Implementing Energy Efficient Strategies in the MANET on-demand routing Protocols and comparing thei

Int. Journal of Electrical & Electronics Engg. Vol. 2, Spl. Issue 1 (2015) e-ISSN: 1694-2310 | p-ISSN: 1694-2426

111 NITTTR, Chandigarh EDIT-2015

Implementing Energy Efficient Strategies inthe MANET on-demand routing Protocols

and comparing their performances1P.Sivasankar, 2G.A.Rathy

1,2Assistant Professor,1Electronics Department, 2Electrical Department NITTTR, Chennai, India.

1 [email protected]

ABSTRACT:-Mobile Ad-hoc networks are self-configuringmulti-hop wireless networks where, the structure of thenetwork changes dynamically. Because of the nodes in theMANET are mobile and battery operated, energyoptimization is one of the major constraints in the MANET.Failure of some nodes operation can greatly impede theperformance of the network and even affect the basicavailability of the network, i.e., routing. To improve thelifetime of these networks can be improving the energy levelsof the individual nodes of the network. This paper presents ananalysis of the effects of different design choices for this on-demand routing protocols DSR and AODV in wireless ad hocnetworks. In this paper, the energy efficient strategies areimplemented in the AODV and DSR protocols to improve thelife time of the Mobile ad hoc network. The CBEER-NN isdeveloped using the existing DSR protocol and the AO-EEDTR is developed using the existing AODV protocol.GloMoSIM simulator is used to simulate the proposedMANET environment. This paper also compares theexisting DSR and AODV protocols with proposed CBEER-NN and AO-EEDTR protocols. From the simulated results,this paper concludes that the proposed CBEER-NN and AO-EEDTR protocols are improving the life time of the networkby improving the average residual energy of the nodes overthe existing DSR and AO-EEDTR protocols.

Keywords: AODV, DSR, AO-EEDTR, CBEER-NN, Cache

INTRODUCTIONMobile ad hoc networks [1] (MANETs) are instantlydeployable without any wired base station or fixedinfrastructure. A node communicates directly with thenodes within radio range and indirectly with all othersusing a dynamically determined multi-hop route.A critical issue for MANETs is that the activity of nodes isenergy-constrained. In the past few years, extensiveresearch has been carried out in developing routingprotocols for MANETs. Past research for reducingenergy consumption has focused on the hardware andthe operating system level. However, significant energysavings can be obtained at the routing level by designingminimum energy routing protocols that take intoconsideration the energy costs of a route when choosingthe appropriate route.This paper is worked on the network layer/routing layer &Radio layer and focuses on design andimplementation of Cluster Based Energy EfficientRouting using Neural Networks(CBEER-NN) in theexisting DSR protocol and AODV based EnergyEfficient Delay Time Routing(AO-EEDTR) in theexisting AODV protocol. These algorithms are designedand implemented using Global Mobile Simulator

(GloMoSim). Also the performance of the protocol isevaluated and compared with the existing DSR and AODVprotocols.

DSR AND AODV PROTOCOLSIn this section, the existing on-demand routing protocolsDSR and AODV protocols and their route discovery, routemaintenance procedures will be discussed.DSR ProtocolDSR [2] is an on demand, source routing protocol, witheach packet carrying in its header the complete, ordered listof nodes through which the packet will be routed. DSRconsists of two mechanisms: route discovery androute maintenance. When a node s has a packet to send forwhich it does not have a route, it initiates routediscovery by broadcasting a route request (RREQ). Therequest is propagated in a controlled manner through thenetwork until it reaches either the destination node T orsome intermediate node, n, that knows of a route to nodeT. Node T then sends a route reply (RREP) to node s withthe new route. In this case that multiple routes are located(i.e., multiple route replies are received), nodes s selectsthe one with the best metric (e.g., hop count).Route Maintenance is the mechanism by which a nodedetects whether or not a route kept in its cache has becomestale as result of host mobility and topology change. Whenan (intermediate) node n detects that the next link in apackets route is broken, it first sends a route error (RERR)message to the source node s that generated the packetsroute.AODV ProtocolAd hoc on-demand distance vector in [2] (AODV)routing protocol uses an on-demand approach for findingroutes, that is, a route is established only when it isrequired by a source node for transmitting data packets. Itemploys destination sequence numbers to identify the mostrecent path. The major difference between AODV andDSR stems out from the fact that DSR uses source routingin which a packet carries the complete path to be traversed.However, in AODV, the source node and the intermediatenodes store the next-hop information corresponding toeach flow for data packet transmission. In an on-demandrouting protocol, the source node floods the Route requestpacket in the network when a route is not available for thedesired destination. It may obtain multiple routes todifferent destinations from a single Route request. Themajor difference between AODV and other on-demandrouting protocols is that it uses a destination sequencenumber to determine an up-to-date path to thedestination. A node updates its path information only if the


NITTTR, Chandigarh EDIT -2015 112

destination sequence number of the current packet receivedis greater than the last destination sequence number storedat the node. When an intermediate note receives a Routerequest, it either forwards it or prepares a Route reply if ithas valid route to the destination. The validity of a route atthe intermediate node is determined by comparingthe sequence number at the intermediate node with thedestination sequence number in the route request packet.

