www.ijecs.in
International Journal Of Engineering And Computer Science ISSN:2319-7242
Volume 4 Issue 2 February 2015, Page No. 10359-10366
Result Evaluation of Dynamic Topology Control Using Quality
Estimation Factors for Mobile Ad-Hoc Network
Jitendra Tiwari, Jasneet Kaur
Department of Computer Science & Engineering
SDBCT Mhow Road, Indore, (M.P), India
tiwari9706@gmail.com
Research Scholar, (PG)
jasneetkaur18gmail.com
Professor, CSE Dept.
ABSTRACT
Mobile ad-hoc network support dynamic topology handling due to their variable nature of communicating nodes. Here the
motion of nodes is random in a specified range of the network. As the mobile nodes containlight weighted protocols for
supporting transmissions, it requires some more controls over the topological aspect. The traditional topology control mechanism
can be categorised according to their use like mobility sensitive, energy awareness, QoS based etc. An efficient protocol is that
which dynamically handles all this issues effectively with better use of bandwidth.
Problem:The aim is to investigate the shortcomings of current solutions with respect to the dynamic topology handling issues
through QoS based transmissions, and bring forth new solutions to improve the performance of the network as a whole or for the
individual nodes. With respect to the issue of mobility, and traffic distribution, the work focuses to investigate the factors that
affect the rerouting time in proactive routing protocols. That is, the time duration needed to reroute and restore a broken
communication path due to node mobility.
Approach: Quality of service and mobility aware topology control reduces spatial interference while increasing the effective
channel capacity and network lifetime.
Results: This study, designs a topology control using efficient QoS based mobility aware topology control algorithm for MANET.
In this study, initially the factors for QoS, mobility, dynamic changes, power level, stability and connectivity is considered for
dynamically handling of topologies.The aim is to provide a effective topology control solutions for minimizing the rerouting time
such that the packet loss can be minimized and the performance in the network is maximized.
Recommendations: By simulation results of quality estimation using modified factors, we show that our CDTRBalgorithm
outperforms existing topology control algorithms in terms of increased node life time and reduced power consumption.
.
Index Term—MANET, Topology Quality Estimation, CDTRB, QoS, Mobility, Power Conservation Consistent, Dynamic Topology;
INTRODUCTION
A group of movable node having wireless type of
network between them is known as mobile ad- hoc network
(MANET). This type of network is not an infrastructure
based network. In this all the mobile nodes can acts as a
router for data transmission between multiple nodes within a
particular range. Nodes equipped with radio transceivers
can communicate directly with other nodes in their
neighborhood and also with rest of nodes along multi-hop
paths where other nodes serve as relay points (in case that
network is connected). This kind of communication network
is very useful in situations, where fixed infrastructure is not
available. We can imagine a scenario, where a group of
exploration robots is deployed in outlying part of the world
or in some unknown region and robots have to form a
formation to survey this area automatically. Other possible
application of communication platform based on Ad hoc
networks is to coordinate rescue teams in the region
damaged by the natural disaster. In such region the whole
communication infrastructure could be damaged. The
standard walkie-talkie may not provide sufficient
communication platform, because of limited range of
individual transceivers. A particular type of Ad hoc network
is a MANET..
Environmental condition of mobile nodes can always
affects this transmission and among them mobility is a
important factor. Due to which the link can be break due to
location updates of the nodes. So for distance location the
transmission can be done via third intermediate device
which helps in relaying the packet & routing. Due to all this
effective factors & condition of mobility, the MANET had a
wide range of application areas like military, disaster relief,
business & home automation systems. For an improved
MANET architecture various factors can work
simultaneously like power utilization, bandwidth utilization,
location updates, reliability, security, quality of service
(QoS) etc. Among all of them the QoS based topology
control (TC) is a primary concern due to frequent changes &
updates in these kinds of network scenarios. Quality of
service (QoS) refers to resource reservation control
mechanisms rather than the achieved service quality. QoS is
the ability to provide different priority to different
Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
Page 10359
applications, users, or data flows, or to guarantee a certain
level of performance to a data flow.
