Multilink Routing in Wireless Sensor Networks with Integrated Approach for Highly Secured Adaptive Energy

International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 9 125 – 129
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125
IJRITCC | September 2017, Available @ http://www.ijritcc.org
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Multilink Routing in Wireless Sensor Networks with Integrated Approach for
Highly Secured Adaptive Energy
Ms. Rucha Kamble
ME in Wireless Communication and Computing
JDCOEM, Nagpur
RTMNU, Nagpur, India
kamble.rucha3@gmail.com
Prof. M.M Baig
ME in Wireless Communication and Computing
JDCOEM, Nagpur
RTMNU, Nagpur, India
mirzammb@gmail.com
Abstract—Now a day’s people make use of sensors in order to have a distant communication without any intervention and to avoid the use of
wires so that our communication will be mobile, but these sensors suffers a problem of battery drainage. There are various Energy Efficient
Protocols for WSN that are being created which aspire to successfully deliver the data packets from sensor node (source) to the Base Station.
These protocols have certain parameters like distance to identify the route. These protocols have a considerable amount of energy to find the
minimum distance. Our aim is to formulate a protocol which has a target to calculate an efficient path at the same time save the energy of
sensors in order to enhance the lifetime of network. In our project we proposed an Optimum Path and Energy Aware Sensor Routing Protocol
(OPEASRP) which makes use of load as a parameter for calculation of optimal path and LEACH for conservation of energy of the nodes. At the
same time we are providing the strong security to the network for preventing the network from different attacks. The main function of this
protocol is for authorized multiple network user. So, with the help of different security parameters the system provides a high security to the
wireless sensor network. Energy efficient new algorithm is also used because it is difficult to crack.
General Terms: Wireless Sensor Network, Path Finding, Load Balancing
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I. INTRODUCTION
Now a day’s Wireless sensor networks are very
popular in transmitting data and gathering useful geographical
and environmental information.
A wireless sensor network (WSN) consisting of
randomly distributed electronic devices make use of sensors to
track local or environmental conditions. A WSN system has a
gateway that offers non-wired connectivity reverted to the
wired world and distributed nodes. A Wireless Sensor
Network’s nodes consists of various components includes the
antenna, power battery, microcontroller, analog circuit, and
sensor interface. While using Wireless Sensor Network’s radio
technology, one must take important trade-offs. In battery-
powered devices, higher radio data transfer rates and
continuous sensing of nearby radio channel may result in
draining battery more often.
To make the battery life better, a node after certain
period of time wakes up and transmits data by powering on the
antenna and then powering it back off to save energy.
Microprocessor trends for WSNs include minimizing power
consumption while retaining or enhancing processor’s speed.
Much like a selected radio, the power usage and its
transforming speed trade-off is a primary factor when
selecting a processor, for communication. Now days more
work is evolving to reduce the power consumption of WSN,
but still the results are not that much proven.
While keeping in mind the energy conservation,
protocols suggested earlier should also be designed to attain
robustness in routing structure. Many paths finding algorithms
focus on endorsing the load-balancing technologies to attain
the energy-saving effect by real time adjusting the distribution
of flow traffic in networks only based on the current-status
resources of link and nodes.
This proposed approach has a determination to save
the energy of sensor nodes. This approach is a combination of
two techniques called Load Balancing and LEACH Algorithm.
This suggested approach will definitely give a better output in
terms of increasing the efficiency of WSN and save the energy
of sensor nodes.
LEACH methodology will form the clusters with the
participation of sensor nodes and selects a Cluster Head to
forward the communication on behalf of the cluster. The
criteria for selecting a cluster head is nothing but the load
calculated in the load calculation process. In a cluster the node
with lowest load is selected as the Cluster Head (CH). This
CH then transfer’s the packets to base station (BS).
As you know that a wireless sensor network (WSN)
consisting of randomly distributed electronic devices make use
of sensors to track local or environmental conditions. A WSN
system has a gateway that offers non- wired connectivity
reverted to the wired world and distributed nodes. A Wireless
Sensor Network’s nodes consists of various components
includes the antenna, power battery, microcontroller, analog
circuit, and sensor interface. While using Wireless Sensor
Network’s radio technology, one must take important trade-
offs. In battery powered devices, higher radio data transfer
rates and continuous sensing of nearby radio channel may
result in draining battery more often. To make the battery life
better, a node after certain period of time wakes up and
transmits data by powering on the antenna and then powering
it back off to save energy. Microprocessor trends for WSNs
include minimizing power consumption while retaining or

