A Survey on Secure Alternate Path Selection for Enhanced Network Lifetime in Wireless Sensor Network

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 12 | Dec-2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 1449
A Survey On Secure Alternate Path Selection For Enhanced Network
Lifetime in Wireless Sensor Network
Kajal K.Kapoor1, Sujata Wakchaure2
1,2 Professor, Department Of Computer Engineering Mitcoe, Pune, Maharashtra, India
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Abstract - The main challenge of wireless sensor network is
its lifetime. In this type of network, single static sink node is
present, a sensor device node require more energy for
estimating information packet specifically those are available
in the area of the sink node. Such nodes separate the energyso
fast due to the numerous tone traffic patterns and at the end
they die. This uneven event is named as hot spot issue which
gets more real as the numbers of sensor nodes increases.
Generally, replacement of such energy sources is not feasible
and cost effective solution. For this problem, there is one
solution regarding to distance. If the distance between sensor
and sink node is minimized; the energy consumption will be
effectively reduced. This paper presents the solution for
enhancing network lifetime with energy saving of sensor
nodes. Here we also discuss on the limitations and advantages
of previous methods. The sensors nodes consume morebattery
power which is at minimum distance from sink node.
Therefore, energy of sensor nodes in network will quickly
consumed their energy. So that, the lifetime of a sensor nodes
will be produces. To overcome this drawbackofthissystem,we
propose alternate shortest path technique. To enhance the
efficiency of energy along with network lifespan thisapproach
is used. Furthermore we developed a novel technique called
Energy Aware Sink Relocation (EASR) for remote base station
in WSN if the energy of alternate path is going to die. This
system exploit information recognized with the remaining
energy of sensor nodes battery for increasing the range of
transmission of sensor node and relocation technique for the
sink node in network. Calculate some numerical and
theoretical calculations are given to demonstrate that the
EASR strategy is used to increase the network energy of the
remote system essentially. ECC algorithm increases more
network lifetime and transfers secure data. An improved AES-
ECC hybrid encryption design has good flexibility and
versatility. It has improved the speed of the digital signature
generation and authentication.
Key Words: Wireless sensor networks; cluster head;
base station; cache based system; sensor nodes.
1.INTRODUCTION
In the wireless network of sensor, nodes are outline by
heavily deployment the huge types of sensor nodes in a
particular geographical area. The informationcapturedfrom
sensor nodes is transmitted to monitoring station. These
monitoring stations worked as a sink or base station. This
base station is placed far from actual sensing area. To
transfer this sensed information from source tobasestation,
concept of multi hop routing and flooding is used. With the
multiple numbers of Base stations, the total number of hops
can get minimized. This will results in minimized energy
consumption by sensor node. The minimum energy
consumption of sensor nodes will improving lifetime of
sensor network along with high rate of packet transmission
to base station. So the communication nodes deployment
and the different sink nodes are treated as most important
components in the lifetime in wireless sensor network.
The WSN have various applications such as climate
observing, battlefield investigation and inventory,
manufacturing progressions. Maximum time, the sensor
environment needs intolerant. In the remote network
system, sensor devices are not present to replacewhentheir
batteries channel. The battery exhausted from nodes can be
brought several issues, for example, take coverage hollow
space moreover, communication hollow space issues.
Consequently, some WSN systems are busy in planning
proficient approach to keep the energy of sensor nodes, as
an instance, drawing schedule of cycle for sensor nodes,
which is used to permit some of nodes and enters into the
die state to moderate power of energy. Now sensor node
does not damaging the running sensing process of the
wireless network. The efficient design of energy algorithms
aim at balancing the depletion of the battery exploitation
strength of every sensor node or consuming a limited data
aggregation technique for mixture of sensory information
into a unit to decreases the number of message transmitted
to prolong the wireless network lifetime. The enormous
majority of such system scans coincide in the network
system work. The another methodology is used for the
purpose of storing energy as well as utilizingremotesensors
to maintain the locations of region with aggregating lifetime
network energy of nodes.
For enhancing the lifespan of network aswell as efficiencyof
energy we propose a shortest alternate path mechanism in
this paper. For transmitting data from source to sink node
safely use alternate path and ECC algorithm. Elliptic curve
cryptography (ECC) is a kind of public key cryptosystemlike
RSA. But it differs from RSA in its quicker evolving capacity
and by providing attractive and alternative way to
researchers of cryptographic algorithm. The security level
which is given by RSA can be provided even by smaller keys
of ECC (for example, a 160 bit ECC has roughly the same
security strength as 1024 bit RSA).

