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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1388
ENERGY EFFICIENT PROTOCOL IN WIRELESS SENSOR NETWORK
M.V. Jitendra1, B.T. Krishna2
1Student, Dept. of ECE, ucek, JNTU Kakinada, AP, India
2Professor, Dept. of ECE, ucek, JNTU Kakinada, AP, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - A wireless sensor network is a group of tiny,
generally battery powered devices and wirelessinfrastructure
that monitor and record conditions in any environment. The
Wireless sensor networks consists of number of sensor nodes
connected each other and sense the data and transmits the
data to the sink node. The sensor nodes in wireless sensor
networks has limited energy, In LEACH (Low energy adaptive
clustering hierarchy) every node has chance to become a CHs
after 1/p rounds. All the nodes may not have same energy in
cluster. So, the energy is not well distributed in the cluster and
the low energy nodes will finish earlier than the high energy
nodes. To improve the network life time DEEC (Distributive
energy efficient clustering) is used.
Key Words: wirelesssensor networks,energy efficient,node,
LEACH, DEEC.
1. INTRODUCTION
Now in recent scenario the growth of wireless
communication is vast. Because the wireless technology can
be applied in any kind of situation it has a capability of
reaching in any part of the earth surface. There are so many
wireless network are there, some are infrastructure based
and some are infrastructure less.Ad-hoc andwirelesssensor
network, cellular network are some example of wireless
network.
The term "wireless" has become a generic and all-
encompassing word used to describe communications in
which electromagnetic waves to carry a signal over part or
the entire communicationpath.Wirelesstechnologycanable
to reach virtually every location on the surface of the earth
[1].Ad- hoc and Sensor Networks are one of the parts of the
wireless communication. In ad-hoc network each and every
nodes are allow tocommunicatewitheachotherwithout any
fixed infrastructure. This is actually one of the features that
differentiate between ad-hoc and other wireless technology
like cellular networks and wireless LAN which actually
required infrastructure based communication like through
some base station. [2].
Wireless sensor network are one of the category
belongs to ad-hoc networks. Sensor network are also
composed of nodes. Here actually the node has a specific
name that is “Sensor” because these nodes are equipped
with smart sensors [2]. A sensor node is a device that
converts a sensedcharacteristic liketemperature,vibrations,
pressure into a form recognize by the users. Wirelesssensor
networks nodes are less mobile than ad-hoc networks. So
mobility in case of ad-hoc is more. In wireless sensor
network data arerequested dependinguponcertainphysical
quantity. So wireless sensor network is data centric. A
sensor consists of a transducer, an embedded processor,
small memory unit and a wireless transceiver and all these
devices run on the power supplied by an attached battery.
Advances in wireless communication made it
possible to develop wireless sensor networks (WSN)
consisting of small devices, which collect information by
cooperating with each other. Thesesmall sensingdevices are
called nodes and consist of CPU (for data processing),
memory (for data storage), battery (for energy) and
transceiver (for receiving and sending signals or data from
one node to another). The size of each sensor node varies
with applications. For example, in some military or
surveillance applications it might be microscopically small.
Its cost depends on its parameters like memory size,
processing speed and battery [3]. Today, wireless sensor
networks are widely used in the commercial and industrial
areas such as for e.g. environmental monitoring, habitat
monitoring, healthcare,processmonitoringandsurveillance.
For example, in a military area, we can use wireless sensor
networks to monitor an activity. If an event is triggered,
these sensor nodes sense it and send the information to the
base station (called sink) by communicating with other
nodes. The use of wireless sensor networksisincreasing day
by day and at the same time it faces the problem of energy
constraints in terms of limited battery lifetime.Aseachnode
depends on energy for its activities, this has become a major
issue in wireless sensor networks. The failure of one node
can interrupt the entire system or application.Everysensing
node can be in active (for receiving and transmission
activities), idle and sleep modes. In active mode nodes
consume energy when receiving or transmitting data.Inidle
mode, the nodes consume almostthesameamountof energy
as in active mode, while in sleep mode, the nodes shutdown
the radio to save the energy.
2. Literature survey
The purpose of this project is to find protocols that are
energy efficient and support real-time traffic for
environments like habitat monitoring or area surveillance.
