Fitness a path failure is detected and it causes

                      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 CollegeTirupati,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 efficiently using of the available 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 alternative
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, energy consumption
and then compare with the results of existing  
AOMDV protocol

 

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

 

1.INTRODUCTION:

 

In recent time
there is change in the computer performance, technologies in mobile communications.
Mobile networks want ad hoc networks in which mobile nodes can connect over
line. In MANETs, network security is essential by which the battery life of the
nodes be not strong. Thus to maintain the network span the routing protocol is
sufficient to increment the intensity of the node. Multiple routing protocols
provide paths to flood the packets i.e., route appeal is managable by the  point of supply to achieve reality in
concerning the ways. MANETs will be classified into three generations: first,
second and third generations. In 1970’s the ad hoc network first generation are
called Packet Radio Network (PRNET). In early 1980’s Survivable Adaptive Radio
Network (SURAN)is evolved from PRNET. The function pack of MANETs formed the
routing code regulated and fix the agents like PDA’S, palmtops, notebooks. Few
codes like Bluetooth, IEEE 802.11(WLAN’S) are developed to maintain the MANETs.
For several years from 1970’s to 1990’s there are changes in the generations of
MANET i.e., finally some standards are made to maintain the MANET.At any time
the channel breaks, the Route Error is transmitted. 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 cannot be
transmitted. Whereas in multiple routing additional routes can be referred to
send the data packets. Particle Swarm Optimization (PSO) is the algorithm from
which the fitness function is derivative. Fitness Function is mostly used to
find the optimal path. The optimum 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:

 

The research
proposed highlights the problem of energy consumption in MANET by applying the
Fitness Function technique to optimize the energy consumption in Ad Hoc on
Demand Multipath Distance Vector (AOMDV) routing protocol. The proposed
protocol is called Ad Hoc on Demand Multipath Distance Vector with the Fitness
Function (FF-AOMDV).The fitness function is used to find the optimal path from
the source to the destination to reduce the energy consumption in multipath
routing.

 

1.2 AOMDV Routing protocol:

 

An on-demand
routing protocol, AOMDV has its roots in the Ad hoc On-Demand Distance Vector
(AODV), a popular single-path routing protocol. AOMDV offers two key services:
route discovery and route maintenance. Compared with AODV, AOMDV’s additional
overhead is extra RERRs and RREPs intended for multipath  maintenance and discovery, along with extra
fields to route control packets . Route discovery and route maintenance involve
finding multiple routes from a source to a destination node. AOMDV utilizes
three control packets: the route request (RREQ); the route reply (RREP); and
the route error (RERR).A new multipath routing protocol called the FF-AOMDV routing
protocol is proposed which is a combination of Fitness Function and the AOMDV’s
protocol. The route, which consumes less energy could possibly be (a) the route
that has the shortest distance; (b) the route with the highest level of energy,
or (c) both.

 

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 overcome this challenge. Secure
optimized link state routing protocol is used to provide security to the
protocol. Node Identification to the network is announced and nodes are
authorized by the access control. Access control entity signs a private key Ki,
public key Ki and the certificate Ci required to obtain the group key by an
authorized node. Group key distribution using the generated keys with messages
helps reducing energy consumption. The group key distribution mechanism enables
replacement of the group key periodically or when a node is excluded. The
periodic distribution excludes 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.

 

 

 

 

 

 

 

 

 

 

Fig. 1 illustrates the group key
distribution mechanism

 

Sudhakar Pandey et al 2 Network
performances can be improved by using cross-layer approach. Application of
transmission power control technique to adjust transmission power results in
reduction of energy consumption. ED is considered to calculate the weight   associated with each node. D stands for degree
and E stands for energy. Energy consumption is reduced and network performance
is improved by Control overhead reduction during route discovery and dynamic
adjustment of transmission power. The energy model of wireless sensor network
can be defined as the total energy consumption of the network, including all
its units, be it sensor device components, energy consumed in routing or route
maintenance, topology maintenance or whosoever it may be. Generating an energy
model is an important part of any protocol development and its performance
evaluation. Here we considered a network with n mobile sensor nodes and one
sink node which is static.Energy consumed by sensor device:The
sensor device comprises of processing units, sensing unit, memory unit and
transceiver unit. So, energy consumption of each unit needs to be considered.

