In recent years there is advancement in thecomputer performance, technologies in mobile communications. Wireless networkswant networks in which mobile nodes will connect over line. In MANETs, networksafety is essential by that the battery extent of the nodes be not strong.
Thusto continue the network span the routing protocol is needed to increment theintensity of the node. Multiple routing protocols stay paths to flood thepackets i.e., route appeal is managed by the point of supply to achieve realityin concerning the ways. MANETs will be classified into three generations:first, second and third generations. In 1970’s the ad hoc network firstgeneration are called Packet Radio Network (PRNET). In early 1980’s SurvivableAdaptive Radio Network (SURAN)is evolved from PRNET.
The function pack ofMANETs 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 tomaintain the MANETs. For several years from 1970’s to 1990’s there are changesin the generations of MANET i.e., finally some standards are made to maintainthe MANET.
Energy efficiency is to be regarded as a factor in MANET. Mainly thepackets are transmitted based on the: · Distanceof the route· ResidualEnergy of the node.Thus the routethat is efficient and likely in transmitting packets can be identified. Routeappeal is controlled by the source to discover the route that is suited. Allthe ways that are made can be find .
The facts about the nodesenergy aligned and the connections are directed to accomplish the Route Reply.At any time the channel breaks, the Route Error is transmitted.When this occursthe source transmit the package over the path to the destination without anyinterruption. This can be done with the multipath routing protocol which are referredto the one path routing protocol. In one path routing once the link splits thepackets cannot be transmitted. Whereas in multiple routing additional routescan be refered to send the data packets. Particle Swarm Optimization (PSO) isthe algorithm from which the fitness function is derivative.
Fitness Functionis mostly used to find 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-AOMDVperformance in maximizing the network lifetime is possible in comparison withthe AOMDV. 1.1 Existing system: The research proposed highlightsthe problem of energy consumption in MANET by applying the Fitness Functiontechnique to optimize the energy consumption in Ad Hoc on Demand MultipathDistance Vector (AOMDV) routing protocol.
The proposed protocol is called AdHoc on Demand Multipath Distance Vector with the Fitness Function(FF-AOMDV).The fitness function is used to find the optimal path from the sourceto 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 popularsingle-path routing protocol. AOMDV offers two key services: route discoveryand route maintenance. Compared with AODV, AOMDV’s additional overhead is extraRERRs 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 key distribution 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:The sensor device comprises of processingunits, sensing unit, memory unit and transceiver unit. So, energyconsumption of each unit needs to beconsidered. E Sensor Device= E processor + E sensor + Ememory+Etransceiver (1) Where E Sensor Device is the total energy consumed by asensor 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 etal 3 Two important aspects of Mobile Ad Hoc Networks (MANETs) are Energyconsumption and security. Using trust management, key management, ?rewalls andintrusion detection security is provided in MANET.
It is essential to considerthe energy and security aspects in routing algorithms since energy and securityare 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 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 of packetsdropped 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 = -Second trustscore for node I, TSi = Overall trust score for node i. For developing a cluster based network aclustering scheme is developed with clusters. A Cluster based Energy Ef?cientSecure Routing Algorithm (CEESRA) is proposed for providing effective routing.Malicious nodes can be avoided and detected using the trust score.
A dynamic clusteringtechnique not only uses low mobility nodes, energy consumption, trust valuesand distance parameters for providing the energy ef?cient secure routingalgorithm. The proposed algorithm provides better performance in terms ofpacket drop ratio, residual energy, security and throughput when compared tothe existing techniques. N.
Magadevi et al 4 The wirelessnodes have limited power resource in Wireless Sensor Networks. To recharge thebatteries of the wireless nodes Wireless charging is an alternative. Using asingle mobile 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-KuangKuo et al 5 The energyconsumption of battery-powered mobile devices can be increased by measured inbits per Joule for MANETs. By jointly considering routing multimediaapplications the energy ef?ciency (EE) is an essential aspect of mobile ad hocnetworks (MANETs).
Based on the cross-layer design paradigm EE optimization is,traf?c scheduling, and power control a non convex mixed integer nonlinearprogramming is modeled as a problem. Branch and bound (BB) algorithm is devisedto ef?ciently solve this optimal problem. EE OPTIMIZATION 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 THE EEOPTIMIZATION 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 adjusted ingiven interval 0, pmax.constraint ( (6) Note that being allowed totransmit does not necessarily mean a transmission actually occurs, which isdecided by the optimization algorithm. With recent advances in information andcommunication technology (ICT), MANETs become a promising and growingtechnique. 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, transmissionschedule, and power control to the network, link, and PHY layers across-layer optimizationframework is proposed to enhance EE.