Wireless sensor nodes which are battery operated are used
fordetecting andcollectinginformationfromtheareaswhere
there is very little scope for manual handling to recharge or
change batteries. Thesesensingnodescollecttheinformation
and pass them on to the network towards the sinkforfurther
actions. For a better functioning and a longer lifetime for a
sensing node within the network, we need to consider its
energy consumption as a major factor of concern. Here these
node detect and collects information regarding any object
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1389
that is moving or any event that’s triggered. The network
carrying this information uses an ordinary protocol stack
which carriesoutthegeneralprocessoftransmissionwithout
any concerns for energy efficiency factor.
Following are the assumptions for the surveillance
applications in wirelesssensor networks which are usedasa
frame of reference in the further study [4]. Wireless sensor
networks consist of a number of sensing nodes which are
distributed in a wide area. They sense an event occurring in
the environment and these sensing nodes are distributed or
placed according to the requirements of the application. The
base station (sink), which collects data from other nodes,
interacts with a user (someone interested in monitoring the
activity). Data can be collected in many ways from a sensing
node to a sink node like using hopping techniques or
transmitting data at certain frequencies. Sinks have more
advanced features than sensing nodes in terms of data
transmissions and processing capabilities, memory size and
energy reserves. There can be multiplesinksforanetworkso
that there is no single point of failure. Energy dissipation is a
major factor in WSNs during communication among the
nodes. Energy should be saved, so that the batteries do not
get depleted or drained quickly as these are not easily
replaceable in applications such as surveillance. Quality of
service ensures the effectivecommunicationwithinthegiven
or bounded delay time. Protocols should check for network
stability, redundant data should be transmitted over the
network for any type of traffic distribution. It also needs to
maintaincertainresourcelimitingfactors,suchasbandwidth,
memory buffer size and processing capabilities. The
transmission mode plays an important role in WSNs. Nodes
can take single-hop or multi-hop depending upon the type of
network topologychosen for communicatingortransmitting
data to other nodes within the network. In surveillance
applications, sensor nodes are placed in unattended areas so
it should be self-organizing and self-creating.
LEACH (Low Energy Adaptive Clustering Hierarchical)
The current interest in wireless sensor networks has led to
the emergence of many application oriented protocols of
which LEACH is the most aspiring and widely used protocol
[5]. LEACH can be described as a combination of a cluster-
based architecture and multi-hop routing. The term cluster-
based can be explained by the fact that sensors using the
LEACH protocol functions are based on cluster heads and
cluster members. Multi-hop routing is used for inter-cluster
communication with cluster heads and base stations[7]. We
have stated that wireless sensorssense data,aggregatethem
and then send data to the base station from a remote area
using the radio transmission scheme as communication
medium. Data which is collected by the sensors is sent to the
base station. During this process a lot of problematic issues
occur, such as data collisionand the dataaggregation.LEACH
is well suited to reduce the data aggregation issues using a
local data fusion which performs a compression of the
amount of data that is collected by the cluster head before it
sends it to the base station. All sensors form a self-organized
network by sharing the role of a cluster head at least once.
Cluster head is majorly responsible for sending the data that
is collected by the sensors to the base station. It tries to
balance the energy dissipation within the network and
enhances the network’slifetime by improvingthelifetimeof
the sensors [6]. The operations that are carried out in the
LEACH protocol are divided into two stages, the setup phase
and the steady-state phase. Set-up Phase In the set up phase,
all the sensors within a network group themselves intosome
cluster regions by communicating with each other through
short messages. At a point of time one sensor in the network
acts as a cluster head and sends short messages within the
network to all the other remaining sensors. The sensors
choose to join those groups or regions that are formed by the
cluster heads, depending upon the signal strength of the
messages sent by the cluster heads. Sensors interested in
joining a particular cluster head or region respond back to
the cluster heads by sending a response signal indicating
their acceptance to join. Thusthe set-up phasecompletes[7].
The cluster head can decide the optimal number of cluster
members it can handle or requires. Before it enters the
steady-state phase, certain parameters are considered, such
as the networktopologyandtherelativecostsofcomputation
versus the communication. ATDMA Schedule isappliedtoall
the members of the cluster group to send messages to the
cluster head, and then to the cluster head towards the base
station.
