A Review Paper on Energy Capable Routing in Wireless Sensor Network

International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume 6 Issue 3, March-April 2022 Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470
@ IJTSRD | Unique Paper ID – IJTSRD49546 | Volume – 6 | Issue – 3 | Mar-Apr 2022 Page 388
A Review Paper on Energy Capable
Routing in Wireless Sensor Network
Prof. Pooja1
, Prof. Sakena Benazer. S1
, Prof. Ajay Kumar2
1
Department of Electrical Engineering, Sandip University, Madhubani, Bihar, India
2
Department of Civil Engineering, Sandip University, Madhubani, Bihar, India
ABSTRACT
This day’s wireless sensor networks draw the attention of researchers
more due to their admired applications in environment monitoring
systems, radiation uses and nuclear-threat detection applications;
weapon sensors for ships; battlefield reconnaissance and surveillance;
military power, control mechanism, intelligence centre,
communications and targeting systems and biomedical applications.
Wireless sensor network provides cheap cost solution to various
world problems. Sensors are low cost devices with limited storage,
computational power systems. Several security mechanisms for
sensor network must be energy efficient as security is the major
concerned when they will be used in large scale as sensors have
limited power and computational capability and should not be
computational intensive. In this review paper we study the various
energy-efficient secure routing methods for WSN.
KEYWORDS: WSN, LEACH, Energy, Efficient, Routing
How to cite this paper: Prof. Pooja |
Prof. Sakena Benazer. S | Prof. Ajay
Kumar "A Review Paper on Energy
Capable Routing in Wireless Sensor
Network" Published
in International
Journal of Trend in
Scientific Research
and Development
(ijtsrd), ISSN: 2456-
6470, Volume-6 |
Issue-3, April 2022,
pp.388-392, URL:
www.ijtsrd.com/papers/ijtsrd49546.pdf
Copyright © 2022 by author(s) and
International Journal of Trend in
Scientific Research and Development
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I. INTRODUCTION
Wireless sensor networks (WSNs) consist of tiny
devices, which have a battery, a sensor, a
microprocessor and a radio transmitter component.
The application area of WSNs can be classified into
two general classes: monitoring applications and
tracking applications. While the first class of
applications includes habitat monitoring, building
monitoring, machinery monitoring and greenhouse
monitoring etc., the second class includes animal
tracking, vehicle tracking and goods tracking insupply
chains etc. Due to this large range of application area,
performance metrics in sensor network are strictly
application-specific. However, 'unattended operation
of the network for long time' or 'long network lifetime'
can be determined as a common performance
requirement for the most of the applications. In
general, network lifetime can be defined as time span
until the network is considered nonfunctional. Infact,
as in performance metrics, perception of no
functionality is also application- specific for sensor
networks. A sensor network can be considered as
nonfunctional if data delivery delay exceeds a
threshold, or if the coverage of the monitoring area is
less than the preferred level, or if the network is
partition due to the energy deficiency of some
bottleneck nodes.
The application area of WSNs can be classified into
two general classes as monitoring and tracking
applications. Based on the type of monitoring or
tracking environment or assets, sensor nodes may be
deployed unstructured or structured based. An
example for the unstructured WSN may be dropping
sensor nodes from an airplane for surveillance of a
field. In this type of WSN, network maintenance such
as managing connectivity is difficult since there are
large numbers of nodes. If all or some of the sensor
nodes are deployed in a pre-planned manner as in
structured WSNs, network maintenance is easier since
fewer nodes are placed at specific locations: an
example may be a structural monitoring such as
buildings or bridges. However, unattended operation
IJTSRD49546

International Journal of Trend in Scientific Research and Development @ www.ijtsrd.com eISSN: 2456-6470
requirement may exist in both scenarios once they are
deployed.
Most important characteristics of wireless sensor
networks
A. Large number of nodes in the network
B. Mostly many to one communication pattern
C. Limited resources (battery powered, processing
capability etc.)
D. Difficult network maintenance especially in
unplanned deployment of sensornodes in the area
(eg. throwing from an airplane)
E. Once they are deployed, there exists a
requirement of unattended operation and
organization of the network for long time.
Resource limited feature of WSN distinguish
sensor networks from other ad hoc networks and
from the performance point of view, unlike ad
hoc networks, performance metrics is strictly
application specific for sensor networks.
