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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 742
Chaos based Secured Communication in Energy Efficient Wireless
Sensor Networks
Nidarsh M P1, Mrs. G Padmaja Devi2
1 PG Scholar, Dept.of E&C, Malnad college of engineering, Karnataka, India
2 Associate Professor, Dept.of E&C, Malnad college of engineering, Karnataka, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Wireless sensor networks has a important role in
recent network technology, WSN which contains number of
sensor nodes used to monitor physical and environmental
condition such as temperature, sound, vibration, pressure,
humidity, motion or pollutants, further it sends their data
through the network to main location. Some of the sensor
nodes are furnished with supported battery power through
which it can furnish ample of operation and it can also
communicate with other nodes. Increasing the lifetime of the
wireless sensor network, power management part is essential
for improving the performance of WSN. This paper proposesa
chaotic encryptionwithclusteredLowEnergyAdoptiveCluster
Head (LEACH) algorithm for wireless energy efficient
networks which also reduces the consumption in WSN. The
performance of the proposed work is evaluated and
comparison is done.
Key Words: WSN, LEACH, Energy efficiency, network
lifetime, chaotic encryption.
1. INTRODUCTION
Wireless Sensor Network is a type of network which self-
organizes with a huge number of small sensors. The main
aim of sensor node is to complete the packet transmission
among itself within the network area, whichcanidentifyand
notice the physical entity of real world environment. WSN
contain of various number of sensor nodeswhichcanfurther
sense their locality and contact among themselves. Main
characteristics of WSN nodes are contains tiny size,
reasonable cost, lessconsumptionofpower,multi-functional
such as it can perform sensing ,data processing, routing and
communicate easily in short distances. Inabandonedhostile
regions, these devices are implemented in general, but it
becomes difficult to recharge the power source.
With the help of multiple clusters,sensor nodesaredesigned
and organized in a proper manner. The cluster head is
selected by several group of nodes,hereeachand everynode
can act has part of message transfer in between multiple
nodes. At last, all nodes will go for sharing messages to base
station by cluster head. Sensornetworksalwayspreferredto
use cluster design, this in turn help us to capture for data
gather and fusion operations by each of sensor nodes. It
exchange message with cluster head which is going to send
message to its nearest base station. The following figure 1
shows actual formation of cluster heads and selection of
those are independent to each other.
Fig -1: Cluster formation
In current situation of WSN correct use of battery power is
not up to the mark, due to which there will be dissimilarity
while sending the message to destination node from source
node. So multi hop communication plays a major role as a
part of its requirements. Sometimes it’s preferred to use
hierarchical routing during data transmission in order to
improve sensor network lifetime. Cluster can be made by
collecting group of nodes which helps to build hierarchical
routing and cluster head to be selected by every clusterinits
corresponding network. As a part of data transmission,
cluster head liable for data collection from adjacent nodes
and base station will go for receiving data.
2. RELATED WORK
WSN facing its own challenges and issues can be identified
by the researchers. To improve the network life time, many
protocols have been followed. Here [1] introduced the
protocol called Low Energy Adoptive Cluster Head [LEACH].
Hence it help us to get improved the energy performance of
network. Drawback here is that the performance is notupto
the mark D.Aradhana, NagaveniB.BiradarandK.LingaRaj[2]
proposed the novel method to get more number of clusters
from the network. Here, they were using mobileagentsfrom
every cluster for sending data to cluster head instead of
choosing nodes. These mobilenodeswill collectdata from all
the nodes belong to network with that aggregation of data
can be performed. The aggregated data will be received by
the base station. The two components play a major role in
this method, such as group array and ordinal array.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 743
Clustering has been broadly considered in the network
literature as well as in information processing [3–5].