Steady State Phase As soon as a cluster head is selected
for a region, all the cluster members of that region send the
collected or sensed data in their allotted TDMA slots to the
cluster head. The cluster head transmitsthiscollecteddatain
a compressed format to the base stationwhichcompletesthe
second phase, called the Steady StatePhase. Oncethesteady-
state finishes the data transmission to the sink, the whole
process comes to an end and a new search for the forming of
cluster heads foraregionandnewcluster-memberformation
begins. In short, it can be said that a new set/up phase and
steady state starts with the end of data transmission done to
the sink. This alternative selection ofclusterheadswithinthe
region, which is carriedamongthesensorsinaself-organized
way helps in reducing or lowering the energy that is utilized.
There is a possibility that all the sensors might not be too
close to the cluster head so the amount of energy that is
utilized by the farther sensor is not equal to the amount of
energy utilized by the nearest node.Inordertominimizethis,
cluster heads formation or the role of cluster head is
performed by a rotation among all the nodes in the group.
LEACH minimizes global energy usage by distributing the
load of the network to all the nodes or cluster members at
different intervals. All the cluster heads send the data which
is collected towards the basestation in a compressed format.
All the cluster heads may not be close to the base station so
they send the compressed data to the neighboring cluster
heads, and in this way, a multi-hop routing network is
formed. LEACH plays a randomized rotation of the cluster
head in order to save the high energy that is dissipated while
transmitting data to the base station.
3. PRAPOSED WORK
DEEC uses the initial and residual energy level of the
nodes for selecting the cluster-heads. DEEC evaluates the
ideal value of network life-time, which is used to calculate
the reference energy that each node should dissipate
throughout a round.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1390
Heterogeneous WSNs consist of two, three,ormultipletypes
sensor nodes in terms of energy levels, hardware structure,
and other special properties [8]. The DEEC protocol is based
on a two-level heterogeneous WSN in which the sensor
nodes are assumed to have normal and advanced battery
levels [9]. However, multilevel heterogeneity can be
considered for DEEC.E0 and E0a represent the initial energy
of a normal and advanced sensor node,
respectively. a indicates how many times energiesadvanced
node has been relative to the normal node. The numbers of
normal and advanced nodes in the network areNnml andNadv
respectively. So, total numbers of nodes (N) in WSN are
defined in
N=Nnml+Nadv
The total first energy (Enml) of the normal nodes in the WSN
is given in
Enml=NnmlE0
The total first energy of the advanced nodes in the WSN
(Eadv) is given in
Eadv=NadvE0a
Thus, the total first energy of the two-level heterogeneous
WSNs is calculated as given in
Etotal=Enml+Eadv
Heterogeneous WSN becomes homogenous after many
rounds due to the different energy dissipation of the sensor
nodes. CH consumes more energy than sensor nodes and
other member nodes. After several rounds, the energy level
of all sensor nodes changes relative to each other. For this
reason, a clustering network protocol that operates with
heterogeneity is more significant than a homogeneous
network method [8]. Energy consumption of a sensor node
involves models that consume energy so that it can perform
specific functions such as sensing, processing and wireless
communication of collected data [10,11,12]. These models
have become functional by making energy consumption
calculations. For the DEEC model, it includes the idea of the
probabilities of the nodes dependent on the start and the
remaining energy, in addition to the average energy of the
network when the CH selection is performed. The average
energy of the network is given as in (5) for r round.
Eavg=1/N Etotal (1-r/R)
As seen in (5), Eavg is found as Etotal is the total energy of
the N nodes and r. round in all rounds is defined as the
number of rounds r predicted according to the available
energy and energy consumed at the current round is given
by (6). Eround refers to the energy consumed for each round.
R=Etotal/Eround
At the beginning of each round, the decisionastowhether or
not the nodes are CH is decided by the threshold value. The
threshold value is recommended as in (7). It is important to
note that desired probability (Pi)is between 0 and 1, which
is the fraction remaining in the inverse of the Pi with r. This
is why mod is used. This residual is subtracted by 1
and T(Ki) is calculated.
11 mod ,( )
0
i
i
ii
i
p
if s G
p rT K p
otherwise

       
  

The selection for CH, G includes the appropriatesetofnodes,
Pi and is the desired possibility forCH. Si isi.node within the
cluster. The possibilities for CH selection in the DEEC model
are given in (8). Ei(r) is the energy of the node. Popt is used
constant probability for CH. In (8), because Eavg is
recalculated for each round, Eavg is important to be here. If it
is also assumed to be Ei(r)popt=Eavg, then the sum of all
possible states of Pi is 1. This case is also true for (11).
