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  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012Dynamically Adjusting Network Topology for MANETS By using DBET T.Damodar Yadav K.M.Hemambaran Department Of E.C.E Department Of E.C.E MTech, SITAMS, Assistant Professor, SITAMS, Chittoor, Andhra Pradesh. Chittoor, Andhra Pradesh. Email: damodar419@gmail.com Email: hemambaran@rediffmail.comAbstract- In MANETS, network topology vary mainly into two categories: by controlling theaccording to nodes, nodes are usually powered by number of nodes with the smaller link cost. In thebatteries. To prolong the network life, the energy first method a small number of nodes awake toconsumption of the routing task is crucial. In previous maintain the network connectivity and remainingworks, enormous topology control methods were nodes go into sleep state to conserve energy. Thisgiven to support the energy-efficient routing, whilethe most of them are designed for static network. We method is effective in low traffic conditions,proposed an Energy efficient topology in Ad-hoc because the power consumption to keep nodesnetworks can be achieved mainly in two different .In awake dominates the power consumption in datathe first method, network maintains a small number transfer. In the second method, topology isof nodes to form a connected backbone and the controlled by keeping lesser cost links in theremaining nodes sleep to conserve energy. The second network. This method is effective in high datamethod is achieved by power control technique. So, traffic because power consumption in data transferwe propose a Demand Based Energy efficient dominates the power required to keep nodes awake.Topology (DBET) to reduce the energy consumption We combine the advantages of these twofor mobile ad hoc network, by dynamically adjustingthe topology for various network traffic conditions. techniques to dynamically adjust network topologyWe have simulated our proposed protocol DBET by for various network traffic conditions. In this paper,using AODV as routing protocol in network simulator we present a demand based energy efficientns2.34 and compared AOMDV The simulation studies topology (DBET) that dynamically adjust networkrevealed that the proposed scheme perform better in topology for various network traffic conditions. Weterms of energy, delay, and delivery ratio. have simulated our proposed protocol DBET by using AODV [8] as routing protocol using networkIndex Term--Energy efficient topology, Routing, simulator ns2.34 [1] and compared with AOMDVMANET. The simulation studies revealed that the proposed scheme perform better in terms of energy, I. INTRODUCTION delay, and delivery ratio. In general network topology is controlled by keeping small number of Mobile Ad-hoc Networks(MANETS) are nodes awake as in the first technique. The proposedself-organizing, infrastructure-less multi-hop DBET keeps more number of nodes along the bulkwireless net-works, Such temporary networks can data transfer path to conserve energy by keepingbe used in battle-fields, disaster areas, military low link cost as in the second technique. The rest ofapplications, mining operations and robot data the paper is organized as follows: the next sectionacquisition. Besides these characteristics they provides a brief review of related studies. The thirdpresent challenges like limited energy, dynamic section gives the design details of proposed DBET.topology, low bandwidth and security. The Integration issues of DBET with routing protocol isdescription of the arrangement of the MANETs, discussed in the forth section. Simulation resultscalled topology, is usually temporary or along with discussions are provided in the sectiondynamically changed with time. Energy conserving 5. The last and final section concludes the paperis one of the challenges because of limited battery with same pointers to future research direction.resource. The techniques which are used to reducethe initial topology of network to save the energy AODV Routing Protocoland increase the lifetime of network, with thepreservence of network connectivity, called The Ad-hoc On-Demand Distance Vectortopology control techniques. Various techniques, (AODV) routing protocol is designed for use in ad-in network layer, are proposed in the literature to hoc mobile networks. AODV is a reactive protocolconserve energy. These techniques can be classfied the routes are created only when they are needed. It 95 All Rights Reserved © 2012 IJARCET