II. NETWORK LIFETIME
In general, network lifetime can be defined as time
span until the network is considered nonfunctional. A
sensor network can be considered as nonfunctional if
data delivery delay exceeds a threshold, or if the
coverage of the monitoring area is less than the
preferred level, or if the network is partition due to the
energy deficiency of some bottleneck nodes. The
lifetime of the sensor network is defined asthe time
period until the first node runs out of battery
(minimum individual node lifetime) or a certain
percentage of the network nodes go at (nth minimum
individual node lifetime), as in . The existing
definitions in the literature the network lifetime is
defined as time span which allows maximum
amount of data delivery to the sink node and
achievable maximum amount is restricted by the
nodes' initial energy level.The network lifetime as the
time spans this allows nodes to deliver the maximum
amount of data to the sink node. Maxi- mum amount
of data delivery meant that nodes spend most of their
time in reception and transmission modes instead of
idle and sleep mode. For example, if there is no
networking activity (transmission and reception), the
battery lifetime of the nodes will be longer (their
battery last in longer time) due to lower energy
consumption of idle mode, but network lifetime will
be zero because transmitted data to the sink node will
be zero.
Time Efficiency
Time efficiency is ability of the sensor network to
perform its duty under the required time limits. In
fact, this performance metrics have broad range to be
considered as fulfilled. While for some application
such as monitoring of intruder time efficiency has big
importance, for others like temperature monitoring it
does not have that importance.
Sink Oriented Connectivity
In ad hoc networks, connectivity is considered as a
metric that shows the ability to transmit data from
any source nodes of network to destination node.
Therefore, the size of the largest connected component
in the network represents an important performance
metric in ad hoc networks. However, in sensor
network where connectivity around a based station is
the most important, the size of the connected
component is not sufficient. Therefore, for
distinguishing from the ad hoc networks,it is called as
"sink oriented connectivity". It must be noted that this
definition assumes that the basic communication
model of wireless sensor network is many- to-one
type. In case of clustered network, the size of the
largest connected component can be taken as a
performance metric to ensure data delivery.
Scalability
Scalability is the ability for the network to accept new
nodes without impacting the application requirement.
Communication algorithms or protocols for sensor
network need to provide scalability. Due to energy
restriction of sensor network, new nodes need to be
added to extend the network lifetime or provide higher
level of reliability.
Energy Efficiency in Wireless Sensor Net-work
In most applications, sensor nodes are restricted in
energy supply. Al- though energy harvesting from
environment is also possible in some applications, this
is out of scope of this study. In order to achieve the
primary goal of energy efficiency in design of
wireless sensor networks, the main energy dissipation
sources are identified in a sensor node component and
sensor networks.
The power consumption of the sensor node radio
subsystem depends on the operational mode. Many
sensor node device vendors provide low-power mode
option for the radio. A radio can be typically in four
different modes of operation; transmission, reception,
idle, and low-power (sleep) mode. Aim of the low-
power mode is putting the radio in this mode when
node is not participating any networkingactivities. In
fact, when a node is in idle mode (neither receiving
nor transmitting), power consumption is the same as
in reception mode. However, sensor nodes perform a
cooperative task in the network as relaying the traffic
to the base station as well as sending their own data.
Therefore, sensor nodes need to listen to the radio
channel for any possible relaying task.
Collision is another major source of energy waste, if
more than one node send packetat the same time, the

transmitted packet is corrupted and discarded.
Consequently,the retransmission of packets is needed
and that increases energy consumption. Therefore,
collision free channel access is an important goal in
the design of sensor network.
In organization of the nodes for cooperative tasks,
there is a need for control packet exchange. This
should be kept as low as possible to use the energy for
useful data packets.
III. POWER AWARE ROUTING IN WSN
Main task of a routing protocol is to deliver the sensed
data from source sensor nodesto a single or a few sink
nodes. Due to ad hoc nature of the sensor networks,
there is no fixed network infrastructure and the nodes
have many possible paths to maintain connectivity to
the sink node. Therefore, energy consideration plays
an important role choosing the optimum path to
access the sink node. In networking, the routing
problem can generally be interpreted as avow
problem. There are several definitions of network
lifetime, this study focuses on the network lifetime
definition in terms of energy deficiency of the nodes.