 
 
 
 
1
1
i opt
avg
i
i opt
avg
E r p
if normal node
a E
p
E r p a
if advanced node
a E



 

 
In this study, the DEEC model was designed as three levels
because the equilibrium heterogeneous structure was
considered in the simulation comparisons. Moreover, the
probability of CH selection in a multilevel heterogeneous
network model is as in
 
1
1opt
multi level N
i
i
p N a
p
N a



 
 
 

4. RESULTS
Fig 1:comparision of dead nodes LEACH vs DEEC
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1391
Fig 2:comparision of data transmission LEACH VS DEEC
5. CONCLUSIONS
In this research, we have discussed about
Distributed Energy-Efficient (DEEC) Protocol. DEEC is an
energy aware adaptive clusteringprotocol whichisdesigned
to deal with nodes of heterogeneous WSNs.ForCHselection,
DEEC uses initial and residual energy level of nodes. DEEC
evaluates the ideal value of network life-time, which is used
to calculate the reference energy that each node should
dissipate throughout a round. In DEEC, every sensor node
independently elects itself as a cluster-head based on its
initial energy and residual energy. To restraint the energy
disbursement ofnodesbymeansofadaptiveapproach,DEEC
use the average energy of the network as the reference
energy. Thus DEEC does not requireanyglobal knowledgeof
energy at every election round. Unlike LEACH, DEEC can
perform well in multi-level heterogeneous wireless sensor
networks.
REFERENCES
[1] Carlos de Morais Cordeiro, Dharma Prakash Agrawal
,Ad-hoc and sensor networks theory and
application,World Scientific publication,2006
[2] Paolo Santi, Topology control in wireless Ad-hoc and
Sensor networks, Jhon Wiley and son’s publication,
2005. J. Clerk Maxwell, A Treatise on Electricity and
Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892,
pp.68–73.
[3] Römer, Kay; Friedemann Mattern "The Design Space of
Wireless Sensor Networks” IEEE Wireless
Communications, Dec. 2004.
[4] Marcel Busse, Thomas Haenselmann, Wolfgang
Effelberg, “TECA: A Topology and Energy Control
Algorithm for Wireless Sensor Networks”, Proc. Of
ACM/IEEE International Symposium on Modeling,
Analysis and simulation of Wireless Mobile Systems,
Malaga, Spain, October 2006..
[5] Jichuan Zha, Ahmet T. Erdogan, and Tughrul Arslan, “A
Novel Application Specific Network Protocol for
Wireless Sensor Networks”, IEEE Reference number 0-
7803-8834- 8/05.
[6] Wendi B. Heinzelman,AnathanP.Chandraskan,andHari
Blakrisshnan, “An Application-Specific Protocol
Architecture for Wireless Microsensor Networks”, IEEE
Trans. on Wireless Communications, 1 (4): 660-670,
OCT 2002.
[7] WendiRabinerHeinzelman, Anantha Chandrakasan,and
Hari Balakrishnan, “Energy Efficient Communication
Protocol for WirelessMicrosensorNetworks”,Published
in the Proceedings of the Hawaii International
Conference on System Sciences,January4-7,2000,Maui,
Hawaii
[8] N. Javaid, T. N. Qureshi, A. H. Khan, A. Iqbal, E. Akhtar,
and M. Ishfaq, “EDDEEC: Enhanced Developed
Distributed Energy-Efficient Clustering for
Heterogeneous Wireless Sensor Networks,” Procedia
Computer Science, vol. 19, pp. 914–919, 2013.
[9] M. Aslam, E. U. Munir, M. M. Rafique, and X. Hu,
“Adaptive energy-efficient clustering path planning
routing protocols for heterogeneous wireless sensor
networks,” Sustainable Computing, vol. 12, pp. 57–71,
2016.
[10] M. Nicolae, D. Popescu, R. Dobrescu, and I. Costea,
“Scheduling mechanism for energy-efficient
communication in hybrid wireless sensor
networks,” Control Engineering and Applied
Informatics, vol. 18, no. 2, pp. 95–102, 2016.