Topology Control in MANET
The topology of a multi-hop wireless network is a “set
of communication links between node pairs used explicitly
or implicitly by routing mechanisms”. A topology can
depend on uncontrollable factors such as node mobility,
weather, interference, noise as well as controllable factors
such as transmission power, directional antennas and multichannel communications [1]. The topology control having
good QoS will always depends upon various factors &
consideration failure of which leads to wastage of
utilization, channel capacity & communication cost. The
design of this topology control should implicitly holds some
characteristics for two major scenarios like if the topology is
too sparse then the network can get partitioned. However,
topology control can provide better control over network
resources such as battery power and reduce redundancy in
network communications.
In MANET both of the above parameters can be used to
understand the mobility principle effectively. Thus the
mobility causes related movement of nodes which can break
links and thus change the topology and this may result in
partitioning of the network. Once the network is partitioned
none of routing/broadcast protocol can be successful and
very rare chances to form the connected network. For
example [2], suppose node a and node b are neighbors in the
network at time t, but somehow move out of the
communication range at time t+Δt. During this period
routing is unaware of this broken link and node a still
forward packets to b and it will never reaches to node b. To
keep the topology unchanged without disconnecting any
node within the network needs topology management
scheme. Effective Topology control will improve the
performance and the capacity of Mobile Ad-hoc networks
by building reliable network structure [3]. This work is
focusing our research concern to both the above mentioned
issues of QoS & topology control implementation of which
expects the effective res
Factors Affecting Topology Control
It is shown that a number of factors can affect the efficiency
of load balancing as listed below:
 Mobility
 Link Breaks
 Location Updates
 Level of asymmetry
 Offered load
 Level of spatial reuse
 Sensing range
 Shape and size of the network
 Location of gateways
 Network Energy
 QoS
However, these factors alone cannot explain why the
performance of topology control is high for certain networks
while it is poor for others. Obviously, the specific layout of
the topology is also an important factor.
I. RELATED STUDY
MANET is a type of dynamic changing nature &
having a varying topology condition at various stages of
transmission. There have been many research efforts to
provide QoS support in MANETs. Various authors
categorizes these efforts into QoS models, QoS resource
reservation signaling, QoS routing, and QoS MAC, and
provides an overview of how these different components
can work together to deliver QoS in MANETs.
In MANET, QoS based TC has no use of existing wired
routing protocols. It requires specialized routing schemes
which are classified into three categories based on topology
update [7]: i) Table driven, ii) On-demand, iii) Hybrid
routing protocols. The table driven routing protocol is also
known as proactive routing protocol, in this protocol route
to every node in the network is maintained in the routing
table. Even if route is not required each node maintains the
route to other nodes in the network. The simulation have
used the network simulator ns-2 for simulating routing
protocols using group mobility model, and present the
results of simulations of networks of 40 wireless mobile
nodes. Overall, the work conclude that under group mobility
model, node's velocity has little impact, but number of FTP
connections has significant impact on the performance of
the routing protocols from QoS perspective. The DSR
protocol emerges as the best in all respect.
In most existing localized topology control protocols
for mobile ad hoc networks (MANETs), each node selects a
few logical neighbors based on location information, and
uses a small transmission range to cover those logical
neighbors. Transmission range reduction conserves energy
and bandwidth consumption, while still maintaining network
connectivity. However, the majority of these approaches
assume a static network without mobility. In a mobile
environment network connectivity can be compromised by
two types of “bad” location information: inconsistent
information, which makes a node select too few logical
neighbors, and outdated information, which makes a node
use too small a transmission range. Various approaches are
proposed over the last few years which take this mobile
topology change as a prime concern. In the paper [8]
mobility-sensitive topology control method is proposed that
extends many existing mobility-insensitive protocols. Two
mechanisms are introduced: consistent local views that
avoid inconsistent information and delay and mobility
management that tolerate outdated information. A buffer
zone mechanism guarantees (under low mobility) or
enhances (under high mobility) the connectivity of the
effective topology. At the analytical and mathematical
evaluations level the works seems to be effective.