Many existing sensor node devices provide the
transmission at different power levels, hence it is
possible to choose between multi- hop or direct
communication. In general, multi-hop routing will
consume less energy than direct communication
because transmission power of a wireless radio is
proportional to distance squared or even higher order
based on the type of theenvironment. However, there
might be some bottleneck nodes in the multi- hop
paths which may create the network partition since
their battery will be exhausted earlier. The energy
consumption model plays a key role on defining the
link costs. There is one mostly used energy
consumption model in the literature.
= . +
where e(x) represents the power required for
transmission across a distance x. fi is thepath loss
exponent and gets the value of 2 for free space and 4
for fading channel, a and c are constants.
IV. LITERATURE REVIEW
Alshowkan, M. and Elleithy, K.; Alhassan, H.
investigated the current security mechanisms in
wireless sensor networks as well as reducing power
consumption. LEACH protocols provide an energy
routing protocol. The improved secure and more
energy efficient routing protocol called Lightweight
Secure LEACH has been adopted. Authentication
algorithm has been integrated to assure data integrity,
availability and authenticity. This investigation
provides the improvement over LEACH protocol
which makes it more secure and extra energy
efficient for reducing the effect of the overhead
energy consumption from the added security
measures.
Haneef, M.; Zhou Wenxun and Zhongliang Deng
presented the deployed redundant nodes in to account
which cover major fraction of energy depletion in the
network which is efficient routing algorithm based
upon the frame work of LEACH.A manyof redundant
data is present in wireless sensor network due to
widely deployed nodes. For checking the presented
methodology simulation has been done using Matlab.
Results show that MG-LEACH had performed better
LEACH on the basis of Network life time.
Yu Miao; Bai Guang-wei and Shen Hang had
proposed the performance analysesof classical low-
energy adaptive clustering hierarchy routing
algorithm. Investigation has been done on the
limitations of the LEACH in terms of energy balance
and networks scalability. The proposed work is that
the cluster-heads are elected by a probability based on
the ratio between residual energy of each node and
the average energy of the network.
Saravanakumar, R., Susila, S.G. and Raja, J. have
analyzed the basic distributed clustering routing
protocol LEACH, then proposed a routing protocol
and the data aggregation method in which the sensor
nodes form the cluster and the cluster-head elected
based on the residual energy of the individual node
calculation without re- clustering and the node
scheduling scheme is adopted in each cluster of the
WSNs. ACTIVE and SLEEP mode, the energy
efficiency has been increased about to 50% than
LEACH protocol. The proposed routing protocol
significantlyreduces energy consumption and increase
the total lifetime of the WSN.
Muhamad, W.N.W. and Naimanalyzed the Wireless
sensor networks lifetime is either superficial or
impractical, which can prevents us from thoroughly
understanding the efficiencyof these proposed routing
protocols. This work has beendone to maximize the
lifetime of the WSN. LEACH routing protocol is
increased the network lifetime by 65.2% compared to
DC and MTE.
Wei Bo, Hu Han-ying and Fu Wen improved
LEACH protocol for data gathering and aggregation
in wireless sensor networks. LEACH includes
distributed cluster formation, local processing for
reducing global communication, and randomized
alternation of the cluster- heads. This research work
protocol uses multi-hop routing instead of 2-hop
routing in LEACH, and related algorithm was
proposed. Results show that improved protocol is
more energy-efficient than conventional LEACH.

Islam, M.J.; Islam, M.M.; Islam, M.N. performed a
solar- aware, programmed clustered routing protocol
A-sLEACH which is an extension to sLEACH for
routing and MTE for radio model. Outcomes of
applying this proposed scheme gives better
performance compared to MTE and sLEACH .
V. CONCLUSION
Performance enhancement of sensor network using
energy efficiency the point of view with the varying
networking parameters. Wireless sensor networks can
provide low cost solution to verity of real-world
harms. Sensors are low cost tiny devices with limited
storage, computational capacity and power. They can
be deployed in large scale for performing both
military and civilian tasks. Security is one of the main
concerned when they will be deployed in large scale.
As sensors have limited power and computational
capability, any security mechanisms for sensor
network must be energy efficient and should not be
computational intensive.
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