[11] A. A. Babayo, M. H. Anisi, and I. Ali, “A Review on energy
management schemes in energy harvesting wireless
sensor networks,” Renewable & Sustainable Energy
Reviews, vol. 76, pp. 1176–1184, 2017.
[12] F. Engmann, F. A. Katsriku, J. Abdulai, K. S. Adu-Manu,
and F. K. Banaseka, “Prolonging the Lifetime of Wireless
Sensor Networks: A Review of Current
Techniques,” Wireless Communications and Mobile
Computing, vol. 2018, pp. 1–23, 2018.

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IRJET- Energy Efficient Protocol in Wireless Sensor Network

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1388 ENERGY EFFICIENT PROTOCOL IN WIRELESS SENSOR NETWORK M.V. Jitendra1, B.T. Krishna2 1Student, Dept. of ECE, ucek, JNTU Kakinada, AP, India 2Professor, Dept. of ECE, ucek, JNTU Kakinada, AP, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - A wireless sensor network is a group of tiny, generally battery powered devices and wirelessinfrastructure that monitor and record conditions in any environment. The Wireless sensor networks consists of number of sensor nodes connected each other and sense the data and transmits the data to the sink node. The sensor nodes in wireless sensor networks has limited energy, In LEACH (Low energy adaptive clustering hierarchy) every node has chance to become a CHs after 1/p rounds. All the nodes may not have same energy in cluster. So, the energy is not well distributed in the cluster and the low energy nodes will finish earlier than the high energy nodes. To improve the network life time DEEC (Distributive energy efficient clustering) is used. Key Words: wirelesssensor networks,energy efficient,node, LEACH, DEEC. 1. INTRODUCTION Now in recent scenario the growth of wireless communication is vast. Because the wireless technology can be applied in any kind of situation it has a capability of reaching in any part of the earth surface. There are so many wireless network are there, some are infrastructure based and some are infrastructure less.Ad-hoc andwirelesssensor network, cellular network are some example of wireless network. The term "wireless" has become a generic and all- encompassing word used to describe communications in which electromagnetic waves to carry a signal over part or the entire communicationpath.Wirelesstechnologycanable to reach virtually every location on the surface of the earth [1].Ad- hoc and Sensor Networks are one of the parts of the wireless communication. In ad-hoc network each and every nodes are allow tocommunicatewitheachotherwithout any fixed infrastructure. This is actually one of the features that differentiate between ad-hoc and other wireless technology like cellular networks and wireless LAN which actually required infrastructure based communication like through some base station. [2]. Wireless sensor network are one of the category belongs to ad-hoc networks. Sensor network are also composed of nodes. Here actually the node has a specific name that is “Sensor” because these nodes are equipped with smart sensors [2]. A sensor node is a device that converts a sensedcharacteristic liketemperature,vibrations, pressure into a form recognize by the users. Wirelesssensor networks nodes are less mobile than ad-hoc networks. So mobility in case of ad-hoc is more. In wireless sensor network data arerequested dependinguponcertainphysical quantity. So wireless sensor network is data centric. A sensor consists of a transducer, an embedded processor, small memory unit and a wireless transceiver and all these devices run on the power supplied by an attached battery. Advances in wireless communication made it possible to develop wireless sensor networks (WSN) consisting of small devices, which collect information by cooperating with each other. Thesesmall sensingdevices are called nodes and consist of CPU (for data processing), memory (for data storage), battery (for energy) and transceiver (for receiving and sending signals or data from one node to another). The size of each sensor node varies with applications. For example, in some military or surveillance applications it might be microscopically small. Its cost depends on its parameters like memory size, processing speed and battery [3]. Today, wireless sensor networks are widely used in the commercial and industrial areas such as for e.g. environmental monitoring, habitat monitoring, healthcare,processmonitoringandsurveillance. For example, in a military area, we can use wireless sensor networks to monitor an activity. If an event is triggered, these sensor nodes sense it and send the information to the base station (called sink) by communicating with other nodes. The use of wireless sensor networksisincreasing day by day and at the same time it faces the problem of energy constraints in terms of limited battery lifetime.Aseachnode depends on energy for its activities, this has become a major issue in wireless sensor networks. The failure of one node can interrupt the entire system or application.Everysensing node can be in active (for receiving and transmission activities), idle and sleep modes. In active mode nodes consume energy when receiving or transmitting data.Inidle mode, the nodes consume almostthesameamountof energy as in active mode, while in sleep mode, the nodes shutdown the radio to save the energy. 