When energy level is less than given threshold for alternate
path, we trigger the relocation of sink. Scheme for sink
relocation is explored here, which decidewhenandwhereto
relocate the position of sink. The mathematical performance
evaluations are calculated to determine the proposed sink
relocating scheme which is beneficial for enhancing the
network lifetime of a system. The simulation of technique
used in project to check out the precaution of the EASR
technique. This type of approach can work to improve the
lifetime of a WSN system. The sink node relocation will be
prolonging the battery usage of nodes.
The existing symmetric encryption schemes, such as AES,
provide a strong security solution but maintenanceofkeysis
difficult. When asymmetric schemes could be used,
maintenance of keys become easier but they providealesser
degree of security when compared to symmetric encryption
schemes. To cope with these shortcomings, the use of a new
version of the hybrid encryption systemisproposedwhichis
a combination of Advanced Encryption Standard and
Elliptical Curve Cryptography with crossencrypted keysfor
secure key exchange. Hence we proposed the AES-ECC
hybrid encryption system targeted to Wireless Sensor
Networks (WSNs) to increase lifetime of network.
Section II illustrates the related work studied for our new
topic. Section III demonstrate the details of project
implementation, definitions of terms and in addition the
documentation can be expressing the proposed system
undertakings in this paper. Section IV includes conclusions
and represents future work of project.
2. LITERATURE SURVEY
In this part we illustrate the previous techniques proposed
by the authors for WSN system.
G. S. Sara and D. Sridharan [2], representsa surveyofrouting
schemes in remote sensor nodesnetworks. In WSN’sauthor
review the challenges for routing protocol designs. The
comprehensive research of individual routing technique
classified into three stages depend upon the structure of
network like as flat, hierarchical, and location-basedrouting
etc.
Somasundara et al. [3] investigate a network system which
depends on the utilization of mobile components and to
reduce the utilizationof the energy constrained nodesatthe
time of communication and enhance useful network.
Similarly, their approach gains the advantages in sensor
networks and inadequately deployed sensors in network.
They demonstrate how their procedure supports to reduce
energy utilization at energy controlled nodes. After that, for
enhancing the performance of energy author illustrate their
framework model which uses their proposed way.
Sensor network deployment is highly challengingbecauseof
the aggressive as well as volatile nature of utilization
environments. Mousavi et al., [4] implemented two routines
for the self-deployment of mobile sensors. Basically author
developed a randomized way that offersboth simplicity and
applicability to different environments.
Akyildiz et al. [5] describe idea of network formed by
sensors. These sensors have combined micro electro
mechanical technology, wirelesscommunication and digital
physics. First, the sensing tasks and applications of sensor
networksare examined, and a comparativeanalysisofthings
influencing the look of sensor networks is given.
The main benefit of sensor node networks is there self-
organizing nature as well as autonomous process and
possible architectural alternatives suitable for a different
types of data centric driven applications. During this article
N. Jain and D. P. Agrawal [6], deal with the present an outline
of this state of the art inside the field of wireless sensor
networks.
D. Tian and N. D. Georganas [7], has introduced, an
inclinations to a node scheduling scheme,whichcanreduced
the energy utilization of complete system,thereforegrowing
network time period, by characteristicredundantnodeswith
respect of sensing coverage of network, moreover
distributing them an offline operation mode. This offline
mode has minimum energy consumption than the online
mode.
Hong et al. [8], implemented a capable route set up for
distributed sensing element network utilizing the similar
processbetween the wirelessandmultihopcommunications
network concerning instruments and rovers and therefore
the packet radio network utilized as a typical ad hoc
networking surroundings.
S. C. Huang and R. H. Jan [9], for enlarge the lifetime of
network’spresented an Energy AwareClusterBasedRouting
Algorithm (ECRA) in WSN’s. This algorithm chooses some
nodes as cluster heads to construct Voronoi outlines, move
the cluster head load balancing in every cluster of nodes. To
improve the execution of the ECRA a two tier architecture
(ECRA-2T) is designed. The reproductions demonstratethat
both the ECRA-2T aswell as ECRA algorithm perform better
than other routing schemes such as direct communication,
static clustering, and LEACH.
R. C. Shah and J. Rabaey [10] developed a energy aware
routing mechanism, that is depend upon sub optimal paths
which gives substantial gain. Additionally the experimental
results are shown that increment in lifetime of networkover
practically similar plans like directed diffusion routing. The
more elegant degradation of service with time in a fairer
manner to overcome the burning energy of nodes.
In planning sensor networksSensordeploymentisaprimary
problem. Wang et al. [11], they review and makes use of
disseminated self deployment protocols for mobile sensors.
The protocols are proposed to estimate the target positions