In the paper [9] the author studied the effect of some
new parameters of QoS on topology control. QoS is usually
defined as a set of service requirements that needs to be met
by the network while transporting a packet stream from a
source to its destination. The network is expected to
guarantee a set of measurable pre-specified service attributes
to the users in terms of end-to-end performance, such as
delay, bandwidth, probability of packet loss, delay variance
(jitter), etc. The idea of leveraging node mobility to improve
QoS can potentially be applied to any QoS-aware routing
scheme. To demonstrate this idea, we chose to work with
our modification of the AODV routing protocol, called QAODV, which enhances AODV to be aware of resource
requirements. The first two fields specify the bandwidth
requirements of the application and are populated by the
source node. At the initial level of their simulation results it
seems to be a effective mechanism.
In this paper we presented a novel QoS architecture
which enables real-time multimedia communication
between peers in wireless mobile ad hoc networks.. During
Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
Page 10360
this period of research the authors also focused on various
interrelated issues of QoS based TC like peer to peer
communication [10] in which a new protocol DACME is a
probe-based admission control mechanism that performs
end-to-end QoS measurements according to the QoS
requirements of multimedia streams. However this is not a
strict requirement, which means that DACME will still
operate correctly in non QoS-compliant MANETs.
Simulation results show that the probabilistic admission
control technique used in DACME is effective at different
levels of congestion, and that delay and jitter constraints are
met with a good level of accuracy. Overall, DACME
improves the performance experienced by users and also
avoids wasting MANET resources. We observe that
enhancing DACME with routing awareness further
improves the performance achieved.
In the paper [11] the author proposes a flexible QoS
model for MANETs (FQMM) which considers the
characteristics of MANETs and combines the high quality
QoS of IntServ and service differentiation of DiServ. The
idea behind IntServ is borrowed from the paradigm of the
telephony world and B-ISDN, i.e., adopting a virtual circuit
connection mechanism. The Resource ReSerVation Protocol
(RSVP) is used as a signaling protocol to setup and maintain
thevirtual connections. Routers apply corresponding
resource management schemes, e.g., Class Based Queuing
(CBQ) to support the QoS specifications of the connection.
Based on these mechanisms, IntServ provides quantitative
QoS for every o. Salient features of FQMM include:
dynamics roles of nodes, hybrid provisioning and adaptive
conditioning. Preliminary simulation results show that
FQMM achieves better performance in terms of throughput
and service differentiation than the best effort model.
In case of multi-beam smart antennas, the network
topology needs to be adjusted dynamically by adjusting the
beam width and beam directions to minimize interference
and to maximize the number of possible concurrent network
communications.Thus the authorextends this concept to
create an Adaptive QoS Topology Control (AQTC) [12]
System using Smart Antennas. The network topology can
be controlled in two ways:
1. Forming an initial fully connected topology during the
network initialization phase and then changing the topology
dynamically if required for new communications.
2. No initial connected topology is formed; the topology
is formed dynamically depending on the communications.
It uses a cross-layer approach to control the topology
dynamically where the topology control layer sits between
the MAC and the routing protocol. The performance of
protocol has been evaluated using extensive simulations.
AQTC always forms a topology to facilitate the current
communications and improves the network throughput and
end-to-end delay.
Some of the authors also focused their work on
cooperative communication. Most existing works on
cooperative communications are focused on link-level
physical layer issues. Consequently, the impacts of
cooperative communications on network-level upper layer
issues, such as topology control, routing and network
capacity, are largely ignored. This paper proposes a
Capacity-Optimized Cooperative (COCO) topology control
scheme to improve the network capacity in MANETs by
jointly considering both upper layer network capacity and
physical layer cooperative communications [13]. When
cooperative transmission is used, a best relay needs to be
selected proactively before transmission. After obtaining the
link capacity and inference models, the network capacity
can be derived as the objective function in the topology
control problem (1). The proposed scheme can determine
the best type of transmission and the best relay to optimize
network capacity. Simulation results have shown that
physical layer cooperative communications techniques have
significant impacts on the performance of topology control
and network capacity, and the proposed topology control
scheme can substantially improve the network capacity in
MANETs with cooperative communications.