N Eghbali [6] deals with nodes are facing problems like lack
of unique address in sensor network and it is most
important for collecting information from the sensors. Once
the nodes have got dispersed, accesses to corresponding
nodes get delayed. The nodes present in the network will
become useless and leads to decay behind the obtained
energy gets over. Hence the issues related to energy
consumption and optimization isa greaterchallengefacedin
real time network applications.Recentlylotsmorehavebeen
appreciated towards it. D. T. Ho, T. A. Johansen, J. B. D. Sousa,
E. I. Grøtli and P. B. Sujit, [7], done a comparison with earlier
papers, this paper have an enhanced method. First of all
using a special scheme called PSO and its get modified with
optimal path selection for relay data. This paper uses a
mixture of two multiple access methods to achieve
communication such as TDMA and CSMA/CA and
performance comparison can be done in better way.
Prof. Rajeev Vishwakarma, Apurva Bhalerao [8] discussed
the concept of gaining reliability andenergyconsumption by
doing setup of wireless sensor network in simulation. Based
on some parameters of WSN, deciding the network stability
in terms of energy and its existence. The particle swarm
optimization is taken into consideration for optimizing the
update time and hop distance. In order to improve the
performance of WSN, the following parameters to be
considered such as transmission power, used frequency,
modulation technique and so on. NING WANG, WEI XIANG
AND YUAN ZHOU, (Senior Member, IEEE) [9] illustrate the
new method for to extend the lifetime of network using
advanced particle swarm optimization algorithm. This is
used to choose target nodes as a processofoptimization. The
set of rules formed to get better results for parameters like
transmission distance and energy efficiency. This paper
proposes a distributed sensor in better way and balanced
system for clusters to enhance the network lifetime. In early
days, optimal cluster layout can be obtained by applying
several fitness functions with the use of PSO [10-12].
Wireless sensor network is have some clustering problems,
PSO act has a solution to those problems by embedding it
into some other algorithms [13]. Alaa SHETA, Basma Fathi
SOLAIMAN [14] addressed the WSN problem facing to use
energy resources efficiently and minimizing traffic during
transmission by applying balanced load distribution. To
solve this type of problem, proposed a new way of finding
optimal distribution of cluster heads and sensors. Hence,
consumption of energy inversely proposed to lifetime of
network. This paper comes with the idea of introducing
hybrid cluster algorithm with the help of particle swarm
optimization and K-means clustering.
3. METHODOLOGY
Cluster head selection algorithm:
Step-1: Create Sensor Network Model.
Step-2: Assign initial energy to sensor nodes.
Step-3: Sort the nodes based on the distance from Base
station.
Step-4: For round=1 assign cluster heads based on minimum
distance from the base-station.
Step-5: Continue step-4 for allotted number of round and
corresponding cluster heads get selected.
3.1 LEACH PROTOCOL
LEACH is network protocol and much essential to
use. Since some nodes present in network is not at all useful
when the battery dies. The LEACH protocol let us to find out
the nodes lifespan and permitting to do minimal work it
essentially used for data transmission
Fig -2: Direct v/s Minimum transmission
The energy used in direct transmission can be modeled by
dk(3d1+d2)2
Whereas energy used for minimum transmissioncanalsobe
modeled using
dk(3d12+d22)
Where d is energy dissipation
k is length of message in bits
Usually LEACH network is having two different stages
such as set-up stage and steady stage. The set-up stage is
meant for cluster heads selection and steady stage is used to
maintain the cluster heads when the transmission of data is
happening among nodes within the network. The Figure4
shows clear cut idea about using LEACH protocol by
comparing with other cases. Here, second gives better
arrangement since the network is accurately sectioned and
neatly spaced out the cluster heads.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 744
Fig -3: LEACH v/s bad-case scenario
3.2 CHAOTIC CRYPTOGRAPHY
3.2.1 Two Dimensional Logistic Map
The two dimensional logistic map is well known for
its complicated chaotic behavior when compared to the one
dimensional logistic map. It takes the input , and in a
plane and maps it to a new point. Mathematically it can be
defined as
(1)
(2)
Where is the system parameter , are the pair wise
points. The map depends on three values namely ,
and whose corresponding initial values are r =1.19 ,
and .