  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012uses traditional routing tables, one entry per made symmetric by removing asymmetric linksdestination, and sequence numbers to determine without impairing connectivity.whether routing information is up-to-date and toprevent routing loops. An important feature of A simple localized distributed topologicalAODV is the maintenance of time-based states in control algorithm (XTC) is proposed byeach node: a routing entry not recently used is Wattenhpfer et al. Initially each node u computes aexpired. In case of a route is broken the neighbours total order (<u) over all its neighbors in thecan be notified. Route discovery is based on query network graph G with respect to decreasing linkand reply cycles, and route information is stored in quality, such as signal attenuation, and packetall intermediate nodes along the route in the form arrival rate. Then, each node start exchanges theof route table entries. neighbor order information among all neighbors.AOMDV Routing Protocol At the later point, each node locally selects those neighboring nodes which will form its Ad-hoc On-demand Multipath Distance neighborhood in the resulting topology controlVector Routing (AOMDV) protocol is an extension graph, based on the previously exchanged neighborto the AODV protocol for computing multiple order informations. It covers three mainloop-free and link disjoint paths. The routing advantages: 1) It does not assume the networkentries for each destination contain a list of the graph to be a Unit Disk Graph,2) it works onnext-hops along with the corresponding hop counts. weighted network graphs, and 3) it does not requireAll the next hops have the same sequence number. availability of the node position information.This helps in keeping track of a route. For each Authors improved by adding node mobility anddestination, a node maintains the advertised hop extended XTC for mobile network [7]. An energycount, which is defined as the maximum hop count efficient dynamic path is maintained to send datafor all the paths, which is used for sending route from source to destination for MANET is proposedadvertisements of the destination. Each duplicate in Sheu, Tu, and Hsu. Due to mobility existingroute advertisement received by a node defines an paths may not be energy efficient. So, each node inalternate path to the destination. Loop freedom is a data path dynamically updates the path byassured for a node by accepting alternate paths to adjusting its transmission power. Each node in thedestination if it has a less hop count than the networks determines its power for dataadvertised hop count for that destination. Because transmission and control packets transmissionthe maximum hop count is used, the advertised hop according to the received beacon messages from itscount therefore does not change for the same neighbors. In dynamic path optimization techniquesequence number. When a route advertisement is protocols dynamically select energy efficient pathreceived for a destination with a greater sequence as per the requirement of dynamic topologicalnumber, the next-hop list and the advertised hop changes in the network [4].count are reinitialized. Another class of topology control protocols based on the k-nearest neighbors graph II RELATED WORK (k-NNG). In k-NNG every node is connected to its We briefly describe various techniques k closest neighbors. The Local Information Norelated to our work topology control. Different Topology protocols (LINT) try to keep the numbertopologies have been proposed in the literature to of neighbors of a node within a low and highreduce the energy consumption. These methods can threshold centered around an optimal value. But thebe clas-sified into centralized controlling and optimal value is not characterized. So thedistributed computing methods. Ideally, for mobile estimation of the number of neighbors can bead hoc network a topology should be computed and inaccurate and connectivity is not guaranteed. Themaintained in distributed, asynchronous, and k-Neighbors (k-NEIGH) [2] protocol keeps thelocalized manner. Li and Wan [6] described a number of neighbors of a node equal to, or slightlydistributed protocol to construct a minimum power below, a given value k. It connects each node withtopology and developed an algorithm which k-closest neighbor, instant of require thedirectly find a path whose length is within a knowledge of all the neighbors. Theconstant factor of the shortest path. The length of communication graph that result is made symmetricthe path is measured in term of energy by removing asymmetric edges, which has k-upperconsumption. This proposed algorithm used only bound neighbors. A characterization of the criticallocal information. A topology based on minimum neighbor numbers is discussed by Xue and Kumarspanning tree, called localized minimum spanning Another way of reducing the power consumption istree (LMST) was proposed by Li et al. [5]. It is a by using efficient energy path for transmittinglocalized distributed protocol with the following packets. These methods choose smaller edges inproperties: (1) the protocol generates a strongly their path to reduce transmission energy. Minimumconnected communication graph; (2) the degree of energy consumption per packet can be achieved byany node is at most six, and (3) the topology can be choosing the optimal energy consumed path from source to destination. However, this technique does 96 All Rights Reserved © 2012 IJARCET