So many other approaches for QoS is been proposed by
various researchers. Some of these are given in [14] like
adaptive routing, fair queuing, CADAR, Two level QoS,
AOQR, QoS GRID etc. All this approaches made an
intermediate decision at various layers of network model
like physical, MAC, Network, transport & application. They
all are dealing with dynamic environments having varying
topology due to mobility of nodes. Generally, the QoS of
any particular network can be defined as its ability to deliver
a guaranteed level of service to its users and/or applications.
QoS provisioning in MANETs typically involve the
collaboration of various layers of the networking protocol
stack, researchers are increasingly considering the use of
cross-layered designs, adaptively, and mobility predictions
to achieve QoS guarantees in the network. Nevertheless,
there are still several outstanding QoS issues that must be
addressed, and alternative forms of mechanisms must be
studied in greater depth to facilitate the development of QoS
in MANETs.
Some of the authors had also worked on long distance
topology control [15], QoS virtual backbone (QoS-VBB)
[16], distributed admission control D-AC [17], for more
than 15 hops of nodes. This contribution is concerned with
the performance evaluation of topology control algorithms
for indoor ad hoc networks in multi-storey buildings.
Several proposed topology control algorithms based on
discrete sets are compared. The topology control algorithms
operate with wireless links having variable transmission
rates according to existing wireless communication
standards. The maximum number of routing steps is limited
to 15 hops. Computational experiments with a queuing
analyzer for open networks are performed to estimate the
connectivity between distant nodes in the network located at
different vertical levels. The tradeoff between connectivity
and delay-throughput is studied assuming that the
algorithms are constrained to the selection of only five links
by each node.
II. PROBLEM DEFINITION
In existing TC protocols, the network is connected with
all the nodes under the smaller range of transmission. In this
every other node selects its nearest neighbors within its
transmission range. This selection of neighbors is based on
its nearest hop information of location, energy, connectivity
& number of nodes. This grouping of short range neighbors
nodes connected with each other is known as consistent
topology. So its needs to be updated synchronously to the
changing network conditions. During this changing
condition some of the nodes can be moved out of the
network & needs to be updated. The node which is still
connected with above consistent group is known as active
topology group. Also the parameters related to mobility had
some of the QoS factors affecting to that directly. These
must be taken into consideration with connectivity & power.
Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
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These discussion leads to three related issues in topology
control which is still unsolved by any of the traditional
mechanisms:
(i)
Most existing topology control algorithms assume
homogeneous wireless nodes with uniform
transmission ranges. When directly applied to
heterogeneous networks, these algorithms may
render disconnectivity.
(ii)
Taking the actual network condition under the
connected transmission ranges, some methods
needs to be given which ensures that consistent
topology is generated from TC protocol.
(iii)
After considering this consistent topology how
motion, connectivity, & power can be maintained
for active topology condition.
III. PROPOSED SOLUTION: CDTRB ALGORITHM
Network changes very frequently due to movable nature
of the nodes and hence their topology dependent activities
get affected. This affection can be taken as transmission
issues by which nature of network can be dynamically
change. For handling of this sudden change in behaviour of
the network connections is comes under the topology
control process. This work proposes an modified
CDTRB[18] with some robust result verifications topology
control with quality parameters. Taking quality of service
with topology control guides the network towards handling
of dynamic behaviour of nodes with motion. The work
considers various factors for updated topology detection and
allotment and for this the parameters are mobility, energy
and QoS. The approach is effectively handling all the issues
related to better utilization of bandwidth using updated
topology control. The suggested work is derived using a
deeper survey of existing mechanism on above parameters
and analytically evaluations of which proves the approach
capability up to some extent.
Here CDTRB stands for the parameters selected for
effective topology control. The work uses connectivity, data
transfer and residual bandwidth. The aim of taking these
parameters is to consider the factor which affects most while
the topology change. Here connectivity aims towards
continuous connection status between any two consecutive
nodes of the network. Data transfer identifies the amount of
data is been transferred before nay topology change and
remaining part of data to be send after the motion of nodes
and change in topology. Residual bandwidth forecast the
network capacity for transmitting the data in terms of size
and hops of the network. The aim is towards assuring
complete and stable connection till data transfer.
The suggested approach is capable of dynamically
handling all the topology situations using above parameters.
