Fitness communication can be done through links in the

     Fitness Function for Energy Efficient                   Multipath Routing Protocol                              in MANETs                        T.

RADHAKRISHNA                                                    V.V.RAMAPRASAD  II.M.Tech student, Department of ComputerScience,                      Professor, Departmentof Computer science,Sree Vidyanikethan Engineering CollegeTirupati, India.      Sree VidyanikethanEngineering College Tirupati, India Abstract:   MobileAd hoc network (MANET) is group of self-routing enabled devices that transmitamong themselves without any certain network infrastructure.

Best services for writing your paper according to Trustpilot

Premium Partner
From $18.00 per page
4,8 / 5
4,80
Writers Experience
4,80
Delivery
4,90
Support
4,70
Price
Recommended Service
From $13.90 per page
4,6 / 5
4,70
Writers Experience
4,70
Delivery
4,60
Support
4,60
Price
From $20.00 per page
4,5 / 5
4,80
Writers Experience
4,50
Delivery
4,40
Support
4,10
Price
* All Partners were chosen among 50+ writing services by our Customer Satisfaction Team

Routing in MANETShas routes between nodes in a topology with many unidirectional links usingminimum resources. Since routing protocols have role in MANETS, theirenergy-awareness make greater network lifetime by simply using the accessibleenergy. In all existing single path routing schemes a new path-discoveryprocess is meant once a path failure is detected and it causes wastage of nodemeasure.

A multipath routing scheme is the alternate to maximize the networklifetime. Energy, distances are the fitness values used in the previous work tofind the optimal path in multipath routing. In this work, it is proposed to usethe network resource bandwidth as a fitness value. The calculations forselecting routes towards the destination will be according to energy, distanceand also bandwidth.

The proposed work is expected to improve the performance ofmobile ad hoc networks by prolonging the lifetime of the network. Theperformance will be evaluated in terms of throughput, packet delivery ratio,end-to-end delay, routing overhead ratio and then compare with the results ofexisting   AOMDV protocol Keywords: Mobile Ad hoc network, routing protocol,multipath routing, fitness value  1.INTRODUCTION:At presentcomputer performance and technologies in mobile system to communicate are beingadvanced. Nodes communication can be done through links in the ad hoc networks.Battery capacity of node is depleted which means network security is needed.

Routingprotocol 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 AdaptiveRadio Network is developed by PRNET in 1980’s.To maintain MANETs there are  standards like Bluetooth, IEEE 802.11.The pathwhich is effective to send packets is taken and the route that is efficient canbe find using Route Request. Route reply gives the view about the hop, residualenergy and bandwidth.

Link breakage can be find by the Route Error. These arethe control packets in the protocol to get the required information about theroute. First the route selection is done based on the control packets. The pathwith less distance and the residual energy of the node can be  considered. When this occurs the sourcetransmit the package over the path to the destination without any interruption.

This can be done with the multipath routing protocol which are referred to theone path routing protocol. In one path routing once the link splits the packetswill not transmit Whereas in multipath, path are  made to sendthe data packets. Fitness function is derived from Particle Swarm Optimization(PSO) algorithm. Fitness Function is mostly used to find the ideal route. Theoptimal path is the one with:·       Lessdistance and·       Exhaustless energy.The optimal pathminimizes the energy loss and increases the network period.

Thus the proposedFF-AOMDV performance in maximizing the network lifetime is possible incomparison with the AOMDV.  1.1.

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

  2. LITERATURE SURVEY:EnergyEfficiency:The authorsTejpreet Singh et al. 1 demonstrates that Energy efficiency and security arethe challenging tasks in the design of a routing protocol. Energy–efficientsecured routing protocol is proposed to get away from this challenge.

Secureoptimized link state routing protocol is used to supply security to theprotocol. Node Identification to the network is declared and nodes are approvedby the access control. Access control entity signs a private key Ki, public keyKi and the certificate Ci needed to obtain the group key by an authorized node.