CBEER-NN AND AO-EEDTR

In this section, the proposed modified energy efficientrouting algorithms [3,5] for MANET using DSR andAODV protocols will be discussed. The Cluster BasedEnergy Efficient Routing using Neural Networks(CBEER-NN) algorithm is implemented in existing DSR protocoland the AODV based Energy Efficient Delay TimeRouting(AO-EEDTR) Algorithm is implemented inexisting AODV protocol.CBEER-NNThis algorithm is implemented in DSR protocol to findenergy efficient route between the source and thedestination nodes. In this algorithm, selection of routesshould be based on the remaining battery energy level ofthe node. This CBEER-NN algorithm selects the routebased on the Energy metrics of a node participating in themobile network to route and deliver the packet to thedestination. The CBEER-NN protocol is designed to bringabout energy aware route establishment in order to avoidthe full drain of the energy from a node, which in thenetwork forms a gateway to the other zones [7]. Theproposed algorithm differs from the existing DSRprotocol in the route discovery and energy aware routemaintenance with higher percentage of reliable delivery ofpackets. The energy efficient route establishment in theCBEER-NN algorithm is described in the followingsection.. Energy Efficient Route EstablishmentThe network is formed by the “divide and rule” policy forthe nodes to deliver the packets to the destination. Thetree structure with virtual backbone is used to deliver thepackets reliably to the destination and optimized use ofenergy in the network. A node on entry to the network getsitself associated to one of the root if its energy level [8] islesser than the root node else it will act as a root and thenode which was a root becomes a leaf node. A virtualbackbone is formed with the nodes having the highestenergy in the domain to establish routes from one node atone end to other end.The Route discovery and maintenance phases of CBEER-NN protocol is discuss in the following sections.3.1.2. Route Discovery PhaseThe DSR protocol broadcasts a route discovery packet andthe reply is formulated by the node, which has entry of thedestination node in its cache or the destination replieswith a route reply packet. The proposed algorithmmakes sure that the route discovery packet is forwarded toits root and if the root has the cache entry for the packet itwill reply back with the route reply or else it will in turnforward the packet to its root. Finally if the route is non-existent till the root node, which participates in thebackbone formation, then the route discovery packet issent through the backbone to the other domain nodes,which may reply back with a route reply. Thus on

establishing a route, the route reply containing the routeback to the source is routed back. Thus if the destinationnode is not existent in the domain then after a time out andresend attempts, the source node could find that thedestination node is unreachable.3.1.3. Route Maintenance PhaseThe CBEER-NN algorithm differs considerably from DSRin Route Maintenance. The route maintenance is easier asthe hello packet which contains the cache contains of thenode can be interchanged between the leaf node and rootnodes. This will ensure that the route is existent and theroute reply can be generated from the reference of thecache. The energy based tree formation ensures theparticipation of nodes in the network though their powerremaining is less, by reception of packets intended to themand transmission of packets (acting as a source) but not asa router. A field namely the ROOT_NODE orLEAF_NODE need to be interchanged between the rootand the leaf nodes (within the range of the root node) withthe sequence number for tracking of the route and identifyto which root the node belongs to.3.1.4. Energy Efficient Cluster Head Selection usingNeural NetworksA five layered feed forward neural network is used topredict the final energy level of the individual nodes in thecluster. The input patterns belong to one wireless node andby using them as the inputs of the neural network canpredict the energy level of the mobile node at the last ofnetwork lifetime. These patterns may be in the form offeatures coded from node’s distance from sink, node’sdistance from the neighboring border, node’s number ofneighbors, the number of neighbors which initially routetheir data through this node. After deploying nodes, thebase station receives nodes positions and neighbor’sinformation, thus it can easily calculate these patterns foreach node and the neural network can be able to predicttheir final energy level. A well-trained neural networkwould be able to receive each node’s features as the inputsand predict its final energy level. Thus, the neural networkis used to increase the life time of the network.Selecting Group Heads amongst all the nodes is also

energy conserving scheme. Each node collects data whichare typically associated with other nodes in itsneighborhood, and then the associated data is sent to theBase Station through Group Head for evaluating the tasksmore efficiently. Assuming the periodic sensing of sameperiod for all the nodes and Group Head is selected.Inside each fixed group of nodes, a node is periodicallyelected to act as Group Head through whichcommunication to/from Group nodes takes place. The setof Group Head nodes can be selected on the basis of therouting cost metric explored by the equation:

RCM = Ek/Ar{ ET(NkS,Nm

D)+ER (NkS,Nm

D)}------ 1

Where,Ek be the energy associated with the delivery ratio of thepacket, delivered correctly from source node NS to thedestination node ND

ET(NkS,Nm

D) energy transmitted from NS andER (Nk

S,NmD) is the energy received at ND,

Ar be the range area of the network.AO-EEDTR



The basic idea behind this AODV based Energy efficientdelay time routing (AO-EEDTR) algorithm is to utilize alonger and more energy efficient routing [6] path instead ofusing a lesser energy efficient and shorter path. The Energyefficient delay time routing algorithm is based on theAODV protocol. The Route Discovery in the AODVprotocol is modified so as to enable the selection of themost energy efficient routes [9] by the source nodes. TheRoute Maintenance is essentially the same as in AODV.3.2.1. Route Discovery PhaseGenerally in on-demand routing algorithm, when a sourceneeds to know the route to a destination, it broadcasts aRREQ packet. The neighboring nodes on receiving thefirst-arrived RREQ packet relay this packet immediately totheir neighbors. But in our algorithm, this packet relayingdoes not occur immediately. The idea of EEDTR algorithmis as follows: Upon receiving a request packet, eachnode first holds the packet for a period of time, which isinversely proportional to its current energy level. Afterthis delay, the node forwards the request packet. Thissimple delay mechanism is motivated by the fact that thedestination accepts only the first request packet anddiscards other duplicate requests. With this delaymechanism, request packets from nodes with lower energylevels are transmitted after a larger delay, whereas therequest packets from nodes with higher energy levels aretransmitted after a smaller delay.Some nodes may receive several copies of the same

RREQ packet from other neighbors. In AO-EEDTR, theduplicate copies of the same RREQ packets would bedropped as in the original AODV protocol. Fig.1. Ilustrates AO-EEDTR algorithm. In the figure, it isassumed that the initial maximum battery capacity of allnodes is 10. The remaining energy levels after a finiteamount of time are shown in Figure alongside the nodes.Due to transmission range limitations, nodes A and B cantransmit the packet only to nodes C and D,respectively. The residual battery capacities of A and Bnodes are same, so they flood the RREQ packets at thesame time. We may ignore the travel time between nodes,without loss of generality. Since node D has more residualbattery capacity than node C, other neighbors that cancommunicate with both nodes C and D first receive theRREQ packet from node D (because of the inverse delay).The process repeats until the RREQ packet arrives at thedestination. In this figure, the destination node receivesthe following routes: (S-B-C-E-T), (S-A-D-F-T)and (S-A-D-G-T). Normally the route with the least hop isselected. But with AO-EEDTR, the route forcommunication from node S to node T is chosen as (S-A-D-F-T), since nodes with lesser energy level delay thepacket more than others. Thus a energy efficient path ischosen. Note that implementation of the algorithmrequires minimal modification at local nodes by adding adelay mechanism. However, the penalty of thisprotocol is introduction of delay in route discoveryprocedure. Various delay functions which map energyvalue into delay, will be evaluated in the simulation sectionthat follows.

The selected route (S-A-D-F-T) may not alwaysguarantee the total minimum energy, partially because itdoes not consider the number of hops in the route.Nevertheless, simulation results showed that AO-EEDTRprolongs the network lifetime significantly.

Fig. 1. AO-EEDTR algorithm

In the algorithm the delay incorporated by each of thenodes is inversely proportional to the remaining energylevel of each of the corresponding nodes. Following linearfunction incorporates the inverse proportionalityDelay di = TM – (TM * er) /EM------------2Where,di Delay to be introducedTMMaximum delay possibleer Remaining energy of a nodeEMMaximal energy possible for a node

RESULT AND ANALYSISSimulation tool : GLOMOSIM

GloMoSim in [4] (Global Mobile Information SystemSimulator) is a scalable simulation environment thateffectively utilizes parallel execution to reduce thesimulation time of detailed high-fidelity models of largecommunication networks. GloMoSim is a scalablesimulation library for wireless network systems built usingthe PARSEC simulation environment. Glomosim can bemodified to add new protocols and applications to thelibrary. Therefore Glomosim is a good choice forimplementing the different traffic sources. GloMoSim isaimed at simulating models that may contain as many as100,000 mobile nodes with a reasonable execution time;this is done by using node aggregation.