3.2.2 Three Dimensional Lorenz Map
The Lorenz equation can be represented in
differential equations having chaotic behavior for certain
parameters with initial conditions. Mathematically it can be
defined as
(3)
(4)
(5)
The System exhibits chaotic behavior when the parameters
are having values , and
Table -1: Network Security Initial Conditions Parameters
3.2.3 Encryption Scheme
The proposed algorithm consists of two phases. The
first phase includes Confusion which scramblesthedata and
the second phase includes Diffusion which modifiesthedata
based on the chaotic sequences.Theproposedcryptosystem
is shown in Fig 1.
Fig -4: Network Encryption Scheme
Chaotic Maps Initial Conditions
2D Logistic Map
= 0.1
= 0.1
3D Lorenz Map
= 0.1
= 0.1
s=10
b=8/3
Input
Node
Informa
tion
Sequence
Key
1
Conf
usion
Diffu
sion
Encry
pted
Data
Key
2
Sequence
Logistic
Map
Lorenz
Map
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 745
3.2.4 Confusion
For a byte level confusion is done by interchanging the
positions of the information based on the chaotic sequence
generated by 2D logistic map.
The Nodal information X (row matrix) of size 1xN is takenas
input for confusion.
The chaotic sequence are generated by 2D logistic map and
arrange them in a row matrix of size Mx1. Sort the obtained
chaotic sequence in the ascendingorderandtheindexvalues
are obtained in L1.
The rows of matrix X are shuffled based on the index values
of L1 to achieve matrix Y.
3.2.5 Diffusion
Diffusion includes logical XOR operation between the
confused data Y and the matrix containing the chaotic
sequences obtainedfromthe three-dimensional Lorenzmap.
Generate chaotic sequences from the three-dimensional
Lorenz map.
Convert the obtained sequences into integer value ranges
from 0 to 255 and store them in a matrix Z1.
Logical XOR is performed between confused data Y with the
matrix obtained from Lorenz map Z1 to achievematrixH1 of
size 1xN.
The obtained encrypted matrix H1 is ready to transfer over
the network.
Fig -5: Block diagram of the proposed encryption
technique
3.3 LIFE TIME OF THE CHAOS NETWORK
The proposed research work is further extended to
evaluate the life time of the network. It includes energy
conservation in each and every sensor node by makes use of
clustering and supporting cluster head selection energy
optimization algorithm. The supporting cluster head is
chosen based on residual energy. To increase the WSN
lifetime, energy optimization techniques and energy
conservation measures are enhanced.
Parameters Initial Values
Number of Nodes 100
Base station Location (100,100)
Packet Length 2000
Initial Energy (E0) 2 Joules
Tx Energy (ETX) 50 x 10-9 Joules
Rx Energy (ERX) 50 x 10-9 Joules
Data Aggregation Energy 5 x 10-9 Joules
Table -2: Energy Efficient Network Parameters
4. RESULTS AND DISCUSSIONS
Fig -6: Distribution of Nodes and Cluster Formation
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 746
Fig -7: Residual Energy versus Number of Iterations
Fig -8: Number of Alive Nodes versus Number of
Iterations
Fig -9: Energy Variance versus Number of Iterations
In order to evaluate the effect of network security on
network life timevariousperformancemetricsaremeasured
and compared with traditional LEACH technique. Residual
Energy is evaluated in Figure 7 for both chaos based
Clustered WSN and traditional LEACH algorithm and it is
shown that Energy reduction is less when compared to
LEACH. Figure 8 shows number of alive nodes when
compared with the LEACH system.
Figure 9 shows Average energy variance of all nodeshasless
significant using proposed chaos based WSN.
