig 3.1 Graph comparison for Energy Consumption
Fig 3.2 Graph comparison for Delay
fusion does not yield any size reduction in outgoing data, the
performances of networks with the proposed network
structure are higher than those with LEACH. The
performance of the proposed network structure can be
further improved by knowing the minimum achievable
compression ratio between the sizes of the incoming and
outgoing data.
IV. CONCLUSION
In the proposed network structure the size of the clusters
are designed in such a way such that the nodes that are
present in the network can communicate with each other.
The clusters present are of different size and data
aggregation is efficient by the proposed structure only when
the data if partially fusible. The results obtained from the
simulation show that the delay and energy consumption is
greatly reduced by the proposed structure when compared
to the LEACH protocol.
REFERENCES
[1]. Sivagami K. Pavai D. Sridharan,“ Latency Optimized
Data Aggregation Timing Model for Wireless Sensor
Networks ”,IJCSI International Journal of Computer
Science Issues, Vol. 7, Issue 3, No 6, May 2010 A
[2]. J. N. Al-Karaki and A. E. Kamal, “Routing techniques in
wireless sensor networks: A survey,” IEEE Wireless
Commun. Mag., vol. 11, no. 6, pp. 6– 28, Dec. 2004.
[3]. Jun Zhang and Xiaohua Jia, “Real-Time Data
Aggregation in Contention-Based Wireless Sensor
Networks”.
[4]. Kemal Akkaya, Mohamed Younis Moustafa Youssef,
“Efficient Aggregation of Delay Constrained Data in
Wireless Sensor Networks”.
[5]. Impact of Data Aggregation in Wireless Sensor
NetworksBhaskar Krishnamachari, Deborah Estrin and
Stephen Wicker
[6]. V.Cibi Castro, Dr.R. Rajesh, “Delay Aware Tree Based
Technique in Wireless Sensor Network”, International
Conference on Computing and Control Engineering
(ICCCE 2012), 12 & 13 April, 2012A.
[7]. Chi-Tsun Cheng, Henry Leung and Patrick Maupin,” A
Delay-Aware Network Structure for Wireless Sensor
Networks With In-Network Data Fusion”, IEEE
SENSORS JOURNAL, VOL. 13, NO. 5, MAY 2013

Delay Constraint Network Structure with in-Network Data Fusion for Wireless Sensor Networks

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