2. Literature survey The purpose of this project is to find protocols that are energy efficient and support real-time traffic for environments like habitat monitoring or area surveillance. Wireless sensor nodes which are battery operated are used fordetecting andcollectinginformationfromtheareaswhere there is very little scope for manual handling to recharge or change batteries. Thesesensingnodescollecttheinformation and pass them on to the network towards the sinkforfurther actions. For a better functioning and a longer lifetime for a sensing node within the network, we need to consider its energy consumption as a major factor of concern. Here these node detect and collects information regarding any object
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1389 that is moving or any event that’s triggered. The network carrying this information uses an ordinary protocol stack which carriesoutthegeneralprocessoftransmissionwithout any concerns for energy efficiency factor. Following are the assumptions for the surveillance applications in wirelesssensor networks which are usedasa frame of reference in the further study [4]. Wireless sensor networks consist of a number of sensing nodes which are distributed in a wide area. They sense an event occurring in the environment and these sensing nodes are distributed or placed according to the requirements of the application. The base station (sink), which collects data from other nodes, interacts with a user (someone interested in monitoring the activity). Data can be collected in many ways from a sensing node to a sink node like using hopping techniques or transmitting data at certain frequencies. Sinks have more advanced features than sensing nodes in terms of data transmissions and processing capabilities, memory size and energy reserves. There can be multiplesinksforanetworkso that there is no single point of failure. Energy dissipation is a major factor in WSNs during communication among the nodes. Energy should be saved, so that the batteries do not get depleted or drained quickly as these are not easily replaceable in applications such as surveillance. Quality of service ensures the effectivecommunicationwithinthegiven or bounded delay time. Protocols should check for network stability, redundant data should be transmitted over the network for any type of traffic distribution. It also needs to maintaincertainresourcelimitingfactors,suchasbandwidth, memory buffer size and processing capabilities. The transmission mode plays an important role in WSNs. Nodes can take single-hop or multi-hop depending upon the type of network topologychosen for communicatingortransmitting data to other nodes within the network. In surveillance applications, sensor nodes are placed in unattended areas so it should be self-organizing and self-creating. LEACH (Low Energy Adaptive Clustering Hierarchical) The current interest in wireless sensor networks has led to the emergence of many application oriented protocols of which LEACH is the most aspiring and widely used protocol [5]. LEACH can be described as a combination of a cluster- based architecture and multi-hop routing. The term cluster- based can be explained by the fact that sensors using the LEACH protocol functions are based on cluster heads and cluster members. Multi-hop routing is used for inter-cluster communication with cluster heads and base stations[7]. We have stated that wireless sensorssense data,aggregatethem and then send data to the base station from a remote area using the radio transmission scheme as communication medium. Data which is collected by the sensors is sent to the base station. During this process a lot of problematic issues occur, such as data collisionand the dataaggregation.LEACH is well suited to reduce the data aggregation issues using a local data fusion which performs a compression of the amount of data that is collected by the cluster head before it sends it to the base station. All sensors form a self-organized network by sharing the role of a cluster head at least once. Cluster head is majorly responsible for sending the data that is collected by the sensors to the base station. It tries to balance the energy dissipation within the network and enhances the network’slifetime by improvingthelifetimeof the sensors [6]. The operations that are carried out in the LEACH protocol are divided into two stages, the setup phase and the steady-state phase. Set-up Phase In the set up phase, all the sensors within a network group themselves intosome cluster regions by communicating with each other through short messages. At a point of time one sensor in the network acts as a cluster head and sends short messages within the network to all