Fitness Tirupati, India Abstract: Mobile Ad hoc network (MANET)

     
Fitness Function for Energy Efficient     

              Multipath Routing Protocol

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                             in MANETs

     

 

                 
T.RADHAKRISHNA                                                    V.V.RAMAPRASAD

 II.M.Tech student, Department of Computer
Science,                      Professor, Department
of Computer science,

Sree Vidyanikethan Engineering College
Tirupati, India.      Sree Vidyanikethan
Engineering College Tirupati, India

 

Abstract:   Mobile
Ad hoc network (MANET) is group of self-routing enabled devices that transmit
among themselves without any certain network infrastructure. Routing in MANETS
has routes between nodes in a topology with many unidirectional links using
minimum resources. Since routing protocols have role in MANETS, their
energy-awareness make greater network lifetime by simply using the accessible
energy. In all existing single path routing schemes a new path-discovery
process is meant once a path failure is detected and it causes wastage of node
measure. A multipath routing scheme is the alternate to maximize the network
lifetime. Energy, distances are the fitness values used in the previous work to
find the optimal path in multipath routing. In this work, it is proposed to use
the network resource bandwidth as a fitness value. The calculations for
selecting routes towards the destination will be according to energy, distance
and also bandwidth. The proposed work is expected to improve the performance of
mobile ad hoc networks by prolonging the lifetime of the network. The
performance will be evaluated in terms of throughput, packet delivery ratio,
end-to-end delay, routing overhead ratio and then compare with the results of
existing   AOMDV protocol

 

Keywords:
 Mobile Ad hoc network, routing protocol,
multipath routing, fitness value

 

1.INTRODUCTION:

At present
computer performance and technologies in mobile system to communicate are being
advanced. Nodes communication can be done through links in the ad hoc networks.
Battery capacity of node is depleted which means network security is needed. Routing
protocol made the node energy effective that represent the lifetime of network.
Lifetime of a network must be maximized. There are 3 generations in MANETs:
first generation is the Packet Radio Network in 1970’s.Survivable Adaptive
Radio Network is developed by PRNET in 1980’s.To maintain MANETs there are  standards like Bluetooth, IEEE 802.11.The path
which is effective to send packets is taken and the route that is efficient can
be find using Route Request. Route reply gives the view about the hop, residual
energy and bandwidth. Link breakage can be find by the Route Error. These are
the control packets in the protocol to get the required information about the
route. First the route selection is done based on the control packets. The path
with less distance and the residual energy of the node can be  considered. When this occurs the source
transmit the package over the path to the destination without any interruption.
This can be done with the multipath routing protocol which are referred to the
one path routing protocol. In one path routing once the link splits the packets
will not transmit Whereas in multipath, path are

 

made to send
the data packets. Fitness function is derived from Particle Swarm Optimization
(PSO) algorithm. Fitness Function is mostly used to find the ideal route. The
optimal path is the one with:

·       
Less
distance and

·       
Exhaust
less energy.

The optimal path
minimizes the energy loss and increases the network period. Thus the proposed
FF-AOMDV performance in maximizing the network lifetime is possible in
comparison with the AOMDV.

 

1.1.Existing system:

Here AODV (ad hoc on-demand
distance vector) is the protocol from which AOMDV can be taken i.e.,AOMDV
creates the multipath between the source and destination. AOMDV has route _list
which is not present in AODV and it has advertised_hopcount. As in AODV the
route reply contains the information regarding the node in AOMDV. Damage in
link happens by which multiple paths are required to send the data packets. All
the process in AOMDV is done through control packets (RREQ,RREP and
RERR).Protocol can be designed based on distance, energy and bandwidth factor.