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enhancing. processor’s speed. Much like your selected radio,
the power usage and its transforming speed trade-off is a
primary factor when selecting a processor for communication.
Now days more work is evolving to reduce the power
consumption of WSN, but still the results are not that much
proven. While keeping in mind the energy conservation,
protocols suggested earlier should also be designed to attain
robustness in routing structure. Many paths finding algorithms
focus on endorsing the load-balancing technologies to attain
the energy-saving effect by real time adjusting the distribution
of flow traffic in networks only based on the current status
resources of link and nodes.
Wireless sensor networks are highly distributed network of
all small and light weighted nodes, deployed in large numbers
to monitor the environment or system by the measurement of
physical parameters such as temperature, pressure, relative
humidity. Each node of the sensor network consists of three
subsystem i.e. sensor subsystem which sense the environment,
processing subsystem which performs local computation on the
sensed data, and communication subsystem is responsible for
message exchange with neighboring sensor node.
II. PRESENT WORK
Many symmetric and asymmetric encryption ciphers have
been proposed and developedby researchers. Literature
demonstrates symmetric ciphers are more efficient as
compared to asymmetric ciphers. Some common symmetric
key ciphers are discussed below.
3.1 DES
DES is a 64 bit block cipher It encrypts 64 bits of data at a
time using key of length 56 bits. 16rounds of processing are
applied to plain text after initial permutation and the last step
is to apply final permutation to obtain a 64 bit cipher text. DES
uses fiestel structure and its designis an inspiration for many
block ciphers. Wuling Ren et. al. in [7] proposed an
hybridencryption mechanism based on DES and RSA. RSA is
a public key encryption algorithm andused for the encryption
of DES's key to be shared between shared and receiver. DES
was prone to Brute Force Attack as there are only 256
combinations of key are possible. It was quite easy to crack
the DES and making it non-preferable approach for WSN
security.
3.2 Triple DES
Triple DES or 3DES was proposed to enhance the security
mechanism of DES. Key sizewas extended from 56 bits to 168
bits (56*3). Also it used 3 rounds of DES encryption.
3DEScan be used in two ways either with three keys having
2168
possible combinations or with twokeys having 2 112
possible combinations. Cryptanalysis of 3DES shows that with
so manycombinations of key, brute force attack is practically
impossible [8]. Large key size makes3DES strongest
encryption algorithm, but however it requires a large amount
of time andmemory and thus making it an expensive
algorithm.
3.3 AES
As per [9] Advance Encryption Standard (AES) also referred
as Rijndael cipher is a block cipher with block size of 128 bits
and three different key sizes of 128, 192 and 256 bits. AES
uses a non-fiestel structure for encryption decryption. Key size
depends on the number of rounds which can be 10,12 or 14 for
key size of 128,192 or 256 bits respectively. Round keyused
by AES is always of 128 bits. As explained in [10] basic
Structure of AES is represented in figure 4. First
transformation of round is Substitution where substitution of
bytes is done via using S-box.After a state is substituted
another transformation that is applied to state isShifting.
Number of shifts of state matrix depends on the row number
that can be 0,1,2 or 3. Mixcolumn transformation is matrix
multiplication where state column is multiplies by a constant
matrix. Finally a round key word is added with each state
matrix in Addroundkey transformation.
Figure 3. AES Architecture
3.4 RC5
As per [11] RC5 is a potential cipher for data security in WBSN. It
is a efficient and flexiblealgorithm where encryption attributes
like number of rounds, block size, key length can beadjusted
according to the application. As discussed in [12] RC5 uses
operations like modulo2word-size addition, bit wise exclusive-
or and a cyclic left rotation of word in each round. RC5with
short parameter value is susceptible to differential attack;
whereas RC5 with large
parameters value is time consuming.
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etc.
III. SIMULATION OUTCOMES
The following are the screen shots acquired during network
formation
5.2.1 Deployment of Nodes
Here the assumption is that sensors are placed into a plane
and linear surface. The sensors are placed randomly i.e.
regardless of their location and sequence. Each Node is

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equipped with the electronic devices like Transceiver,
Battery etc. to initiate the communication by sensing other
nodes and forwarding data packets,
Fig. 1 Screenshot Deployment of Nodes
5.2.2 Forming Clusters and Cluster’s Head
To accomplish this, the proposed approach has applied
LEACH algorithm in order to form the cluster and select
cluster Head the Algorithm is explain in chapter 3. Different
colors shows, different clusters. Every cluster Head is marked
Fig. 2 Screenshot Formation of Cluster and Selecting
Cluster Head.
with CH on the top. The destination node is given as
Base_Station.
5.2.3 Sensing Neighbors:
In the proposed approach, in order to find the optimal path
AODV algorithm is been applied. To send the packet from
source to destination every CH is sensing its neighbor by
considering the parameters like Distance and Battery power.
This process will helps in knowing which path to choose to
forward the data packet.
Fig.3. Screenshot Sensing Neighbor.
5.2.4 Selecting Path:
In the proposed approach optimal path has been
selected, shown by nodes surrounding by square. The paths
have been selected by calculating loads of each and every
individual node so that the transmission will be proper and
reliable. Calculating the load balance using the below
approach:
Load = no of packets released / total number of
packets
Fig. 4. Selecting the Path
5.2.5 Detection of Malicious Node :-
In the network, it is very difficult to identify that node is
malicious or not. But, malicious nodes are detected and
that are removed with the help of AP algorithm
Fig. 5 Detecting the Malicious Node.
.