5. CONCLUSIONS
The performance of WSN is improved by LEACH based
clustering and cluster head selection method algorithms by
increasing the residual energy,throughput,quantityofactive
nodes and packet delivery ratio. The better clustering
algorithm builds clusters in a centralized manner within a
base station and choice of cluster heads by using LEACH in
dispersed manner. The performance metrics such as
network lifetime, throughput, packet delivery ratio, delay,
normalizedoverhead,total energyconsumptionandresidual
energy are estimated and compared with advanced
clustering methodology. The simulation result shows that
the projected Chaotic Encryption with Clustered LEACH
scheme gives improved performance in order to reduce the
total energy consumption and increasing the lifetime of
WSN.
REFERENCES
[1] Liu, Z., Liu, Z., and Wen, L. (2011). “A leach protocol
for wireless sensor networks. In Advanced
Computational Intelligence (IWACI)”,2011 Fourth
International Workshop on, pages 766-769.
[2] K. LingaRaj, D. Aradhana and Nagaveni B.Biradar,
“Multiple mobile agents in wireless sensor networks
using genetic algorithms”, International Journal of
Scientific and EngineeringResearch,vol3,2012,pp1–
5.
[3] Low CP, Fang C, Mee J, Ang, YH. Load-balanced
clustering algorithms for wireless sensor networks.
In: IEEE International Conference on
Communications; 24–28 June 2007; Glasgow, UK.
New York, NY, USA: IEEE. pp. 3485-3490.
[4] Gavalas D, Mpitziopoulos A, Pantziou G,
Konstantopoulos C. An approach for near-optimal
distributed data fusion in wireless sensor networks.
Wirel Netw 2010; 16: 1407-1425.
[5] Tan R, Xing G, Li, B, Wang J, Jia X. Exploiting data
fusion to improve the coverage of wireless sensor
networks. IEEE/ACM Tr Netw 2012; 20: 450-462.
[6] N.Eghbali,”PerformanceImprovementofInformation
Dissemination Protocols in Sensor Networks
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 747
Through Data Aggregation, Computer Engineering
andInformationTechnologyDepartment”,2007.PP1-
121.
[7] D. T. Ho, E. I. Grøtli, P. B. Sujit, T. A. Johansen, and J. B.
D. Sousa, “Cluster-based communication topology
selection and UAV path planning in wireless sensor
networks,” in Proc. of International Conference on
Unmanned Aircraft Systems (ICUAS). Atlanta, GA,
USA: IEEE, 2013.
[8] Prof. Rajeev Vishwakarma, Apurva Bhalerao,
“Performance of Wireless Sensor Network using
Particle Swarm Optimization Algorithm”,
International Journal of Computer Application
(2250-1797) Volume 6– No.1, January- February
2016.
[9] YUAN ZHOU, (Senior Member, IEEE), NING WANG,
AND WEI XIANG, (Senior Member, IEEE),“Clustering
Hierarchy Protocol in Wireless Sensor Networks
Using an Improved PSO Algorithm”, date of
publication December 1, 2016, date of current
version March 13, 2017.
[10] Latiff N, Tsimenidis C, Sharif B. Energy-aware
clustering for wireless sensor networks using
particle swarm optimization. In: IEEE 18th
International Symposium on Personal, Indoor and
Mobile RadioCommunications;3–7September2007;
Athens, Greece. New York, NY, USA: IEEE. pp. 1-5.
[11] Hou J, Fan X, Wang W, Jie J, Wang Y. Clustering
strategy of wireless sensor networks based on
improved discrete particle swarm optimization. In:
IEEE Sixth International Conference on Natural
Computation; 10–12 August 2010; Yantai, China.
New York, NY, USA: IEEE. pp. 3866-3870.
[12] Kulkarni R, Venayagamoorthy G. Particle swarm
optimization in wireless sensor networks: a brief
survey. IEEE TSyst Man Cy C 2011; 41: 262-267.
[13] KarthikeyanM,VenkatalakshmiK.Energy conscious
clustering of wireless sensor network using PSO
incorporated cuckoo search. In: IEEE Third
International Conference on Computing
Communication Networking Technologies; 26–28
July 2012; Coimbatore, India. New York, NY, USA:
IEEE. pp. 1-7.