The concern is towards accurately measuring the network
capacity in terms of data transfer, power, and required
bandwidth before applying any change to the network
connections. If the information is updated then it is quite
effective to tolerate any kind of data losses. There is also a
alert system which guides the topology changes and predicts
its after effect. As in network where the node mobility is
high, the constraints related to energy and bandwidth must
be effectively utilized and by the suggested CDTRB
approach the aim is achieved.
Architecture
CDTRB Topology Control
Node
Connectivity
Data Transfer
Node
Check Link
Quality
(Power)
Node
Node
Dynamic Network
(Old Topology)
Data
Collection
For
Sufficient
Power
Transmit the
Packet
Check Data
Status
Forward
Complete Rcv
Packet
Wait: InComplete Rcvd
Packet
Node
Residual
Bandwidth
Node
Monitor
Bandwidth
Utilization
Node
Node
Bandwidth
Available >
Required
Dynamic Network
(New Topology)
DO Transmit
Calculate Average Quality Path= (Route Existence
(Connectivity and Power) + Data Status (Complete) +
Residual Bandwidth)/3
Best Suited Path Selection (Average Quality Path>=
Min Threshold)
Update
(Delete Old
Path, Add
New Path)
Set Status to
BiDirectional
Figure 1: Proposed CDTRB Based QoS topology Control in MANET
Components and Description:
(i)
Connectivity:
Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
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(ii)
(iii)
(iv)
(v)
(vi)
(vii)
Data Transfer:
Residual Bandwidth:
Data Collection:
Average Quality Estimation:
Best Path:
New Topology Update:
Flowchart
Start
1
Set Initial Values
Power Status
Connectivity,
Status,
Bandwidth
Transmission
Checks
Calculate
Remaining Power
Verify Path
Value
If
(RemPow>Thr
eshold)
No
Yes
Data Status
Search New Path
No
If (NRP==Full)
Wait for Completion
Update New
Node
Status==
Completely
Connected
Yes
Forwards
Old Status 1 for
Incomplete
Packet
Forwarding Status 0
1
3
Collect the Above
Data for CDTRB
Decision
Link Status
Residual
Bandwidth
Wait for Status
Change
Yes
Calculate Average
Quality Path
Update All Routing
Entries
Continue
Communication
No
If
(Available Band
>ReqBand)
If
(Flow==Accepted)
No
Link Quality<0
Yes
Old Status 0 for
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Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
Link Quality
Exit
Link Quality=No
New Link
3
The proposed CDTRB localized topology control
algorithms maintains the network connectivity while
reduces energy consumption and improved network
capacity. These algorithms not only outperform existing
approaches in terms of energy efficiency, network capacity,
and several other performance metrics, but also provide
certain performance guarantees such as the degree bound of
optimality.
The proposed approach works as an effective topology
control mechanism taking QoS parameters as a major
concern. Several problems and their corresponding solutions
related to QoS topology control and strongly connectivity
topology control in wireless ad hoc and sensor networks are
discussed. Specifically, topics discussed include: (1) QoS
topology construction algorithms in both homogeneous and
heterogeneous networks with respect to different
optimization objectives; and (2) how to construct strongly
connected network topology under both non-restricted and
restricted maximum transmission power.
IV. CONTRIBUTION OF THE PAPER
In this work implementation and analysis of topology
control algorithms for mobile ad-hoc networks with
emphasis on deployment on simulators fro studying the real
affects of the suggested approach. The proposal and
implementation of our algorithms using the customized
models provide the solutions for end-user application
without the need of any new network model or product to
use or implement the required features. To solve the above
problem of effective and dynamic topology control
considering both QoS and mobility aware parameters,
following steps have to be carrying out:
(i)
Identification of the best suitable approach to
topology control problem in this particular
arrangement of hardware components and
scenarios.
(ii) Evaluating the topology control using quality based
estimations of data transmissions and energy
constraints
(iii) Dynamic handling of topologies connections with
mobility based modifications
(iv) The work also provides the identification of the
usable configuration methods, built-in functions
and limitations of hardware communication
platform, which can influence the opportunity of
the topology control.
(v)
The work also provides an implementation analysis
of the suitable and reliable communication
protocol.