 

 

2. LITERATURE SURVEY:

Energy
Efficiency:

The authors
Tejpreet Singh et al. 1 demonstrates that Energy efficiency and security are
the challenging tasks in the design of a routing protocol. Energy–efficient
secured routing protocol is proposed to get away from this challenge. Secure
optimized link state routing protocol is used to supply security to the
protocol. Node Identification to the network is declared and nodes are approved
by the access control. Access control entity signs a private key Ki, public key
Ki and the certificate Ci needed to obtain the group key by an authorized node.
Group key distribution accepting the generated keys with messages support
reducing energy consumption. The group key distribution mechanism allows
substitute of the group key periodically or when a node is removed. The cyclic
distribution suspends adversaries with the group key, but not a private key. In
community networks, an authorized user may send the group key to a
non-authorized friend so as to the friend accesses network resources. An
intrusion detection system (IDS) also triggers the group key distribution.

 

 

 

Fig1. illustrates the group key
distribution mechanism

 

 

Sudhakar Pandey et al 2 Network
accomplishment can be enriched by using cross-layer approach.Application of sending
power charge method to arrange communication power issues in decline of energy
consumption. ED is examined to consult the weight   assisted with each node. D views for degree
and E views for energy. Energy consumption is reduced and network accomplishment
is enriched by Control overhead reduction while route discovery and dynamic
improvement of transmission power is done. The energy model of wireless sensor network
can be stated as the total energy consumption of the network, arrange all its
units, be it sensor device components, energy used in routing or route
maintenance, topology maintenance or whosoever it may be. Creating an energy
model is an vital part of any protocol growth and its performance estimation.
Here a network is treated with n mobile sensor nodes and single sink node that
is static. Energy consumed by sensor device: The sensor device consists
of processing units, sensing unit, memory unit and transceiver unit. So, energy
consumption of each unit made considered as:

E Sensor Device = E processor + E sensor +

                              Ememory+Etransceiver            (1)                                                                                      

Where E Sensor Device is the energy consumed by a
sensor device, E processor is the energy depleted by the processing units, E sensor
is the energy use up by the sensing unit, E memory is the energy spent by the
memory unit and E transceiver is the energy consumed by the transceiver unit. Since
network lifespan is an vital aspect criterion Sensor nodes perform for years.
clearly 70% of network’s energy is used  in data communication. By getting average of
Received Signal Strength (RSS) values, transmission power is improved by
Cross-Layer design approach for Power Control.

 

S.Muthurajkumar 
et al 3 Two important aspects of Mobile Ad Hoc Networks (MANETs) are
Energy consumption and security. Using trust management, key management,
?rewalls and intrusion detection security is provided in MANET. It is essential
to consider the energy and security aspects in routing algorithms since energy
and security are important for communication. Energy consumption can be reduced
automatically by the prevention of security attacks on routing protocols and
cluster based routing. Trust score evaluation, routing and threshold
setting using the trust values are the phases in trust based secure routing
algorithm. In trust score evaluation process the trust score for individual
nodes are calculated based on constraints like nodes which are genuinely
sending their acknowledgement to neighbors when they received the packets are
treated as first group and  the nodes
which drop more packets are considered as and 
the nodes which drop more packets are considered as group two nodes.
Now, the initial trust score is computed using the Eq that represents the percentage
of  acknowledgements.

 

 TS1i=(ACK/RP)*100                                    (2)

                                

ACK = No. of acknowledgements sent to the neighbors , TS1i = First trust
score in percentage for ith node, RP = No. of packets received from 
neighbors second trust score is computed using Eq (3) which calculates
the dropped packets

 

TS1i=100-((DP/TDP)*100)                           (3)                                   

 

DP = No. of packets dropped, TDP = Total number of
packets dropped in network. TS2i = Second trust score percentage
for ith node. The overall trust score of the particular node
is calculated using Eq. (4)

 

    TSi=(TSli+TS2i)/2                                      (4)                                  

TS1i = First trust score for node i, TS2i = -Second
trust score for node I, TSi = Overall trust score for node i.

 For
developing a cluster based network a clustering scheme is developed with
clusters. A Cluster based Energy Ef?cient Secure Routing Algorithm (CEESRA) is proposed
for providing effective routing. Malicious nodes can be avoided and detected
using the trust score. A dynamic clustering technique not only uses low
mobility nodes, energy consumption, trust values and distance parameters for
providing the energy ef?cient secure routing algorithm. The proposed algorithm
provides better performance in terms of packet drop ratio, residual energy,
security and throughput when compared to the existing techniques.