  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012not take the nodes’ energy capacity into c i +f i As the values of 𝑐 𝑖 and fi increase, the stabilityconsideration. So some nodes may exhaust their nipower since energy consumption is not fair among of the node decreases.the nodes in the network. There for the network • Utility factor (denoted by U): Nodes that havelift- time decrease. higher number of neighbors without an active neighbor are given more preference. This heuristic is derived from the fact that such nodes, if elected, can help a larger number of other nodes, which can III DEMANED BASED ENERGY then be put to sleep state. Thus, the utility factor Ui EFFICIENT TOPOLOGY n i −n a i of a node i is calculate as . ni In this section, we present a demand basedenergy efficient topology (DBET) for mobile ad • Energy factor (denoted by E): Nodes that havehoc network, which dynamically changes the higher amounts of percentage remaining power aretopology according to the network traffic given more preference over others to be elected asrequirements. Initially we compute a small set of active nodes. This introduces fairness in thenodes, which form a connected backbone, while the protocol by ensuring proper Let 𝐸0 𝑖 denote theother nodes are put off to conserve energy. This initial node’s energy and 𝐸 𝑡 𝑖 be the amount ofconnected backbone is used for routing the packets energy of a node at time t. So the energy factor 𝐸 𝑖under low network load. When there is a bulk data 𝐸0 𝑖 +𝐸 𝑡 𝑖 of the node i is calculate as Thus, the abovetransfer between a pair of nodes, the topology 𝐸0 𝑖dynamically changes along the path between these discussion suggests that the coordinator selectionnodes by power control and route optimize factor for phase − I can be the sum of all thesetechnique to minimize the power consumption. The factorsproposed DBET can be divided into four phases. 𝑐 𝑖 +𝑓 𝑖 𝑛 𝑖 −𝑛 𝑎 𝑖 𝐸0 𝑖 −𝐸 𝑡 𝑖The first phase selects a small set of nodes that 𝐶𝑖 = 𝑆 𝑖 + 𝑈𝑖 + 𝐸𝑖 = + + (1)constitutes an independent set of the network. The 𝑛𝑖 𝑛𝑖 𝐸0 𝑖second phase is responsible for electing more nodesto ensure that the selected nodes form a connected Only nodes that do not have an activebackbone. Remaining nodes go to sleep to conserve node in their neighbor-hood are allowed toenergy. Active node withdraw process is participate in the election. Announcementimplement in the third phase to remove redundant contention occurs when multiple nodes discover thenodes in each region. To improve the performance lack of an active node, and all decide to becomealong the high traffic path we use the route active nodes. We resolve the contention byoptimization with power control technique in the delaying the announcement with randomized backfourth phase. In this technique, we change topology off delay, which is proportional to the extent todynamically to connect more nodes, around the which the node satisfies the heuristics. The selectedrouting path to minimize the total power nodes forms an independent set of a connectingconsumption. backbone of the network. Selected active nodes go back to sleep after they have used up a fixedA. Phase I: Independent set formation percentage of their power to ensure fairness and allow other nodes to become active. The first phase selects a minimal set ofnodes that constitute a minimal independent set of a B. Phase II: Connecting the Independent Setconnected backbone of the network. This selectionis done in a distributed and localized manner using Nodes selected in the first phase are notneighbor information available with the network connected. This is because there is only one activelayer. Let ni be the total number of nodes node in a given locality. In this phase more nodessurrounding a node i and let 𝑛 𝑎 𝑖 be the number of are elected to ensure that the selected nodes form a connected network. All nodes that have two oradditional nodes among these neighbors, which are more active nodes as neighbors, which are notconnected, if node i becomes a coordinator to the connected directly or through one or two activeforward packets. The following heuristic is used in nodes, are eligible to become active in this phase.this phase: Preference is given to the nodes satisfying the• Stability factor (denoted by S): Nodes that are following criteria:relatively more stable as compared to the others inthe localities are given more preference. The node’s  Nodes having higher amount of remainingstability is measured as the ratio of number of link energy.failures (fi ) and new connection established (ci ) per  Nodes having higher stability. This can beunit time to the total number of nodes surrounding measured similar to the one used in thethat node (ni ). Therefore, stability of a node i is first phase. 97 All Rights Reserved © 2012 IJARCET