E Sensor
Device = E processor + E sensor +

                         Ememory+Etransceiver            (1)                                                                                      

Where E Sensor Device is the total energy consumed by
a sensor device, E processor is the energy consumed by the processing units, E sensor
is the energy consumed by the sensing unit, E memory is the energy consumed by
the memory unit and E transceiver is the energy consumed by the transceiver
unit.Since network lifetime is an important performance criterion Sensor nodes
operate for years. Energy consumption plays an important role in network
lifetime. In working with network mobility is an important factor. About 70% of
network’s energy is consumed in data communication. By taking average of
Received Signal Strength (RSS) values, transmission power can be enhanced 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, which is a
combination of Fitness Function and the AOMDV’s protocol. When a RREQ is
broadcast and received, the source node will have three types of information in
order to find the shortest and optimized route path with minimized energy
consumption. This  include:

·       
Information about network’s each node’s energy level

·       
The distance of every route

·       
The energy consumed in the process of route discovery.

 

The source node will then sends the data packets via
the route with highest Energy level, after which it will calculate its energy
consumption. The optimal route with less distance to destination will consume
less energy and it can be calculated as follows:

Optimum route 1 = ?(n)rene(v(n)) / ? v Vene(v)  
                                                 (7)                                       

In this equation, v represents the vertices (nodes) in the optimum route rand V represent all the vertices in the

network. It compares the energy level among all the
routes and chooses the route with the highest energy level.

The calculation of the shortest route is as follows:

 Optimumroute2=?(n)rdist(e(n))/?eE                                                                       (8)                        

 

Where e represents
the edges (links) in the optimum route rand
E represent all the edges in
the network.

 

The
pseudo-code for the fitness function is provided and Simulations are conducted
to run the FF-AOMDV protocol. In this simulation, an OTcl script has been
written to define 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 produced when running the simulation: trace file for
processing and a network animator (NAM) to visualize the simulation. NAM is a
graphical simulation display tool. It shows the route selection of FF-AOMDV
based on specific parameters. The optimum route refers to the route that has
the highest energy level and the less distance. Priority is given to the energy
level, as seen on the route with the discontinuous arrow. In another scenario,
if the route has the highest energy level, but does not have the shortest
distance, it can also be chosen but with less priority. In some other
scenarios, if the intermediate nodes located between the source and destination
with lesser energy levels compared to other nodes in the network, the fitness
function will choose the route based on the shortest distance available. . Energy,
distances are the fitness values used in the previous work to find the optimal
path in multipath routing.

 

 

 

Fig. 2 Optimum
route selection

same proposed
FF-AOMDV protocol is used along with the bandwidth as a fitness value. Now the
calculations for selecting routes towards the destination will be according to
energy, distance and also bandwidth. The same performance metrics used in the
experiments: 

1. Packet
Delivery Ratio.

2. Throughput.

3. End-to-end
delay.

4. Energy
Consumption.

5. Network
Lifetime.

are used here
to evaluate the results. Thus 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, energy consumption and then compare with the
results of existing AOMDV protocol.

 

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 scenarios as: 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.

 

5. CONCLUSION:

Energy
ef?ciency (EE) is an essential 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 can be reduced by
the prevention of security attacks on routing protocols. Here to find the
optimal path in multipath routing, distance and energy are the fitness values
used. It is proposed to use the network resource bandwidth and calculations in
selecting the routes towards the destination will be according to the distance,
energy and also bandwidth .Thus the proposed work minimizes energy consumption
and maximizes network lifetime.

 

REFERENCES:

1.TejpreetSingh,JaswinderSingh,
and SandeepSharma,

“Energy
ef?cient secured routing protocol for MANETs,” in Wireless Networks, Springer,pp-1001-1009,May2017.

2.SudhakarPandeyandDeepikaAgarwal,”AnEDBasedEnhanced
Energy Ef?cient Cross Layer Model for Mobile Wireless Sensor Network,” in National
Academy Science Letters., Springer, pp 421-427,December 2017.

3.S.Muthurajkumar,S.Ganapathy
and M.Vijayalakshmi, “An Intelligent
Secured and Energy Ef?cient Routing Algorithm for MANETs,” in Wireless personal
communications ,Springer,pp 1753-1769,September 2017.

4.N.Magadevi,V.JawaharSenthilKumarand
A.Suresh, “Maximizing the Network Life Time of Wireless Sensor Networks Using a
Mobile Charger,” in Wireless personal communications .,Springer ,pp 1-11,2017.

5.Wen-KuangKuo
and Shu-Hsien Chu, “Energy Efficiency Optimization for Mobile Hoc Networks,” IEEE
Access, pp 928-940,March 2016

 

 

 

 

 

 

 

 

 

 

 

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