Fitness Routing in MANETS has routes between nodes

                      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 CollegeTirupati,India Abstract:   MobileAd hoc network (MANET) is group of self-routing enabled devices that transmitamong themselves without any certain network infrastructure. Routing in MANETShas routes between nodes in a topology with many unidirectional links usingminimum resources. Since routing protocols have  role in MANETS, their energy-awareness makegreater network lifetime by efficiently using of the available energy. In allexisting single path routing schemes a new path-discovery process is meant oncea path failure is detected and it causes wastage of node measure.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

A multipath routing scheme is the alternativeto maximize the network lifetime. Energy, distances are the fitness values usedin the previous work to find the optimal path in multipath routing. In thiswork, it is proposed to use the network resource bandwidth as a fitness value.

The calculations for selecting routes towards the destination will be accordingto energy, distance and also bandwidth. The proposed work is expected toimprove the performance of mobile ad hoc networks by prolonging the lifetime ofthe network. The performance will be evaluated in terms of throughput, packetdelivery ratio, end-to-end delay, routing overhead ratio, energy consumptionand then compare with the results of existing  AOMDV protocol Keywords: Mobile Ad hoc network, routing protocol,multipath routing, fitness value  1.INTRODUCTION: In recent timethere is change in the computer performance, technologies in mobile communications.Mobile networks want ad hoc networks in which mobile nodes can connect overline. In MANETs, network security is essential by which the battery life of thenodes be not strong. Thus to maintain the network span the routing protocol issufficient to increment the intensity of the node.

Multiple routing protocolsprovide paths to flood the packets i.e., route appeal is managable by the  point of supply to achieve reality inconcerning the ways. MANETs will be classified into three generations: first,second and third generations. In 1970’s the ad hoc network first generation arecalled Packet Radio Network (PRNET). In early 1980’s Survivable Adaptive RadioNetwork (SURAN)is evolved from PRNET. The function pack of MANETs formed therouting code regulated and fix the agents like PDA’S, palmtops, notebooks. Fewcodes 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 ofMANET i.e., finally some standards are made to maintain the MANET.At any timethe channel breaks, the Route Error is transmitted.

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 the one path routingprotocol. In one path routing once the link splits the packets cannot betransmitted. Whereas in multiple routing additional routes can be referred tosend the data packets. Particle Swarm Optimization (PSO) is the algorithm fromwhich the fitness function is derivative. Fitness Function is mostly used tofind the optimal path. The optimum path is the one with:·       Lessdistance and·       Exhaustless energy.              The optimal path minimizes theenergy loss and increases the network period.

Thus the proposed FF-AOMDV performancein maximizing the network lifetime is possible in comparison with the AOMDV.  1.1  Existing system: The researchproposed highlights the problem of energy consumption in MANET by applying theFitness Function technique to optimize the energy consumption in Ad Hoc onDemand Multipath Distance Vector (AOMDV) routing protocol. The proposedprotocol is called Ad Hoc on Demand Multipath Distance Vector with the FitnessFunction (FF-AOMDV).The fitness function is used to find the optimal path fromthe source to the destination to reduce the energy consumption in multipathrouting.

 1.2 AOMDV Routing protocol: An on-demandrouting 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 additionaloverhead is extra RERRs and RREPs intended for multipath  maintenance and discovery, along with extrafields to route control packets . Route discovery and route maintenance involvefinding multiple routes from a source to a destination node.

AOMDV utilizesthree control packets: the route request (RREQ); the route reply (RREP); andthe route error (RERR).A new multipath routing protocol called the FF-AOMDV routingprotocol is proposed which is a combination of Fitness Function and the AOMDV’sprotocol. The route, which consumes less energy could possibly be (a) the routethat has the shortest distance; (b) the route with the highest level of energy,or (c) both.  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 overcome this challenge. Secureoptimized link state routing protocol is used to provide security to theprotocol. Node Identification to the network is announced and nodes areauthorized 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 anauthorized node. Group key distribution using the generated keys with messageshelps reducing energy consumption.

The group key distribution mechanism enablesreplacement of the group key periodically or when a node is excluded. Theperiodic distribution excludes adversaries with the group key, but not aprivate key. In community networks, an authorized user may send the group keyto a non-authorized friend so as to the friend accesses network resources. Anintrusion detection system (IDS) also triggers the group key distribution.          Fig.

1 illustrates the group keydistribution mechanism Sudhakar Pandey et al 2 Networkperformances can be improved by using cross-layer approach. Application oftransmission power control technique to adjust transmission power results inreduction of energy consumption. ED is considered to calculate the weight   associated with each node. D stands for degreeand E stands for energy. Energy consumption is reduced and network performanceis improved by Control overhead reduction during route discovery and dynamicadjustment of transmission power. The energy model of wireless sensor networkcan be defined as the total energy consumption of the network, including allits units, be it sensor device components, energy consumed in routing or routemaintenance, topology maintenance or whosoever it may be.

Generating an energymodel is an important part of any protocol development and its performanceevaluation. Here we considered a network with n mobile sensor nodes and onesink node which is static.Energy consumed by sensor device:Thesensor device comprises of processing units, sensing unit, memory unit andtransceiver unit. So, energy consumption of each unit needs to be considered.E SensorDevice = E processor + E sensor +                          Ememory+Etransceiver            (1)                                                                                      Where E Sensor Device is the total energy consumed bya sensor device, E processor is the energy consumed by the processing units, E sensoris the energy consumed by the sensing unit, E memory is the energy consumed bythe memory unit and E transceiver is the energy consumed by the transceiverunit.Since network lifetime is an important performance criterion Sensor nodesoperate for years.