  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012 𝑃𝑡  Nodes having more number of active The actual power 𝜉 𝑖,𝑗 = K +X, required 𝑃𝑟 nodes in the 1-hop neighborhood. for sending data from a node I to the node J at a The stability and energy factors of this phase distance d, where X represents the energyare very much similar with 1st phase. But the utility consumed by receiving node.factor is depends upon the 1st phase’s black activenodes. Let 𝑛 𝑏 𝑖 be the number of active nodes of the1st phase in 1 − hop neighborhood of a node i. Ifnodes with high 𝑛 𝑏 𝑖 become the coordinators in thisphase, fewer coordinators in total may be needed inorder to make sure every node can talk to acoordinator. Thus a node with a high 𝑛 𝑏 𝑖 shouldvolunteer more quickly than one with smaller Fig.1. Minimizing the transmission power.value. Thus, the coordinator selection factor for2 𝑛𝑑 phase is the sum of all these factors The minimum required energy for the data transmission can be calculated as follow: each node 𝑐 𝑖 +𝑓 𝑖 𝑛 𝑖 −𝑛 𝑏 𝐸0 𝑖 −𝐸 𝑡 𝑖𝐶 𝑖 =𝑆 𝑖 + 𝑈 𝑖 + 𝐸 𝑖 = + 𝑖 + (2) in the network has fixed default full transmission 𝑛𝑖 𝑛𝑖 𝐸0 𝑖 power 𝑃 𝑡 , when a node I receives control message from node J with power Pr it calculates the distanceThe contention if any is also resolved using the between nodes I and J then node I can findback off mechanism like in the first phase. minimum energy 𝑃 𝑡 (d) required for transmitting the data to node J. Let consider the nodes B and node CC. Phase III: Coordinator Withdraw which are in the transmission range of a node A as Every active node periodically checks if it shown in the Fig. 1. If 𝜉 𝐴,𝐵 + 𝜉 𝐵,𝐶 < 𝜉 𝐴,𝐶 thenshould go o sleep state or not. The need for a node sending data packet from node A to the node C viato be an active may also cease to exist due to the intermediate node B consume less energy. Ourdynamics of the system. More explicitly, this may proposed DBET uses this power optimizationhappen due to one of the following reasons technique locally along the routing path to minimize the energy consumption during the .• If first phase active nodes may move transmission. Whenever a new node satisfies theinto a region that already has another first phase above criteria it remains awake to participate in theactive node so that the region now has more than high traffic flow path. Please note that a new nodeone first phase active nodes. These active nodes can come either a sleeping node wakes up nearrecognize this situation and one of them withdraws. high traffic flow path or awake node moves closer to high traffic flow path.• If the withdrawal of a first phase active node maymean that the second phase active nodes in the IV. INTEGRATING DBET WITHlocality no longer serve their purpose and hence ROUTING PROTOCOLwithdraw. The proposed DBET can be integrated In the above scenarios the respective active nodes with any routing protocol. In this section, wewithdraw, as their need no longer exists. However, discuss the process of integration with AODV. Inwhen an active node withdraws by virtue of our approach all control packets and data packetscompletion of its quota of time it needs to be awake are transmit on low traffic path with fulluntil another node is elected in the locality. transmission power and data packets on high traffic path with minimum required energy.D. Phase IV: Local route customization withPower control technique Route discovery: Route discovery uses route cost in place of hop count as route metric. We use the The energy consumption per data packet notation 𝛿 𝐼,𝐽 denotes the cost of least cost path fromform source to destination is high when each node the node I to the node J. When a source node Suses full transmission power. This can be reduced wants to find a route to a destination D, itby chooses a lower energy cost path. The minimum broadcasts the route request packet (RREQ) to itstransmission power 𝑃 𝑡 (d) =a 𝑑 𝑘 +c is required to neighbors. The route request packet contains thesend data to a node at a distance d, where 2 <k< 4 least route cost from source node S, which isand for some constants a and c. The receiving initially zero. An intermediate node J receiving the ℎ 2ℎ 2 𝑘power 𝑃𝑟 =𝑃 𝑡 𝐺 𝑡 𝐺 𝑟 𝑡 4 𝑟 =𝑃 𝑡 4 by surface reflection route request packet from another intermediate 𝑑 𝑑 node I, it calculates the cost of the path form nodemodel, where ℎ 𝑡 , 𝐺 𝑡 , ℎ 𝑟 , and 𝐺 𝑟 are respectively S to nodes J as 𝛿 𝑆,𝐽 + 𝜉 𝐼,𝐽 . The node J update itsantenna height and gain of sending and receivingnodes [10]. routing table if the calculated cost is less than the cost in its routing table and forward the route 98 All Rights Reserved © 2012 IJARCET
  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012request packet to its neighbors with updated cost. End-to-end delay: The end-to-end delay is theIn order to avoid another cost update, node J waits average time between data packets sent out fromfor the time (propositional to the cost to 𝛿 𝑆,𝐽 ) the sources and received at the destination. The Figbefore forwarding. When a destination node D C shows the delay with respect to the time. DBETreceives first route request packet (RREQ), it by AOMDV performance is better than AODV.calculates the route cost and update its routing This is because the low transmission power impliestable. It waits for a fixed time interval to receive low queuing delay and reduced interference.more route request packets and find the least costroute among them. The node D unicast a route TABEL 1: Simulation Parametersreply packet (RREP) back to its neighbor fromwhich it received the least cost route. The neighbornodes unicast RREP towards the source node S. S.No Parameters Values 1 Simulation time 130 secLocal route customization: As we discussedearlier due to the dynamic nature of the network 2 Number of nodes 38new node may come closer to existing path, which 3 Max node energy 1000Jmay reduce the existing route cost, if it participatesin forwarding the data. 4 Energy 0-1000J Distribution 5 MAC IEEE802.11 6 Max Tx power 0.75W 7 Max Rx power 0.25W 8 Routing protocol AODV Fig. 2. Local path customization. 