Group key distribution accepting the generated keys with messages supportreducing energy consumption. The group key distribution mechanism allowssubstitute of the group key periodically or when a node is removed. The cyclicdistribution suspends adversaries with the group key, but not a private key. Incommunity networks, an authorized user may send the group key to anon-authorized friend so as to the friend accesses network resources. Anintrusion detection system (IDS) also triggers the group key distribution.   Fig1.

illustrates the group keydistribution mechanism  Sudhakar Pandey et al 2 Networkaccomplishment can be enriched by using cross-layer approach.Application of sendingpower charge method to arrange communication power issues in decline of energyconsumption. ED is examined to consult the weight   assisted with each node. D views for degreeand E views for energy.

Energy consumption is reduced and network accomplishmentis enriched by Control overhead reduction while route discovery and dynamicimprovement of transmission power is done. The energy model of wireless sensor networkcan be stated as the total energy consumption of the network, arrange all itsunits, be it sensor device components, energy used in routing or routemaintenance, topology maintenance or whosoever it may be. Creating an energymodel 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 thatis static. Energy consumed by sensor device: The sensor device consistsof processing units, sensing unit, memory unit and transceiver unit.

So, energyconsumption 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 asensor device, E processor is the energy depleted by the processing units, E sensoris the energy use up by the sensing unit, E memory is the energy spent by thememory unit and E transceiver is the energy consumed by the transceiver unit. Sincenetwork 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 ofReceived Signal Strength (RSS) values, transmission power is improved byCross-Layer design approach for Power Control.  S.Muthurajkumar et al 3 Two important aspects of Mobile Ad Hoc Networks (MANETs) areEnergy consumption and security.

Using trust management, key management,?rewalls and intrusion detection security is provided in MANET. It is essentialto consider the energy and security aspects in routing algorithms since energyand security are important for communication. Energy consumption can be reducedautomatically by the prevention of security attacks on routing protocols andcluster based routing. Trust score evaluation, routing and thresholdsetting using the trust values are the phases in trust based secure routingalgorithm. In trust score evaluation process the trust score for individualnodes are calculated based on constraints like nodes which are genuinelysending their acknowledgement to neighbors when they received the packets aretreated as first group and  the nodeswhich 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 percentageof  acknowledgements.

  TS1i=(ACK/RP)*100                                    (2)                                 ACK = No. of acknowledgements sent to the neighbors , TS1i = First trustscore in percentage for ith node, RP = No. of packets received from neighbors second trust score is computed using Eq (3) which calculatesthe dropped packets TS1i=100-((DP/TDP)*100)                           (3)                                    DP = No.

of packets dropped, TDP = Total number ofpackets dropped in network. TS2i = Second trust score percentagefor ith node. The overall trust score of the particular nodeis calculated using Eq. (4)     TSi=(TSli+TS2i)/2                                      (4)                                  TS1i = First trust score for node i, TS2i = -Secondtrust score for node I, TSi = Overall trust score for node i. Fordeveloping a cluster based network a clustering scheme is developed withclusters. A Cluster based Energy Ef?cient Secure Routing Algorithm (CEESRA) is proposedfor providing effective routing. Malicious nodes can be avoided and detectedusing the trust score. A dynamic clustering technique not only uses lowmobility nodes, energy consumption, trust values and distance parameters forproviding the energy ef?cient secure routing algorithm.

The proposed algorithmprovides 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 havelimited power resource in Wireless Sensor Networks. To recharge the batteriesof the wireless nodes Wireless charging is an alternative. Using a singlemobile anchor a wireless recharging and also localization are proposed.Localization provides the position information. Static node is located by themobile anchor first and then it receives the battery level. Later static nodesare recharged if the static node battery is lesser than the threshold limit.