Thetransmission power of every active node in each time slot is specified by thepower control problem. To globally optimize ,a novel BB algorithm is developed.In terms of computational complexity proposed algorithm outperformed thereference algorithm. By exploiting the cross-layer design principle a solutionto determine the optimal EE of the MANET is provided.
Distributed algorithms andprotocols are designed to find the optimal EE. Any technique which can optimizenon convex MINLP problem in a distributed manner is not proposed. Thusdistributed algorithms and protocols are developed using approximationalgorithms. The guarantee for acquiring the optimal solution is thedisadvantage 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 new multipath routing protocolcalled the FF-AOMDV routing protocol, which is a combination of FitnessFunction and the AOMDV’s protocol. When a RREQ is broadcast and received, thesource node will have three types of information in order to find the shortestand 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 theroute 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:Optimumroute 1 = ?(n)rene(v(n)) / ? v Vene(v) (7) In this equation, vrepresents the vertices (nodes) in the optimum route rand V represent all the vertices in thenetwork. It compares the energy level among all the routesand 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. The pseudo-code for the fitnessfunction is provided and Simulations are conducted to run the FF-AOMDVprotocol. In this simulation, an OTcl script has been written to define thenetwork parameters and topology, such as traffic source, number of nodes, queuesize, node speed, routing protocols used and many other parameters. Two filesare produced when running the simulation: trace file for processing and anetwork animator (NAM) to visualize the simulation.
NAM is a graphicalsimulation display tool. It shows the route selection of FF-AOMDV based onspecific parameters. The optimum route refers to the route that has the highestenergy level and the less distance. Priority is given to the energy level, asseen on the route with the discontinuous arrow. In another scenario, if theroute has the highest energy level, but does not have the shortest distance, itcan also be chosen but with less priority. In some other scenarios, if theintermediate nodes located between the source and destination with lesserenergy levels compared to other nodes in the network, the fitness function willchoose the route based on the shortest distance available. . Energy, distancesare the fitness values used in the previous work to find the optimal path inmultipath routing.
Fig. 2 Optimum route selection inFF-AOMDV same proposed FF-AOMDV protocolis used along with the bandwidth as a fitness value. Now the calculations forselecting routes towards the destination will be according to energy, distanceand 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 theresults. Thus 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, energy consumption and then compare with the results ofexisting 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 distance increases energyconsumption also increases and when the route distance is less energy consumedwill be low.2. when bandwidth is high energyconsumption is also high and when it is less energy consumed will be low. Thusbandwidth is the parameter considered here and the simulation has scenarios likenode speed, packet size and simulation time.simulations are done by keeping thescenarios as: varying the packetsize(64,128,256,512,1024) and keep both thenode 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 proposedsystem as the bandwidth is the other parameter the mathematical model is to befind based on the three parameters energy, distance and bandwidth. 5. CONCLUSION:Energy ef?ciency (EE) is anessential aspect of mobile ad hoc networks (MANETs).secured routing protocol isproposed which is energy efficient and security is provided for both link andmessage without relying on the third party. A secure communication among theparticipating nodes is offered by the environment of MANETS.
Energy consumptionplays an important role in network lifetime. Since network mobility is animportant factor and network’s energy is consumed in data communication,Cross-Layer design approach is used to enhance the transmission power for powercontrol. Energy consumption can be reduced by the prevention of securityattacks on routing protocols.
Here to find the optimal path in multipathrouting, distance and energy are the fitness values used. It is proposed to usethe network resource bandwidth and calculations in selecting the routes towardsthe destination will be according to the distance, energy and also bandwidth.Thus the proposed work minimizes energy consumption and maximizes networklifetime. REFERENCES:1.
TejpreetSingh,JaswinderSingh,and SandeepSharma,”Energy ef?cient secured routing protocolfor 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.Ganapathy andM.Vijayalakshmi, “An Intelligent Securedand Energy Ef?cient Routing Algorithm for MANETs,” in Wireless personalcommunications ,Springer,pp 1753-1769,September 2017.4.N.Magadevi,V.JawaharSenthilKumarand A.Suresh, “Maximizing the Network Life Time of Wireless Sensor NetworksUsing a Mobile Charger,” in Wireless personal communications .,Springer ,pp1-11,2017.5.Wen-KuangKuo and Shu-Hsien Chu,”Energy Efficiency Optimization for Mobile Hoc Networks,” IEEE Access, pp928-940,March 2016