[14] Basma Fathi SOLAIMAN,, Alaa SHETA, “Energy
optimization in wireless sensor networks using a
hybrid K-means PSO clustering algorithm”, Turk
Journal of Electrical Engineering & Computer
Science(2016) 24: 2679 – 2695,doi:10.3906/elk-
1403-293.

More Related Content

IRJET- Chaos based Secured Communication in Energy Efficient Wireless Sensor Networks

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 742 Chaos based Secured Communication in Energy Efficient Wireless Sensor Networks Nidarsh M P1, Mrs. G Padmaja Devi2 1 PG Scholar, Dept.of E&C, Malnad college of engineering, Karnataka, India 2 Associate Professor, Dept.of E&C, Malnad college of engineering, Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Wireless sensor networks has a important role in recent network technology, WSN which contains number of sensor nodes used to monitor physical and environmental condition such as temperature, sound, vibration, pressure, humidity, motion or pollutants, further it sends their data through the network to main location. Some of the sensor nodes are furnished with supported battery power through which it can furnish ample of operation and it can also communicate with other nodes. Increasing the lifetime of the wireless sensor network, power management part is essential for improving the performance of WSN. This paper proposesa chaotic encryptionwithclusteredLowEnergyAdoptiveCluster Head (LEACH) algorithm for wireless energy efficient networks which also reduces the consumption in WSN. The performance of the proposed work is evaluated and comparison is done. Key Words: WSN, LEACH, Energy efficiency, network lifetime, chaotic encryption. 1. INTRODUCTION Wireless Sensor Network is a type of network which self- organizes with a huge number of small sensors. The main aim of sensor node is to complete the packet transmission among itself within the network area, whichcanidentifyand notice the physical entity of real world environment. WSN contain of various number of sensor nodeswhichcanfurther sense their locality and contact among themselves. Main characteristics of WSN nodes are contains tiny size, reasonable cost, lessconsumptionofpower,multi-functional such as it can perform sensing ,data processing, routing and communicate easily in short distances. Inabandonedhostile regions, these devices are implemented in general, but it becomes difficult to recharge the power source. With the help of multiple clusters,sensor nodesaredesigned and organized in a proper manner. The cluster head is selected by several group of nodes,hereeachand everynode can act has part of message transfer in between multiple nodes. At last, all nodes will go for sharing messages to base station by cluster head. Sensornetworksalwayspreferredto use cluster design, this in turn help us to capture for data gather and fusion operations by each of sensor nodes. It exchange message with cluster head which is going to send message to its nearest base station. The following figure 1 shows actual formation of cluster heads and selection of those are independent to each other. Fig -1: Cluster formation In current situation of WSN correct use of battery power is not up to the mark, due to which there will be dissimilarity while sending the message to destination node from source node. So multi hop communication plays a major role as a part of its requirements. Sometimes it’s preferred to use hierarchical routing during data transmission in order to improve sensor network lifetime. Cluster can be made by collecting group of nodes which helps to build hierarchical routing and cluster head to be selected by every clusterinits corresponding network. As a part of data transmission, cluster head liable for data collection from adjacent nodes and base station will go for receiving data. 2. RELATED WORK WSN facing its own challenges and issues can be identified by the researchers. To improve the network life time, many protocols have been followed. Here [1] introduced the protocol called Low Energy Adoptive Cluster Head [LEACH]. Hence it help us to get improved the energy performance of network. Drawback here is that the performance is notupto the mark D.Aradhana, NagaveniB.BiradarandK.LingaRaj[2] proposed the novel method to get more number of clusters from the network. Here, they were using mobileagentsfrom every cluster for sending data to cluster head instead of choosing nodes. These mobilenodeswill collectdata from all the nodes belong to network with that aggregation of data can be performed. The aggregated data will be received by the base station. The two components play a major role in this method, such as group array and ordinal array.