 

 N.Magadevi et al 4 The wireless nodes have
limited power resource in Wireless Sensor Networks. To recharge the batteries
of the wireless nodes Wireless charging is an alternative. Using a single
mobile anchor a wireless recharging and also localization are proposed.
Localization provides the position information. Static node is located by the
mobile anchor first and then it receives the battery level. Later static nodes
are recharged if the static node battery is lesser than the threshold limit. Fundamental
unit of sensor network is sensor node. It comprises of   sensors, microprocessor, transceiver,memory
and power supply.An Adhoc network with a collection of number of sensor nodes
is Wireless Sensor Network. It is used in many ?elds like disaster rescue, intrusion
detection and in health care applications. Gateway between the WSN and the
other network is sink node. Noise Ratio (SNR), increased ef?ciency, improved
robustness and scalability are the advantages in WSN. In designing WSN there
are several challenges like software development, deployment, localization,
hardware design, routing protocol and coverage. For effective data
communication and computation sensor node must be accurate. In the advancement
of wireless sensor networks effective localization system must be developed.Range
free localization algorithms do not require distance or angle measurements.
Along with the wireless charging localization problem is addressed here. Sensor
senses the data and communicates with the base station through Multi hop
communication. In Wireless Rechargeable Sensor Network an effective and
controllable energy harvesting scheme is to be adopted. Thus proposed method
improves the network’s lifetime.

 

Wen-KuangKuo
et al 5 The energy consumption of battery-powered mobile devices can be
increased by measured in bits per Joule for MANETs. By jointly considering
routing multimedia applications the energy ef?ciency (EE) is an essential
aspect of mobile ad hoc networks (MANETs). Based on the cross-layer design
paradigm EE optimization is, traf?c scheduling, and power control a non convex
mixed integer nonlinear programming is modeled as a problem. Branch and bound
(BB) algorithm is devised to ef?ciently solve this optimal problem.

EE
OPTIMIZATION PROBLEM:

A MANET comprised of one set of stationary nodes N connected by a set L of
links. We consider every

link l = nt
-> nr to be directional,
where nt and nr are the
transmitter and receiver of l,
respectively

MATHMATICAL MODEL FOR THE
EE OPTIMIZATION PROBLEM:

For every link l at every time slot t,
binary variable  as

 

  (),                                                (5)                  

Where ? = 
(1 ,…., T) and T is the total number of scheduled time slots. Transmission
power on link l at time slot t, i.e., , is continuously adjusted
in given interval 0, pmax.

constraint      

 

        

 (                                                    (6)

Note that
being allowed to transmit does not necessarily mean a transmission actually
occurs, which is decided by the optimization algorithm. With recent advances in
information and communication technology (ICT), MANETs become a promising and
growing technique. Multimedia services like video on-demand, remote education,
surveillance, and health monitoring are supported using MANETs. Energy is a
scarce resource for mobile devices, which are typically driven by batteries.
Using cooperative multi-input-single-output transmissions authors maximized EE
for the MANET. By designing resource allocation mechanisms cross-layer
optimization can substantially enhance EE. By jointly computing routing path,
transmission schedule, and power control to the network, link, and PHY layers
across-layer optimization framework is proposed to enhance EE. The transmission power of every active node in
each time slot is specified by the power control problem. To globally
optimize,a novel BB algorithm is developed. In terms of computational
complexity proposed algorithm outperformed the reference algorithm. By
exploiting the cross-layer design principle a solution to determine the optimal
EE of the MANET is provided. Distributed algorithms and protocols are designed
to find the optimal EE. Any technique which can optimize non convex MINLP
problem in a distributed manner is not proposed. Thus distributed algorithms and
protocols are developed using approximation algorithms. The guarantee for
acquiring the optimal solution is the disadvantage of approximation algorithm. A
customized BB algorithm for the optimization of the problem is proposed. A
novel lower bounding strategy and branching rule is designed and incorporated
in the proposed BB algorithm. To optimize EE of MANETs distributed protocols
and algorithms are implemented. To improve EE of MANETs novel distributed
protocols and algorithms are developed.