of the sensors after finding coverage of hole in network
where the sink is ready to move.
3. IMPLEMENTATION DETAILS
In this field, we illustrate the overviewofsystem,algorithmic
steps of system, and mathematical formulation of the
proposed system.
3.1 System Overview
Figure 1 represents that architecture of the proposed
system. System works as following way:
Fig -1.Proposed System Architecture
 Network Generation
In this phase, user can generate vertices or nodes. These
nodes are connected by edges.
 Path Generation:
It creates all possible routes from source to sink node
after creating source as well as sink.
 Shortest Path Selection:
After generation of all possible paths from source to
destination node, shortest path is selected on the basis of
minimum weight of edge.
 Generation and distribution of Keys:
At key generation center, keys are generated and
distributed to all nodes belongs to shortest path.
 Encryption of data:
At every node, collected data is encrypted by using ECC
algorithm for security purpose.
 Estimation of Energy Consumption:
After collection of data or sending of data or any type of
action, consumed energy is calculated at each node.
 Data Authentication:
Sink node check the authenticated data after determining
the hash value at source node.
 Data Decryption:
After receiving the data from source node, sink node
decrypt the data for further processing. For decryption
sink node has the decryption key.
3.2 Mathematical Model
System S is represented as
S= {N, S, D, P, Sp, K, d}
1. Deployment of nodes
N = {n1, n2. . ..nn}
Where,
N is set of n umber of deployed nodes.
2. Source node selection
S = {s1, s2,… ,sn}
Where, S is a set of Sources selected at each run time.
3. Sink Node selection
D = {d1, d2, ....,dn}
Where, D is a set of sink nodes selected at each run time.
4. All Paths from source to destination
P = {p1, p2,....,pn}
Where, P is a set of all n number of paths from source to
destination.
5. Shortest Path Slection
Sp = {sp1, sp2, sp3, ....,spn}
Where Sp is the set of all possible shortest path from
source to destination at each run time.
6. Authentication with keys
K = {k1, k2,....,kn}
Where, k is a set of n number of Keys generated and
distributed to each node for authentication.

7. Data sending from source to destination.
d= {d1, d2, d3, ....,dn}
Where, d is the set of all data packets securely routing
through shortest path.
3.2.1 Algorithm
The proposed scheme works as:
 Algorithm 1: EASR Algorithm
1. Generate a network graph Graph such as g(v,e)
Where, V is the set of vertices and e is the set of all
connecting edges to vertices.
2. Choose source and destination node among all sensor
nodes.
3. Produce all possible paths from selected source to
destination node.
4. Among all generated possible path, select the one
shortest path based on weight factor.
5. Generate and distribute public-private key pair for
source and destination node.
6. Perform data sending at source node through selected
shortest path.
7. Encrypt the data with the private key before actual
sending.
8. Estimate energy consumed by each node belongs to
shortest path.
9. Decrypt the private key and authenticatereceiveddataat
destination.
10. If energy node in path is going to die then select
Alternate path among shortest path.
11. Resend the data from source to destinationnodethrough
alternate path and also calculate energy consumed by
path.
12. Again energy may expire of alternate path.
13. When energy is minimize, use energy-aware sink
relocation technique (EASR) to relocate sink node at
other place.
Explanation: Algorithm 1 describes primarily, with sensor
nodes, source and sink node network is created. Then
generate all routes from source to sink node and for data
sending purpose choose the shortest path. Sensor nodesare
not working properly if energy utilization is greater.
Therefore systems choose optional communication path
between source and destination node also estimate energy
consumed by each node in network. By using the ECC
algorithm encrypt the data with the secret key.Withthehelp
of its hash value data is validated. Only verified data is
accepted by sink node. Decrypt the received data with the
appropriate public key. If again energy is evacuate and path
is expired, then repeat the procedure of sink relocation.
 Algorithm 2: ECC Algorithm
Elliptic Curve Cryptography (ECC): Elliptic Curve
Cryptography (ECC) [14] is a public key cryptography
developed independently by Victor Miller and Neal
Koblitz in the year 1985. In Elliptic Curve Cryptography
we will be using the curve equation of the form
y2 = x3 + ax + b
which is known as Weierstrass equation, where a and b
are the constant with
4a3 + 27b2 =0
Algorithm:
1. Sender and Receiver node Calculate edB = S =(s1, s2).
2. Sender node sends a message M E to Receiver node as
follows:
3. Compute L such that, (s1 * s2) mod N = L.
4. Compute L * M = C.
5. Send C to sender node.
6. Receiver node receives C and decrypts as follows:
7. Compute (s1 * s2)modN = L.
8. Compute (L-1)mod N, Where N = E
9. L-1*C = L-1*L*M = M.
 Algorithm 3:AES-ECC Hybrid Encryption Model
Implementation Algorithm
ECC signature and verification process: Using the Hash
function which was selected to process messages first,
Signature Scheme Based on EllipticCurvefollows:Thesigner
A has a private key d and a public key Q, making known to
the public the public key Q, the selected Hash and other
necessary information; A will send B signature-messages, B
can verify the legitimacy of signaturesbased on publicnews,
n is the order of point G. The signature generation processis
as shown in Fig. 2 [13].
 To sign a message m, the sender performs the following
steps:
1. kε[1, n-1], u = [k]G = (x1, y1); K isa random selection
2. Compute r = x1 mod n, if r = 0, return to step 1
3. According sk = sha-1(m)+dr mod n, we would
calculate s. If s = 0, return to step 1
4. (u, s) is the signature information, then, we sent m
and (u, s) to B as (m(u, s))