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 743 Clustering has been broadly considered in the network literature as well as in information processing [3–5]. N Eghbali [6] deals with nodes are facing problems like lack of unique address in sensor network and it is most important for collecting information from the sensors. Once the nodes have got dispersed, accesses to corresponding nodes get delayed. The nodes present in the network will become useless and leads to decay behind the obtained energy gets over. Hence the issues related to energy consumption and optimization isa greaterchallengefacedin real time network applications.Recentlylotsmorehavebeen appreciated towards it. D. T. Ho, T. A. Johansen, J. B. D. Sousa, E. I. Grøtli and P. B. Sujit, [7], done a comparison with earlier papers, this paper have an enhanced method. First of all using a special scheme called PSO and its get modified with optimal path selection for relay data. This paper uses a mixture of two multiple access methods to achieve communication such as TDMA and CSMA/CA and performance comparison can be done in better way. Prof. Rajeev Vishwakarma, Apurva Bhalerao [8] discussed the concept of gaining reliability andenergyconsumption by doing setup of wireless sensor network in simulation. Based on some parameters of WSN, deciding the network stability in terms of energy and its existence. The particle swarm optimization is taken into consideration for optimizing the update time and hop distance. In order to improve the performance of WSN, the following parameters to be considered such as transmission power, used frequency, modulation technique and so on. NING WANG, WEI XIANG AND YUAN ZHOU, (Senior Member, IEEE) [9] illustrate the new method for to extend the lifetime of network using advanced particle swarm optimization algorithm. This is used to choose target nodes as a processofoptimization. The set of rules formed to get better results for parameters like transmission distance and energy efficiency. This paper proposes a distributed sensor in better way and balanced system for clusters to enhance the network lifetime. In early days, optimal cluster layout can be obtained by applying several fitness functions with the use of PSO [10-12]. Wireless sensor network is have some clustering problems, PSO act has a solution to those problems by embedding it into some other algorithms [13]. Alaa SHETA, Basma Fathi SOLAIMAN [14] addressed the WSN problem facing to use energy resources efficiently and minimizing traffic during transmission by applying balanced load distribution. To solve this type of problem, proposed a new way of finding optimal distribution of cluster heads and sensors. Hence, consumption of energy inversely proposed to lifetime of network. This paper comes with the idea of introducing hybrid cluster algorithm with the help of particle swarm optimization and K-means clustering. 3. METHODOLOGY Cluster head selection algorithm: Step-1: Create Sensor Network Model. Step-2: Assign initial energy to sensor nodes. Step-3: Sort the nodes based on the distance from Base station. Step-4: For round=1 assign cluster heads based on minimum distance from the base-station. Step-5: Continue step-4 for allotted number of round and corresponding cluster heads get selected. 3.1 LEACH PROTOCOL LEACH is network protocol and much essential to use. Since some nodes present in network is not at all useful when the battery dies. The LEACH protocol let us to find out the nodes lifespan and permitting to do minimal work it essentially used for data transmission Fig -2: Direct v/s Minimum transmission The energy used in direct transmission can be modeled by dk(3d1+d2)2 Whereas energy used for minimum transmissioncanalsobe modeled using dk(3d12+d22) Where d is energy dissipation k is length of message in bits Usually LEACH network is having two different stages such as set-up stage and steady stage. The set-up stage is meant for cluster heads selection and steady stage is used to maintain the cluster heads when the transmission of data is happening among nodes within the network. The Figure4 shows clear cut idea about using LEACH protocol by comparing with other cases. Here, second gives better arrangement since the network is accurately sectioned and neatly spaced out the cluster heads.