(vi) The simulations of QoS based traffic scenarios
brought out the behavior and priority details in
multi-hop network.
used to evaluate the performance. For simulation purpose
this work will use five performance metrics for showing the
expected results. Results are plotted using Xgraph utility of
NS2.To prepare simulation for desired network utility the
following given network setup is provided.
Table 1 Network Setup
No of nodes
20
Radio-propagation
Propagation/TwoRayGround
Antenna model
Antenna/OmniAntenna
Routing protocol
AODV
Simulation dimension
750 X 550
Initial energy in Joules
1000
Simulation time
150 seconds
Traffic
TCP
Channel type
Channel/WirelessChannel
Using TCL script the network scenario is created then
Simulation is executed. And by using AWK file RREQ
packets send, received is captured and also used for the
remaining energy of the nodes. When the simulation starts
then trace file and nam file generated. fig shown below is
the scenario of the Wireless mobile ad-hoc network with six
nodes.
Figure 3: nam file of the network simulation.
 PDR (Packet Delivery Ratio) Graph
Packet delivery ratio is the ratio of number of packets
received at the destination to the number of packets sent
from the source. The performance is better when packet
delivery ratio is high.
V. RESULT EVALUATIONS
In this section the results of practical implementation will
show the effectiveness of proposed scheme. For network
simulation, there are several performance metrics which is
Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
Page 10364
Graph 1: Comparison of PDR Ratio between existing and
Proposed CDTRB
Graph Summary: As the PDR ratio is used to identify the
performance of the approaches using the packet delivery
ratio. It is the ration of number of packet sent to the number
of packet received. In ideal condition it should be high as
possible. For comparing the suggested work of CDTRB, the
above graph interprets the result as an improved PDR ration
than the existing approaches.
 Throughput
It is one of the dimensional parameters of the network which
gives the fraction of the channel capacity used for useful
transmission selects a destination at the beginning of the
simulation i.e., information whether or not data packets
correctly delivered to the destinations.
Graph 3: Comparison of Routing Overhead between
Existing and Proposed CDTRB
Graph Summary: The above graph verifies its results by
minimum routing overhead associated with the suggested
approach. It also shows that the complexity of using the
proposed method is quite less in comparison with the
existing.
 Average End to End Delay
This parameter works as an estimation of time required to
completely deliver the packets from source to destination.
For effective delivery it should be as low as possible. While
comparing the values of existing from proposed, it is found
that suggested CDTRB had lesser average end to end delay
values which guarantees effective communication.
Figure 4.1: Comparison of Average End to End Delay
between Existing and Proposed CDTRB

Graph 2: Comparison of Throughput between Existing and
Proposed CDTRB
Graph Summary: As throughput measure the transmission
efficiency in terms of successfully delivered packets in unit
time for a specified channel bandwidth. The above graph
shows the effectiveness of the suggested approach while
comparing it with the existing. The graph interprets the
constant throughput for several cases which justify the
approach.
 Routing Overhead Load
Routing Load is the ratio of total number of the routing
packets to the total number of received data packets at
destination. The amount of control traffic generated (in bits)
per data traffic delivered (in bits). It should be taken in
terms of the extra load started while executing the suggested
approach than the normal protocol load for the system..
Considering the factors
Jitter
Figure 4.2: Comparison of Jitter between Existing and
Proposed CDTRB
VI.
CONCLUSION
Various approaches had been proposed for topology
control according to the requirements during the last few
years. Among all of these QoS, Mobility & energy
conservation based approaches is getting popularity day by
day. To select the best one between them which satisfy all
the user requirements is a typical task. Thus this paper gives
a wide selection criterion after which it becomes easy to
select better approach. Topology control in ad hoc network
will dynamically improves the performance of the network
by specific orientation of nodes towards these parameters of
Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
Page 10365
quality. Among the various mechanism we have mentioned
approaches for dynamic topology control with a hop-by-hop
routing protocol which increases the network throughput
and reduces the end-to-end delay. Thus to analyze the
effective TC algorithms above mentioned metrics of QoS
needs to be calculated. In this way the required TC can be
find out.
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Jitendra Tiwari, IJECS Volume 4 Issue 2 February, 2015 Page No.10359-10366
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