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IV. RESULTS AND CONCLUSIONS
Energy Consumption Graph:
Fig.6 Screenshot Energy Consumption graph (red= existing::
green = our)
The above graph depicts that after using the approach
proposed here, the energy consumed by sensor nodes
decreased as compared to the existing approach.
Packet Delivery Ratio Graph:
Fig. 7. Screenshot Packet Delivery Ratio (red= existing:: green
= our)
The above graph shows that after comparing the
existing approach with this proposed approach the packet
delivery ratio also gets increase as the ratio of failure of nodes
has been decreased.
7. Throughput Graph:
The above graph shows the throughput of the system
after applying the proposed approach. As the proposed
approach results in less power consumption and increased in
packet delivery ratio hence, the throughput of the system is
also increased.
Fig. 8. Screenshot Throughput (red= existing:: green = our)
V. CONCLUSION AND FUTURE SCOPE
Considering such a problem with wireless sensor network in
accordance with the security is more complex and
challenging in nature and the security vulnerabilities in data
discovery and dissemination when used in WSNs. Also, some
energy efficient new algorithms (AP) havebeen proposed.
Thus, in the future work, we will consider how to ensure data
confidentiality in the design of secure and distributed data
discovery and dissemination protocols and AP algorithm and
the system will maintain the integrity of the data also ensure
the performance of the system. We proposed a new symmetric
key algorithm (AP) based on shuffling, substitution and
shifting to depict a security scheme for WSN which is energy
efficient as well as difficult to crack. In this research we will
not only going to detect the malicious node from the network,
but we will also remove the attacker node from the network,
which will make the system muchmore secure and reliable.
This will provide us a high security to the wireless sensor
networkby detecting and removing the attacker from the
network. and optimal path finding and toextend the lifetime of
the Sensor node. Here we can conclude that the proposed
system will provide the high security. Then by applying
energy efficient new algorithm we can encrypt and decrypt the
message for the security purpose. This will provide us a high
security to thewireless sensor network by detecting and
removing the attacker from the network. The analysiswas
performed in network simulator (NS2).The project is the
successful implementation of an optimal path finding approach
which results in saving the energy of sensor nodes which in
turn increase the lifetime of a wireless sensor network.This
approach will not only make the communication better but it

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will remove thedrawback of changing battery by reducing the
power consumption of the sensor nodes.
The future work will include the placing of Sensor’s on a non-
planar surface, also with a solution to find a shortest path for
transmission.
REFERENCES
[1] Rupika Goyal, Shashikant Gupta, Pallavi Khatri Energy Aware
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International Conference on Computing, Communication and
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2/16/$31.00 ©2016 IEEE, pg no. 699-703
[2] Chuanyao Nie, Hui Wu, Wenguang Zheng, Latency and
Lifetime-Aware Clustering and Routing in Wireless Sensor
Networks, 2016 IEEE 41st Conference on Local Computer
Networks, © 2016, Chuanyao Nie. Under license to IEEE. 164
DOI 10.1109/LCN.2016.33
[3] Haibo Zhang and Hong Shen Energy-Efficient Beaconless
Geographic Routing in Wireless Sensor Networks IEEE
Transactions On Parallel And Distributed Systems, Vol. 21, No.
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[5] J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd
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[6] D. He, C. Chen, S. Chan and J. Bu, “DiCode: DoS resistant and
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IEEE Trans. Wireless Commun., vol. 11, no. 5, pp. 1946-1956,
May 2012
[7] D. He, S. Chan, S. Tang, and M. Guizani, “Secure data
discovery and dissemination based on hash tree for wireless
sensor networks,” IEEE Trans. Wireless Commun., vol. 12, no.
9, pp. 4638-4646, Sept. 2013
[8] Yong-Zhen Li, Ai-Li Zhang, Yu-Zhu Liang Improvement of
Leach Protocol for Wireless Sensor Networks 2013 Third
International Conference on Instrumentation, Measurement,
Computer, Communication and Control
[9] DipakWajgi, Dr. Nileshsingh V. ThakurLoad Balancing
Algorithms in Wireless Sensor Network : A Survey IRACST –
International Journal of Computer Networks and Wireless
Communications (IJCNWC), ISSN: 2250-3501
[10] TrianaMugiaRahayu, Sang-Gon Lee*, Hoon-Jae Lee Survey on
LEACH-based Security Protocols February 16~19, 2014
ICACT2014

Multilink Routing in Wireless Sensor Networks with Integrated Approach for Highly Secured Adaptive Energy

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