Energy consumption plays an important role in networklifetime. In working with network mobility is an important factor. About 70% ofnetwork’s energy is consumed in data communication.

By taking average ofReceived Signal Strength (RSS) values, transmission power can be enhanced 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 andthreshold setting using the trust values are the phases in trust based securerouting algorithm.

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,respectively MATHMATICAL 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 globally optimize ,anovel BB algorithm is developed. In terms of computational complexity proposedalgorithm outperformed the reference algorithm. By exploiting the cross-layer designprinciple a solution to determine the optimal EE of the MANET is provided. Distributedalgorithms and protocols are designed to find the optimal EE.

Any techniquewhich can optimize non convex MINLP problem in a distributed manner is notproposed. Thus distributed algorithms and protocols are developed usingapproximation algorithms. The guarantee for acquiring the optimal solution isthe disadvantage of approximation algorithm. A customized BB algorithm for theoptimization of the problem is proposed.

A novel lower bounding strategy andbranching rule is designed and incorporated in the proposed BB algorithm. Tooptimize EE of MANETs distributed protocols and algorithms are implemented. Toimprove EE of MANETs novel distributed protocols and algorithms are developed. 3.

PROPOSED SYSTEM:A newmultipath routing protocol called the FF-AOMDV routing protocol, which is acombination of Fitness Function and the AOMDV’s protocol. When a RREQ isbroadcast and received, the source node will have three types of information inorder to find the shortest and optimized route path with minimized energyconsumption. 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 viathe route with highest Energy level, after which it will calculate its energyconsumption. The optimal route with less distance to destination will consumeless 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 thenetwork. It compares the energy level among all theroutes 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 representsthe edges (links) in the optimum route randE represent all the edges inthe network.

 Thepseudo-code for the fitness function is provided and Simulations are conductedto run the FF-AOMDV protocol. In this simulation, an OTcl script has beenwritten to define the network parameters and topology, such as traffic source,number of nodes, queue size, node speed, routing protocols used and many otherparameters. Two files are produced when running the simulation: trace file forprocessing and a network animator (NAM) to visualize the simulation. NAM is agraphical simulation display tool.

It shows the route selection of FF-AOMDVbased on specific parameters. The optimum route refers to the route that hasthe highest energy level and the less distance. Priority is given to the energylevel, 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 shortestdistance, it can also be chosen but with less priority. In some otherscenarios, if the intermediate nodes located between the source and destinationwith lesser energy levels compared to other nodes in the network, the fitnessfunction will choose the route based on the shortest distance available. . Energy,distances are the fitness values used in the previous work to find the optimalpath in multipath routing.    Fig.

2 Optimumroute selection same proposedFF-AOMDV protocol is used along with the bandwidth as a fitness value. Now thecalculations for selecting routes towards the destination will be according toenergy, distance and also bandwidth. The same performance metrics used in theexperiments: 1. PacketDelivery Ratio.2. Throughput.3.

End-to-enddelay.4. EnergyConsumption.

5. NetworkLifetime.are used hereto evaluate the results.

Thus the proposed work is expected to improve theperformance of mobile ad hoc networks by prolonging the lifetime of thenetwork. The performance will be evaluated in terms of throughput, packetdelivery ratio, end-to-end delay, energy consumption and then compare with theresults of existing AOMDV protocol. Available Bandwidth:            Bandwidth is also known as the datatransfer rate. It describes the data sent out by means of connection over aspecified time and the bandwidth is expressed in bps. Bandwidth is the bit-rateof the existing 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 scenarios as: varying the packetsize(64,128,256,512,1024) andkeep 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 thescenarios. In the proposed system as the bandwidth is the other parameter themathematical model is to be find based on the three parameters energy, distanceand bandwidth. 5. CONCLUSION:Energyef?ciency (EE) is an essential 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 can be reduced bythe prevention of security attacks on routing protocols. Here to find theoptimal path in multipath routing, distance and energy are the fitness valuesused. It is proposed to use the network resource bandwidth and calculations inselecting the routes towards the destination will be according to the distance,energy and also bandwidth .Thus the proposed work minimizes energy consumptionand maximizes network lifetime.

 REFERENCES:1.TejpreetSingh,JaswinderSingh,and SandeepSharma,”Energyef?cient secured routing protocol for MANETs,” in Wireless Networks, Springer,pp-1001-1009,May2017.2.SudhakarPandeyandDeepikaAgarwal,”AnEDBasedEnhancedEnergy Ef?cient Cross Layer Model for Mobile Wireless Sensor Network,” in NationalAcademy Science Letters., Springer, pp 421-427,December 2017.

3.S.Muthurajkumar,S.Ganapathyand M.Vijayalakshmi, “An IntelligentSecured and Energy Ef?cient Routing Algorithm for MANETs,” in Wireless personalcommunications ,Springer,pp 1753-1769,September 2017.4.N.Magadevi,V.JawaharSenthilKumarandA.Suresh, “Maximizing the Network Life Time of Wireless Sensor Networks Using aMobile Charger,” in Wireless personal communications .,Springer ,pp 1-11,2017.5.Wen-KuangKuoand Shu-Hsien Chu, “Energy Efficiency Optimization for Mobile Hoc Networks,” IEEEAccess, pp 928-940,March 2016