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 744 Fig -3: LEACH v/s bad-case scenario 3.2 CHAOTIC CRYPTOGRAPHY 3.2.1 Two Dimensional Logistic Map The two dimensional logistic map is well known for its complicated chaotic behavior when compared to the one dimensional logistic map. It takes the input , and in a plane and maps it to a new point. Mathematically it can be defined as (1) (2) Where is the system parameter , are the pair wise points. The map depends on three values namely , and whose corresponding initial values are r =1.19 , and . 3.2.2 Three Dimensional Lorenz Map The Lorenz equation can be represented in differential equations having chaotic behavior for certain parameters with initial conditions. Mathematically it can be defined as (3) (4) (5) The System exhibits chaotic behavior when the parameters are having values , and Table -1: Network Security Initial Conditions Parameters 3.2.3 Encryption Scheme The proposed algorithm consists of two phases. The first phase includes Confusion which scramblesthedata and the second phase includes Diffusion which modifiesthedata based on the chaotic sequences.Theproposedcryptosystem is shown in Fig 1. Fig -4: Network Encryption Scheme Chaotic Maps Initial Conditions 2D Logistic Map = 0.1 = 0.1 3D Lorenz Map = 0.1 = 0.1 s=10 b=8/3 Input Node Informa tion Sequence Key 1 Conf usion Diffu sion Encry pted Data Key 2 Sequence Logistic Map Lorenz Map
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 745 3.2.4 Confusion For a byte level confusion is done by interchanging the positions of the information based on the chaotic sequence generated by 2D logistic map. The Nodal information X (row matrix) of size 1xN is takenas input for confusion. The chaotic sequence are generated by 2D logistic map and arrange them in a row matrix of size Mx1. Sort the obtained chaotic sequence in the ascendingorderandtheindexvalues are obtained in L1. The rows of matrix X are shuffled based on the index values of L1 to achieve matrix Y. 3.2.5 Diffusion Diffusion includes logical XOR operation between the confused data Y and the matrix containing the chaotic sequences obtainedfromthe three-dimensional Lorenzmap. Generate chaotic sequences from the three-dimensional Lorenz map. Convert the obtained sequences into integer value ranges from 0 to 255 and store them in a matrix Z1. Logical XOR is performed between confused data Y with the matrix obtained from Lorenz map Z1 to achievematrixH1 of size 1xN. The obtained encrypted matrix H1 is ready to transfer over the network. Fig -5: Block diagram of the proposed encryption technique 3.3 LIFE TIME OF THE CHAOS NETWORK The proposed research work is further extended to evaluate the life time of the network. It includes energy conservation in each and every sensor node by makes use of clustering and supporting cluster head selection energy optimization algorithm. The supporting cluster head is chosen based on residual energy. To increase the WSN lifetime, energy optimization techniques and energy conservation measures are enhanced. Parameters Initial Values Number of Nodes 100 Base station Location (100,100) Packet Length 2000 Initial Energy (E0) 2 Joules Tx Energy (ETX) 50 x 10-9 Joules Rx Energy (ERX) 50 x 10-9 Joules Data Aggregation Energy 5 x 10-9 Joules Table -2: Energy Efficient Network Parameters 4. RESULTS AND DISCUSSIONS Fig -6: Distribution of Nodes and Cluster Formation
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 746 Fig -7: Residual Energy versus Number of Iterations Fig -8: Number of Alive Nodes versus Number of Iterations Fig -9: Energy Variance versus Number of Iterations In order to evaluate the effect of network security on network life timevariousperformancemetricsaremeasured and compared with traditional LEACH technique. Residual Energy is evaluated in Figure 7 for both chaos based Clustered WSN and traditional LEACH algorithm and it is shown that Energy reduction is less when compared to LEACH. Figure 8 shows number of alive nodes when compared with the LEACH system. Figure 9 shows Average energy variance of all nodeshasless significant using proposed