Fundamentalunit of sensor network is sensor node. It comprises of   sensors, microprocessor, transceiver , memoryand power supply. An Adhoc network with a collection of number of sensor nodesis Wireless Sensor Network. It is used in many ?elds like disaster rescue, intrusiondetection and in health care applications. Gateway between the WSN and theother network is sink node. Noise Ratio (SNR), increased ef?ciency, improvedrobustness and scalability are the advantages in WSN. In designing WSN thereare several challenges like software development, deployment, localization,hardware design, routing protocol and coverage. For effective datacommunication and computation sensor node must be accurate.

In the advancementof wireless sensor networks effective localization system must be developed.Rangefree localization algorithms do not require distance or angle measurements.Along with the wireless charging localization problem is addressed here. Sensorsenses the data and communicates with the base station through Multi hopcommunication.

In Wireless Rechargeable Sensor Network an effective andcontrollable energy harvesting scheme is to be adopted. Thus proposed methodimproves the network’s lifetime. Wen-KuangKuoet al 5 The energy consumption of battery-powered mobile devices can beincreased by measured in bits per Joule for MANETs.

By jointly consideringrouting multimedia applications the energy ef?ciency (EE) is an essentialaspect of mobile ad hoc networks (MANETs). Based on the cross-layer designparadigm EE optimization is, traf?c scheduling, and power control a non convexmixed integer nonlinear programming is modeled as a problem. Branch and bound(BB) algorithm is devised to ef?ciently solve this optimal problem.EEOPTIMIZATION PROBLEM:A MANET comprised of one set of stationary nodes N connected by a set L oflinks. We consider everylink l = nt-> nr to be directional,where nt and nr are thetransmitter and receiver of l,respectivelyMATHMATICAL MODEL FOR THEEE 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. Transmissionpower on link l at time slot t, i.e., , is continuously adjustedin given interval 0, pmax.

constraint                (                                                    (6)Note thatbeing allowed to transmit does not necessarily mean a transmission actuallyoccurs, which is decided by the optimization algorithm. With recent advances ininformation and communication technology (ICT), MANETs become a promising andgrowing technique. Multimedia services like video on-demand, remote education,surveillance, and health monitoring are supported using MANETs. Energy is ascarce resource for mobile devices, which are typically driven by batteries.Using cooperative multi-input-single-output transmissions authors maximized EEfor the MANET. By designing resource allocation mechanisms cross-layeroptimization can substantially enhance EE. By jointly computing routing path,transmission schedule, and power control to the network, link, and PHY layersacross-layer optimization framework is proposed to enhance EE.

The transmission power of every active node ineach time slot is specified by the power control problem. To globallyoptimize,a novel BB algorithm is developed. In terms of computationalcomplexity proposed algorithm outperformed the reference algorithm. Byexploiting the cross-layer design principle a solution to determine the optimalEE of the MANET is provided. Distributed algorithms and protocols are designedto find the optimal EE. Any technique which can optimize non convex MINLPproblem in a distributed manner is not proposed. Thus distributed algorithms andprotocols are developed using approximation algorithms. The guarantee foracquiring the optimal solution is the disadvantage of approximation algorithm.

Acustomized BB algorithm for the optimization of the problem is proposed. Anovel lower bounding strategy and branching rule is designed and incorporatedin the proposed BB algorithm. To optimize EE of MANETs distributed protocolsand algorithms are implemented. To improve EE of MANETs novel distributedprotocols and algorithms are developed. 3. PROPOSED SYSTEM:A newmultipath routing protocol called the FF-AOMDV routing protocol is acombination of Fitness Function and the AOMDV’s protocol. When a RREQ isbroadcast and taken, the source node can have three kinds of data to get theshortest and optimized  path with lessenergy consumption.

This  has:1.Information about network’s every node’s energy level 2.The distance of each path 3.Theenergy consumed in the method of route     discovery. The source node will transmit the data packets by thepath that has more Energy level, through that it can get the energyconsumption.