 

3. PROPOSED SYSTEM:

A new
multipath routing protocol called the FF-AOMDV routing protocol is a
combination of Fitness Function and the AOMDV’s protocol. When a RREQ is
broadcast and taken, the source node can have three kinds of data to get the
shortest and optimized  path with less
energy consumption. This  has:

1.Information about network’s every node’s energy level

2.The distance of each path

3.The
energy consumed in the method of route

     discovery.

The source node will transmit the data packets by the
path that has more Energy level, through that it can get the energy
consumption. Through the simulation, an OTcl script is taken to demonstrate the
network parameters and topology, such as traffic source, number of nodes, queue
size, node speed, routing protocols used and many other parameters. Two files
are generated when loading the simulation: trace file for processing and a network
animator (NAM) to see the simulation.

 

 

 

 

Fig. 2 Optimum
route selection

 

NAM is a
graphical simulation display tool. It makes the route selection of FF-AOMDV
depending on certain parameters. The optimum route is  the route which has the best energy level and
the minimal distance. Preference is likely to the energy level, regarding the
route with the disordered arrow.In other criteria, if the path contains maximum
energy level, but does not has the smallest distance, it will be taken but with
less preference. In other scenarios, if the intermediate nodes placed between
the source and destination with less energy levels distinguished to remaining
nodes in the network, the fitness function can select the route depending on
the smallest distance.

 

Available Bandwidth:

 Bandwidth is also known as the data transfer
rate. It describes the data sent out by means of connection over a specified
time and the bandwidth is expressed in bps. Bandwidth is the bit-rate of the
existing or the consumed information capacity uttered normally in metric
multiples of bits per second. As the bandwidth is kept high the energy
consumption is also high. The data packets send increases and the energy
consumed at each node is also high. The transmission power consumption is high
because the packets send are more. When the bandwidth is taken as a parameter
along with the distance and energy, energy consumption varies as:

1. when distance
increases energy consumption also increases and when the route distance is less
energy consumed will be low.

2. when
bandwidth is high energy consumption  is
also high  and when it is  less energy consumed will be low. Thus
bandwidth is the parameter considered here and the

simulation has
scenarios like node speed, packet size and simulation time.simulations are done
by keeping the scenariosas:varying the packetsize(64,128,256,512,1024) and keep
both the node speed and simulation time fixed. Packet delivery ratio,
Throughput, End-to-end delay, Routing overhead ratio are   the performance metrics used to test the scenarios.
In the proposed system as the bandwidth is the other parameter the mathematical
model is to be find based on the three parameters energy, distance and
bandwidth.Route reply’s are sent from the specified intermediate nodes by which
hop count,residual energy, Qlength,bandwidth values are taken.Let the formula
be

 

                  Ax1+bx2+cx3+dx4/4                     (7)              

 where   x1-> hop count,

              x2->Q length,

              x3->residual energy,

              x4->bandwidth.

  And a,b,c,d are based on priority.By taking
the values of the parameters optimal path can be find.

 

 

 

 

 

 

 

4. CONCLUSION:

Energy
ef?ciency (EE) is an important aspect of mobile ad hoc networks
(MANETs).secured routing protocol is proposed which is energy efficient and
security is provided for both link and message without relying on the third
party. A secure communication among the participating nodes is offered by the
environment of MANETS. Energy consumption plays an important role in network
lifetime. Since network mobility is an important factor and network’s energy is
consumed in data communication, Cross-Layer design approach is used to enhance
the transmission power for power control. Energy consumption will be decreased by
the avoidance of security attacks on routing protocols and cluster based
routing and for this an algorithm A Cluster based Energy Ef?cient Secure
Routing Algorithm (CEESRA) is implemented to provide efficient routing. Another
algorithm branch and bound (BB) is implemented to solve the energy efficiency. Thus
the proposed work minimizes energy consumption and maximizes network lifetime.

 

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