the other remaining sensors. The sensors choose to join those groups or regions that are formed by the cluster heads, depending upon the signal strength of the messages sent by the cluster heads. Sensors interested in joining a particular cluster head or region respond back to the cluster heads by sending a response signal indicating their acceptance to join. Thusthe set-up phasecompletes[7]. The cluster head can decide the optimal number of cluster members it can handle or requires. Before it enters the steady-state phase, certain parameters are considered, such as the networktopologyandtherelativecostsofcomputation versus the communication. ATDMA Schedule isappliedtoall the members of the cluster group to send messages to the cluster head, and then to the cluster head towards the base station. Steady State Phase As soon as a cluster head is selected for a region, all the cluster members of that region send the collected or sensed data in their allotted TDMA slots to the cluster head. The cluster head transmitsthiscollecteddatain a compressed format to the base stationwhichcompletesthe second phase, called the Steady StatePhase. Oncethesteady- state finishes the data transmission to the sink, the whole process comes to an end and a new search for the forming of cluster heads foraregionandnewcluster-memberformation begins. In short, it can be said that a new set/up phase and steady state starts with the end of data transmission done to the sink. This alternative selection ofclusterheadswithinthe region, which is carriedamongthesensorsinaself-organized way helps in reducing or lowering the energy that is utilized. There is a possibility that all the sensors might not be too close to the cluster head so the amount of energy that is utilized by the farther sensor is not equal to the amount of energy utilized by the nearest node.Inordertominimizethis, cluster heads formation or the role of cluster head is performed by a rotation among all the nodes in the group. LEACH minimizes global energy usage by distributing the load of the network to all the nodes or cluster members at different intervals. All the cluster heads send the data which is collected towards the basestation in a compressed format. All the cluster heads may not be close to the base station so they send the compressed data to the neighboring cluster heads, and in this way, a multi-hop routing network is formed. LEACH plays a randomized rotation of the cluster head in order to save the high energy that is dissipated while transmitting data to the base station. 3. PRAPOSED WORK DEEC uses the initial and residual energy level of the nodes for selecting the cluster-heads. DEEC evaluates the ideal value of network life-time, which is used to calculate the reference energy that each node should dissipate throughout a round.
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1390 Heterogeneous WSNs consist of two, three,ormultipletypes sensor nodes in terms of energy levels, hardware structure, and other special properties [8]. The DEEC protocol is based on a two-level heterogeneous WSN in which the sensor nodes are assumed to have normal and advanced battery levels [9]. However, multilevel heterogeneity can be considered for DEEC.E0 and E0a represent the initial energy of a normal and advanced sensor node, respectively. a indicates how many times energiesadvanced node has been relative to the normal node. The numbers of normal and advanced nodes in the network areNnml andNadv respectively. So, total numbers of nodes (N) in WSN are defined in N=Nnml+Nadv The total first energy (Enml) of the normal nodes in the WSN is given in Enml=NnmlE0 The total first energy of the advanced nodes in the WSN (Eadv) is given in Eadv=NadvE0a Thus, the total first energy of the two-level heterogeneous WSNs is calculated as given in Etotal=Enml+Eadv Heterogeneous WSN becomes homogenous after many rounds due to the different energy dissipation of the sensor nodes. CH consumes more energy than sensor nodes and other member nodes. After several rounds, the energy level of all sensor nodes changes relative to each other. For this reason, a clustering network protocol that operates with heterogeneity is more significant than a homogeneous network method [8]. Energy consumption of a sensor node involves models that consume energy so that it can perform specific functions such as sensing, processing and wireless communication of collected data [10,11,12]. These models have become functional by making energy consumption calculations. For the DEEC model, it includes the idea of the probabilities of the nodes dependent on the start and the remaining energy, in addition to the average energy of the network when the CH selection is performed. The average energy of the network is given as in (5) for r round. Eavg=1/N Etotal (1-r/R) As seen in (5), Eavg is found as Etotal is the total energy of the N nodes and r. round in all rounds is defined as the number of rounds r predicted according to the available energy and energy consumed at the current round is given by (6). Eround refers to the energy consumed for each round. R=Etotal/Eround At the beginning of each round, the decisionastowhether or not the nodes are CH is decided by the threshold value. The threshold value is recommended as in (7). It is important to note that desired probability (Pi)is between 0 and 1, which is the fraction remaining in the inverse of the Pi with r. This is why mod is used. This residual is subtracted by 1 and T(Ki) is calculated. 