Performance MetricsThe various parameters that were measured during thesimulation are as follows:Packet Delivery Ratio: It is defined as the ratio of numberof packets received to that of the number of packets sent.Routing overhead: It is defined as the sum of number ofroute requests, route replies & route errors.End to End Delay: It is the overall average delayexperienced by a packet from the source to that of thedestination.Average Residual Energy: It is taken as the average ofthe remaining energy levels of all the nodes in the network.These metrics were measured by varying thefollowing three parameters

1. Number of Nodes2. Speed(m/sec)

3. Number of Source Destination PairsSimulation Results and ComparisionFig. 2 shows that the proposed CBEER-NN and AO-EEDTR algorithms are performing well compared to theexisting DSR and AODV protocols for maintaining theaverage residual energy in each of their nodes even if theNumber of nodes pairs increased. Similarly the averageresidual energy in each of their nodes are improved inthe proposed AO-EEDTR and CBEER-NN over the


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existing AODV and DSR protocols, though the nodesmobility or speed increased. This is shown in Fig. 3 bycomparing the average residual energy for varying thenodes mobility.

Fig. 2.a.

Fig. 2.b.Fig. 2. No. of Nodes Vs Avg. Residual Energy

Fig. 3.a.

Fig. 3.b.Fig.3. Speed Vs Avg. Residual Energy

Fig. 4 shows the improved Packet delivery ratio for theproposed CBEER-NN and AO-EEDTR algorithms overthe existing protocols for varying the different Number ofSource Destination Pairs.

Fig. 4.a.

Fig. 4.b.Fig. 4. No. of Source Destination Pair Vs Packet Delivery Ratio

Fig. 5 shows that the proposed algorithms produces moreEnd to End delay over the existing protocols because notfollowing the shortest hop path. Fig. 6. shows the ControlOverhead with Number of Nodes. It indicates that theOverhead increases as the Number of Nodes increases,due to increase in number of route requests and number ofroute replies flooded in the network. Also it is concludedthat the CBEER-NN and AO-EEDTR algorithmsare working well when compared to existing DSR andAODV protocols.

Fig. 5. No. of Nodes Vs End to End Delay

Fig. 6. No. of Nodes Vs Control OverheadCONCLUSION

The DSR and AODV protocols have been implementedand compared with the modified energy aware CBEER-NN and AO-EEDTR protocol and it is observed to have

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improved performances of the ad-hoc network. It is foundthat the modified algorithms have the comparableperformance with respect to Average Residual Energy,Packet Delivery Ratio and Overhead with the existing DSRand AODV protocols. It has also been observed that byimplementing a proper standardized energy model in theexisting DSR and AODV protocols, our CBEER-NN andAO-EEDTR protocols are feasible and capable of betterenergy performance than the preset DSR and AODVprotocols.

REFERENCES1. Journal Papers[1] Marco Conti and Silvia Giordano “ Multihop Ad Hoc Networking:The Theory”, IEEE communication Magazine, 2007.[2] X.Hong,K.Xu and Gerla, “Scalabe Routing Protocols for MANET ”,IEEE network vol 16, pp 11-21, 2002.[3] Shio Kumar Singh, D K Singh and M P Singh,. “A Survey of Energy-Efficient Hierarchical Cluster-Based Routing in Wireless SensorNetworks, Int. J. of Advanced Networking and Applications”, Volume:02, Issue: 02, Pages: 570-580, 2010.[4] Rajiv Bagrodia, Xiang zeng and Mario Gerla, “Glomosim: A libraryfor simulation of wireless networks”, University of califrnia ,Los Angels.

2. Conference Proceedings[5] C. Jinshong Hwang, Ashwani Kush, Sunil Taneja,. “Making MANETEnergy Efficient, IEEE”, 2011[6] Eei Yu and jangwon Lee, “DSR based Energy aware RoutingProtocols in Ad Hoc networks”, IEEE,2003[7] H.safa,Mirza.O, and Artail.H, “A Dynamic Energy EfficientClustering Algorithm for MANET.IEEE International Conference onWireless and Mobile Computing, 2008[8] Young-sam Kim, Kyung-min Doo, and Kang-whan Lee,. “A Study onthe Synchronization Clustering Control for MANET, ICCIT, IEEE. 2008.[9] Avni Khatkar, Yudhvir Singh, and Rohtak, “Performance Evaluationof Hybrid Routing Protocols in Mobile Adhoc Networks”, 2012 SecondInternational Conference on Advanced Computing & CommunicationTechnologies. 2012[10] Imane M. A. Fahrnv, Hesham A. Hefny and Laila Nassef,. PEEBR:“Predictive Energy Efficient Bee Routing Algorithm for Ad-hoc WirelessMobile Networks, The 8th International Conference on INFOrmatics andSystems (INFOS2012) , Computer Networks Track”, 2012

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Implementing Energy Efficient Strategies in the MANET on-demand routing Protocols and comparing thei