9 Propagation model Two ray ground 10 Node motion Random-motion Let consider the example network given inthe Fig. 2(a) with the existing path cost from the 11 Area 1000x1000𝑚2node I to the node J is 9 units. If a node is in datatransmission path, it sends the <Source address,Destination address, Route cost from source to Packet delivery ratio: Packet delivery ratio is theitself> as a piggyback with periodic hello messages ratio of the data packets received at the destinationin full transmission path. After receive the hello to the data packets sent out from the sources. Themessages from the node I and the node C, along Fig D shows the overall delivery ratio with respectwith piggyback information, node X calculate the to the time. As the time rate increases, the deliverylink cost 𝜉 𝐼.𝑋 and 𝜉 𝐶,𝑋 and checks whether it can ratio always decreases. AOMDV performs betterparticipate in the ongoing data transfer. The node X than AODV routing protocol.can participate in data forwarding, if it reduces thecost of the path from the node I to the node C. That VI. CONCLUSIONSis, if 𝜉 𝐼,𝑋 + 𝜉 𝐶,𝑋 < 𝛿 𝐼,𝐶 then the new node Xparticipate in the routing by sending route update In this paper, we proposed a demandcontrol message (RUP) to the node I and the node based energy efficient topology that dynamicallyC with route cost 𝛿 𝐼,𝐶 . When the node I and the adjusts its topology for various network trafficnode C receive (RUP) messages and then update conditions. We have simulated our proposedtheir routing tables. protocol DBET by AOMDV and compared with AODV routing protocol. The simulation studies V. PERFORMANCE EVALUATION revealed that the proposed scheme perform better in terms of energy, delay, and delivery ratio. It We have evaluated the performance of would be interesting to investigate the use ofDBET with AODV [8] as a routing protocol and directional antenna to further reduce the energycompared with AOMDV using the network consumption.simulator NS2.34. The simulation parameters arelisted in the table I.Energy consumption: The energy consumed byDBET by using AOMDV is less when comparewith AODV routing protocol. SIMULATION RESULTS 99 All Rights Reserved © 2012 IJARCET
  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012 Fig A: Omni antenna Fig C: delay (vs.) timeFig B: directional antenna Fig D: delivery ratio (vs.) time 100 All Rights Reserved © 2012 IJARCET
  • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012 REFERENCES T.Damodar Yadav, PG Student,[1] The network simulator - ns-2.33. Dept of ECE, SITAMS, Chittoor.http://www.isi.edu/nsnam/ns. He received B.Tech degree from[2] Douglas M. Blough, Mauro Leoncini, JNTU, Anantapur, doing hisGiovanni Resta, and Paolo Santi. The k- research work in MANETS to receive M.Tech degree fromneighbors approach to interference bounde JNTU, Anantapur, in communication systems. Hed and symmetric topology control in ad presented various papers in national conferenceshoc networks. IEEE Transactions onMobile Computing, 5(9):1267–1282, K.M.Hemambaran, Assistant2006. Professor, Dept of ECE, SITAMS, Chittoor. He had[3] Benjie Chen, Kyle Jamieson, Hari completed his MTech and AreaBalakrishnan, and Robert Morris. Span: of Interest in Digital andAn energy-efficient coordination algorithm Communication. He presented and published in various nationalfor topology maintenance in ad hoc and international conferences and journals, and hewireless networks. ACM Wireless is a life time member of IETE / ISTE.Networks, 8:85–96, September 2001.[4] H. P. Gupta and S. V. Rao. Pclr: Powercontrol-based locally customize routing formanet. In Proc. IEEE InternationalConference on RF and Signal ProcessingSystems, pages 632–637, 2010. [5] Charles E. Perkins and Elizabeth M.Royer. Ad-hoc on-demand distance vectorrouting. In WMCSA ’99: Proceedings ofthe Second IEEE Workshop on MobileComputer Systems and Applications,pages 90– 100, Washington, DC, USA,1999. IEEE Computer Society.[6] N. Li, J.C. Hou, and L. Sha. Designand analysis of an mst-based topologycontrol algorithm. In INFOCOM 2003.Twenty-Second Annual Joint Conferenceof the IEEE Computer andCommunications. IEEE Societies, pages1702 – 1712, mar. 2003. [6] Xiang-YangLi and Peng-Jun Wan. Constructingminimum energy mobile wirelessnetworks. SIGMOBILE Mob. Comput.Commun. Rev., 5(4):55–67, 2001.[7]A. Naghshegar, A. Dana, A.Darehshoorzadeh, and K. Karimpoor.Topology control scheme in manets foraodv routing. In Information andCommunication Technologies: FromTheory to Applications, 2008. ICTTA2008. 3rd International Conference on,pages 1 –6, 7-11 2008. 101 All Rights Reserved © 2012 IJARCET