11 mod ,( ) 0 i i ii i p if s G p rT K p otherwise              The selection for CH, G includes the appropriatesetofnodes, Pi and is the desired possibility forCH. Si isi.node within the cluster. The possibilities for CH selection in the DEEC model are given in (8). Ei(r) is the energy of the node. Popt is used constant probability for CH. In (8), because Eavg is recalculated for each round, Eavg is important to be here. If it is also assumed to be Ei(r)popt=Eavg, then the sum of all possible states of Pi is 1. This case is also true for (11).         1 1 i opt avg i i opt avg E r p if normal node a E p E r p a if advanced node a E         In this study, the DEEC model was designed as three levels because the equilibrium heterogeneous structure was considered in the simulation comparisons. Moreover, the probability of CH selection in a multilevel heterogeneous network model is as in   1 1opt multi level N i i p N a p N a           4. RESULTS Fig 1:comparision of dead nodes LEACH vs DEEC
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 08 | Aug 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1391 Fig 2:comparision of data transmission LEACH VS DEEC 5. CONCLUSIONS In this research, we have discussed about Distributed Energy-Efficient (DEEC) Protocol. DEEC is an energy aware adaptive clusteringprotocol whichisdesigned to deal with nodes of heterogeneous WSNs.ForCHselection, DEEC uses initial and residual energy level of nodes. DEEC evaluates the ideal value of network life-time, which is used to calculate the reference energy that each node should dissipate throughout a round. In DEEC, every sensor node independently elects itself as a cluster-head based on its initial energy and residual energy. To restraint the energy disbursement ofnodesbymeansofadaptiveapproach,DEEC use the average energy of the network as the reference energy. Thus DEEC does not requireanyglobal knowledgeof energy at every election round. Unlike LEACH, DEEC can perform well in multi-level heterogeneous wireless sensor networks. REFERENCES [1] Carlos de Morais Cordeiro, Dharma Prakash Agrawal ,Ad-hoc and sensor networks theory and application,World Scientific publication,2006 [2] Paolo Santi, Topology control in wireless Ad-hoc and Sensor networks, Jhon Wiley and son’s publication, 2005. J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73. [3] Römer, Kay; Friedemann Mattern "The Design Space of Wireless Sensor Networks” IEEE Wireless Communications, Dec. 2004. [4] Marcel Busse, Thomas Haenselmann, Wolfgang Effelberg, “TECA: A Topology and Energy Control Algorithm for Wireless Sensor Networks”, Proc. Of ACM/IEEE International Symposium on Modeling, Analysis and simulation of Wireless Mobile Systems, Malaga, Spain, October 2006.. [5] Jichuan Zha, Ahmet T. Erdogan, and Tughrul Arslan, “A Novel Application Specific Network Protocol for Wireless Sensor Networks”, IEEE Reference number 0- 7803-8834- 8/05. [6] Wendi B. Heinzelman,AnathanP.Chandraskan,andHari Blakrisshnan, “An Application-Specific Protocol Architecture for Wireless Microsensor Networks”, IEEE Trans. on Wireless Communications, 1 (4): 660-670, OCT 2002. [7] WendiRabinerHeinzelman, Anantha Chandrakasan,and Hari Balakrishnan, “Energy Efficient Communication Protocol for WirelessMicrosensorNetworks”,Published in the Proceedings of the Hawaii International Conference on System Sciences,January4-7,2000,Maui, Hawaii [8] N. Javaid, T. N. Qureshi, A. H. Khan, A. Iqbal, E. Akhtar, and M. Ishfaq, “EDDEEC: Enhanced Developed Distributed Energy-Efficient Clustering for Heterogeneous Wireless Sensor Networks,” Procedia Computer Science, vol. 19, pp. 914–919, 2013. [9] M. Aslam, E. U. Munir, M. M. Rafique, and X. Hu, “Adaptive energy-efficient clustering path planning routing protocols for heterogeneous wireless sensor networks,” Sustainable Computing, vol. 12, pp. 57–71, 2016. [10] M. Nicolae, D. Popescu, R. Dobrescu, and I. Costea, “Scheduling mechanism for energy-efficient communication in hybrid wireless sensor networks,” Control Engineering and Applied Informatics, vol. 18, no. 2, pp. 95–102, 2016. [11] A. A. Babayo, M. H. Anisi, and I. Ali, “A Review on energy management schemes in energy harvesting wireless sensor networks,” Renewable & Sustainable Energy Reviews, vol. 76, pp. 1176–1184, 2017. [12] F. Engmann, F. A. Katsriku, J. Abdulai, K. S. Adu-Manu, and F. K. Banaseka, “Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques,” Wireless Communications and Mobile Computing, vol. 2018, pp. 1–23, 2018.