chaos based WSN. 5. CONCLUSIONS The performance of WSN is improved by LEACH based clustering and cluster head selection method algorithms by increasing the residual energy,throughput,quantityofactive nodes and packet delivery ratio. The better clustering algorithm builds clusters in a centralized manner within a base station and choice of cluster heads by using LEACH in dispersed manner. The performance metrics such as network lifetime, throughput, packet delivery ratio, delay, normalizedoverhead,total energyconsumptionandresidual energy are estimated and compared with advanced clustering methodology. The simulation result shows that the projected Chaotic Encryption with Clustered LEACH scheme gives improved performance in order to reduce the total energy consumption and increasing the lifetime of WSN. REFERENCES [1] Liu, Z., Liu, Z., and Wen, L. (2011). “A leach protocol for wireless sensor networks. In Advanced Computational Intelligence (IWACI)”,2011 Fourth International Workshop on, pages 766-769. [2] K. LingaRaj, D. Aradhana and Nagaveni B.Biradar, “Multiple mobile agents in wireless sensor networks using genetic algorithms”, International Journal of Scientific and EngineeringResearch,vol3,2012,pp1– 5. [3] Low CP, Fang C, Mee J, Ang, YH. Load-balanced clustering algorithms for wireless sensor networks. In: IEEE International Conference on Communications; 24–28 June 2007; Glasgow, UK. New York, NY, USA: IEEE. pp. 3485-3490. [4] Gavalas D, Mpitziopoulos A, Pantziou G, Konstantopoulos C. An approach for near-optimal distributed data fusion in wireless sensor networks. Wirel Netw 2010; 16: 1407-1425. [5] Tan R, Xing G, Li, B, Wang J, Jia X. Exploiting data fusion to improve the coverage of wireless sensor networks. IEEE/ACM Tr Netw 2012; 20: 450-462. [6] N.Eghbali,”PerformanceImprovementofInformation Dissemination Protocols in Sensor Networks
  • 6. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 05 Issue: 06 | June-2018 www.irjet.net p-ISSN: 2395-0072 © 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 747 Through Data Aggregation, Computer Engineering andInformationTechnologyDepartment”,2007.PP1- 121. [7] D. T. Ho, E. I. Grøtli, P. B. Sujit, T. A. Johansen, and J. B. D. Sousa, “Cluster-based communication topology selection and UAV path planning in wireless sensor networks,” in Proc. of International Conference on Unmanned Aircraft Systems (ICUAS). Atlanta, GA, USA: IEEE, 2013. [8] Prof. Rajeev Vishwakarma, Apurva Bhalerao, “Performance of Wireless Sensor Network using Particle Swarm Optimization Algorithm”, International Journal of Computer Application (2250-1797) Volume 6– No.1, January- February 2016. [9] YUAN ZHOU, (Senior Member, IEEE), NING WANG, AND WEI XIANG, (Senior Member, IEEE),“Clustering Hierarchy Protocol in Wireless Sensor Networks Using an Improved PSO Algorithm”, date of publication December 1, 2016, date of current version March 13, 2017. [10] Latiff N, Tsimenidis C, Sharif B. Energy-aware clustering for wireless sensor networks using particle swarm optimization. In: IEEE 18th International Symposium on Personal, Indoor and Mobile RadioCommunications;3–7September2007; Athens, Greece. New York, NY, USA: IEEE. pp. 1-5. [11] Hou J, Fan X, Wang W, Jie J, Wang Y. Clustering strategy of wireless sensor networks based on improved discrete particle swarm optimization. In: IEEE Sixth International Conference on Natural Computation; 10–12 August 2010; Yantai, China. New York, NY, USA: IEEE. pp. 3866-3870. [12] Kulkarni R, Venayagamoorthy G. Particle swarm optimization in wireless sensor networks: a brief survey. IEEE TSyst Man Cy C 2011; 41: 262-267. [13] KarthikeyanM,VenkatalakshmiK.Energy conscious clustering of wireless sensor network using PSO incorporated cuckoo search. In: IEEE Third International Conference on Computing Communication Networking Technologies; 26–28 July 2012; Coimbatore, India. New York, NY, USA: IEEE. pp. 1-7. [14] Basma Fathi SOLAIMAN,, Alaa SHETA, “Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm”, Turk Journal of Electrical Engineering & Computer Science(2016) 24: 2679 – 2695,doi:10.3906/elk- 1403-293.