Through the simulation, an OTcl script is taken to demonstrate thenetwork parameters and topology, such as traffic source, number of nodes, queuesize, node speed, routing protocols used and many other parameters. Two filesare generated when loading the simulation: trace file for processing and a networkanimator (NAM) to see the simulation.     Fig. 2 Optimumroute selection  NAM is agraphical simulation display tool. It makes the route selection of FF-AOMDVdepending on certain parameters. The optimum route is  the route which has the best energy level andthe minimal distance. Preference is likely to the energy level, regarding theroute with the disordered arrow.In other criteria, if the path contains maximumenergy level, but does not has the smallest distance, it will be taken but withless preference.

In other scenarios, if the intermediate nodes placed betweenthe source and destination with less energy levels distinguished to remainingnodes in the network, the fitness function can select the route depending onthe smallest distance. Available Bandwidth: Bandwidth is also known as the data transferrate. It describes the data sent out by means of connection over a specifiedtime and the bandwidth is expressed in bps. Bandwidth is the bit-rate of theexisting or the consumed information capacity uttered normally in metricmultiples of bits per second. As the bandwidth is kept high the energyconsumption is also high.

The data packets send increases and the energyconsumed at each node is also high. The transmission power consumption is highbecause the packets send are more. When the bandwidth is taken as a parameteralong with the distance and energy, energy consumption varies as:1. when distanceincreases energy consumption also increases and when the route distance is lessenergy consumed will be low.

2. whenbandwidth is high energy consumption  isalso high  and when it is  less energy consumed will be low. Thusbandwidth is the parameter considered here and the simulation hasscenarios like node speed, packet size and simulation time.

simulations are doneby keeping the scenariosas:varying the packetsize(64,128,256,512,1024) and keepboth 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 mathematicalmodel is to be find based on the three parameters energy, distance andbandwidth.Route reply’s are sent from the specified intermediate nodes by whichhop count,residual energy, Qlength,bandwidth values are taken.Let the formulabe                    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 takingthe values of the parameters optimal path can be find.

       4. CONCLUSION:Energyef?ciency (EE) is an important aspect of mobile ad hoc networks(MANETs).secured routing protocol is proposed which is energy efficient andsecurity is provided for both link and message without relying on the thirdparty. A secure communication among the participating nodes is offered by theenvironment of MANETS.

Energy consumption plays an important role in networklifetime. Since network mobility is an important factor and network’s energy isconsumed in data communication, Cross-Layer design approach is used to enhancethe transmission power for power control. Energy consumption will be decreased bythe avoidance of security attacks on routing protocols and cluster basedrouting and for this an algorithm A Cluster based Energy Ef?cient SecureRouting Algorithm (CEESRA) is implemented to provide efficient routing. Anotheralgorithm branch and bound (BB) is implemented to solve the energy efficiency. Thusthe proposed work minimizes energy consumption and maximizes network lifetime.

     REFERENCES:1 TejpreetSingh,JaswinderSingh,andSandeepSharma,      “Energy ef?cient secured routing protocolfor       MANETs,”inWirelessNetworks,Springer,  pp.1001-       1009, May 2017                              2SudhakarPandey and DeepikaAgarwal , “An ED      Based Enhanced Energy Ef?cient Cross LayerModel      for  MobileWireless Sensor Network,” in National      Academy Science Letters., Springer, pp.421-427,       December2017.

3 S.Muthurajkumar,S.Ganapathyand M.

Vijayalakshmi        , “An Intelligent Secured and EnergyEf?cient      Routing Algorithm for MANETs,” in Wireless      Personal Communications,Springer, pp.1753-1769,      September 2017.4N.Magadevi,V.

JawaharSenthilKumar and 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-KuangKuoand Shu-Hsien Chu,”Energy       Efficiency Optimization for Mobile HocNetworks,”        IEEEAccess,  pp.

928-940, March 2016