5. To verify the signature, the receiver performs the
following steps:
o If s [1.n-1], the signature is forged, reject
the signature
o Verify the equation:
[s]u = [sha-1(m)]G+[r]Q
Validation passes if and only if equality holds, otherwise,the
signature is forged, reject the signature proving the
equation:
 Because s = k-1(sha-1(m)+dr) and u = [k]G
 Compute [s]u = [k-1(sha-1(m)+dr)k]G
= [sha-1(m)]G+[dr]G
= [sha-1(m)]G+[r]Q
Fig -2 Digital signature software process
 AES-ECC Hybrid Encryption Model
Implementation Algorithm:
1. Data is collected by the sensor data acquisition system
2. Using SHA-1 function to generate the data summary
3. Using the sender’s private key K and ECC digital
signature module to generate Digital Signatures
4. According to AES encryption module (the privatekeyis
KAES), encrypting digital signature andencryptingdata
which need to be sent. Then, getting data-ciphertext
and signature-ciphertext
5. Encrypting the private key KAES by ECC encryption
module, then, generating key-ciphertext
6. Packing all ciphertext and sending it by means of
wireless sensor networks
7. The sender upload that ciphertext to the internetbythe
sink node, the users can use the mobile terminal to
receive data
8. When the receiver receives the ciphertext, receiver
uses his private key to decrypt the key KAES, then,
decrypting the data-ciphertextandsignature-ciphertext
by KAES. Using the sender’s public key to verify the
signature and get the summary B; then we can get the
summary A by using SHA-1 algorithm. Comparing
summary A with summary B, if they are the same, then
the data is valid and available; otherwise, it represents
invalid data
Fig -3 AES-ECC hybrid encryption system
The existing framework of the hybrid encryption scheme
allows for only one way key encapsulation. That is, the AES
key is protected by encrypting it with the ECC key. This
necessitates periodic updation of AES key and ECC public
key without increase in complexity andalsocrossencryption
of AES and ECC keys with one another. The improved AES-
ECC Hybrid encryption scheme is shown in fig 3.
4. CONCLUSIONS
This paper implemented the differentmethodtoimprovethe
lifetime of network. A relocate-able sink is one approach to
enhance the lifetime of network but still it have its own
limitations as sink relocation involves more energy so we
have proposed alternate shortest path technique which
optimizes all nodes in the network system also enhances
lifetime of network by limiting the number of sinkrelocating
actions. In addition, we also proposed secure data sending
and node authentication for communication purpose. In
future, we can increase lifetime of a network.Alsocansecure
the network by providing security.

REFERENCES
[1] G. S. Sara and D. Sridharan, Routing in mobile wireless
sensor network: A survey, Telecommun. Syst., Aug.
2013.
[2] A.A. Somasundara, A. Kansal, D. D. Jea, D. Estrin, and M.
B. Srivastavam, Controllably mobile infrastructure for
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[3] H. Mousavi, A. Nayyeri, N. Yazani, and C. Lucas, Energy
conserving movement-assisted deployment of ad hoc
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[4] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and
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[11] Bing Ji, Liejun Wang and Qinghua Yang, 2015. New
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[12] A Arjuna Rao1 , K Sujatha1 , A Bhavana Deepthi1 , L V
Rajesh1 1 Miracle Educational Society Group of
Institutions, Bhogapuram, Vizianagram, India , Survey
paper comparing ECC with RSA, AES and Blowfish
Algorithms, IJRITCC | January 2017,
http://www.ijritcc.org
BIOGRAPHIES
Kajal K. Kapoor received the B.E. and
M.Tech. degrees in Computer Scienceand
Engineering from Yeshwantrao Chavan
College of Engineering and Bapurao
Deshmukh College of Engineering,
Wardha in 2009 and 2014, respectively.
She is currently working as assistant
professor in Computer Engineering
Department in MITCOE,Pune.
Sujata S. Wakchaure received theB.E.and
M.E. degrees in Computer Science and
Engineering from Amrutvahini Collegeof
Engineering, Sangamner and JSPM
College of Engineering, Pune in 2009 and
2014, respectively. She is currently
working as assistant professor in
Computer Engineering Department in
MITCOE,Pune.

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