Multipath Position Based Routing Protocol For Mobile Ad-Hoc Network Using Adaptive Beacon Forwarding Scheme

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1 Volume 117 No , ISSN: (printed version); ISSN: (on-line version) url: doi: /ijpam.v117i8.12 ijpam.eu Multipath Position Based Routing Protocol For Mobile Ad-Hoc Network Using Adaptive Beacon Forwarding Scheme Jincy francis 1, Elakkiya S 2 Department of electronics and communication Veltech Dr.RR & SR University, Chennai, India jincyfrncs@gmail.com Abstract Mobile Ad Hoc Network (MANET) is a collection of wireless mobile nodes that dynamically form a temporary network topology without the reliance on any infrastructure or central administration. Flooding is one of the simplest way of broadcasting, in which each node in the network retransmits an incoming message once. To find destination address of each node, position based routing protocols can opt. Geographic routing has been widely considered as the most scalable wireless position based routing in which each node maintains the current position of their immediate neighbors. Broadcasting of packets to the destination is inefficient in terms of resource consumption such as energy and band-width This paper presents a new hybrid scheme that combines different techniques which leads to a dynamic position updation mechanism known adaptive beacon forwarding scheme ABFS. Keywords- manet, routing, mobility, forwarding, packet delivery. 1. INDRODUCTION A multi hop network with self organizing and self configuring capability can be possible using DSR (Dynamic Source Routing protocol. Which is one of the simple yet efficient on demand routing protocol.in multi-hop wireless ad hoc networks, as nodes in the network moves out or join in the network all the routing path will automatically update and maintain by DSR routing protocol. The DSR protocol provides reactive service in order to ensure successful delivery of data packets in spite of dynamic movement of node or other changes in network topology. Route discovery and route maintenance are the two mechanism to design DSR protocol to reduce routing overhead and topology updation. Route discovery: mechanism to uncover a new path for the source to send its message to destination for the first time Route maintenance: consider the source is using an established path to destination for data sending. After sending few packets due to topology change shown in figure 1.1, if any link is broken in the route source can t use the same path for further data forwarding.either the source can use other established paths to destination or else invoke route discovery mechanism to find a new path. Figure 1.1 Topology Changes in MANET 2.RELATED WORK Geographic routing has been considered as an effective and flexible routing protocol, since it utilize nodes current location information to route data packets to a destination instead of global network topology information in error-prone wireless sensor networks. All node are aware about the current position of neighboring node and each node have the capability to find its own position.this geographical information is used for data transfer instead of using the network address. This type of routing is known as geographic routing or geo routing. Position-based routing protocols are highly scalable and robust to random changes in the network topology. To forward the data packet position information of neighboring node and destination position information is required for all type of packet forwarding strategies (unicasting, broadcasting and multicasting)[10].geographical routing develop a local topology to make correct forwarding decisions and avoids routing table maintenance, and hence reduces the control overhead. Each node share its location information to the neighboring node and update its own location in periodic intervals. Position information of nodes can find out by means of any location finding schemes like GPS. The mechanism used in position based routing is greedy mechanism where node forwards a packet to the neighboring node that is very closest to the destination and node generate 55

2 a local map consist of the position information of all neighboring nodes within its vicinity. The forwarding path is determined by either the sender node or the intermediate node in the forwarding zone. The local topology maintenance require a periodic beacon sending mechanism. This periodic updation of position information of each node is not an efficient method for topology maintenance due to the following reasons. Sending of beacon frame in periodic interval increase the energy conception of each node. Beacon packets doesn t consist of any message leads to the decreasing in effective band width utilization.if the number of nodes in the network increases then the number of beacon packets also increases which leads to packet collision. To avoid this issue generated by the beacons, many beaconless geometric routing protocols have been proposed in the literature. The basic idea of beaconless routing is to reactively discover the position information of neighbor nodes when routing data packets. It can be divided into two schemes according to the forwarding path selection method the handshake-based method and : the fully-distributed method.the research work on beaconless routing find these following feedback.1.routing protocols cannot be directly applied to the error-prone wireless sensor networks because of their limitations.2. Reactively recovering the location information of neighbors leads to significant delay problem.these limitations causes them to not be suited in most real-time sensor applications. 3.PROPOSED SYSTEM The basic idea of geographic routing is that the current node finds the Euclidean distance from each neighbor node to the destination.selects the closest neighbor to the destination as a next-hop forwarding node according to the calculated Euclidean distance. Finally, the current node sends the beacon packet to the closest neighbor, and this process is repeated until the packet arrives at the destination, called greedy routing. In order to realize the location information of neighbor nodes before routing, every sensor node in the network periodically should exchange the beacon.which is a control message consisting of its identifier and its location information..flooding of beacon leads to unnecessary energy consumption, interference, congestion and/or collisions problems[1-9]. 3.1 System and Network Model The rate of dynamism of each node varies depends of nodal characteristics, certain node shows low rate of mobility and some high rate. Nodes which shows high rate of mobility should update its position information frequently compared to nodes with low rate of mobility characteristics. Another considering factor is that during the data transmission from source to destination only few nodes are participating for packet forwarding. To update all the remaining nodes position information is unnecessary and expensive. Nodes which are nearer to the forwarding path should updates its position information compared to nodes which are far away from the forwarding path. Considering these to facts we proposed system to dynamically adjust the beacon updation interval. The main assumptions made in our work is that a)all nodes should aware of their location information and velocity b)all links in the network are capable of bi-directional data transmission. C) during initialization each node broadcasts a beacon frame informing its neighbors about its presence and its current location and velocity Dynamicity prediction rule The beacon updation interval rate is determined by the mobility characteristic or dynamic property of nodes. The mobility characteristics is broadcast to the neighboring node through control packet known as beacon. By the help of linear motion (kinematic) equations all the neighbors can then trace the node s motion. How to predict the rate of dynamism is explained below (x l n,y l n ) The X and Y Co-ordinate values of node N at time T last (included in the previous becon) (xp n,yp n ) The predicted X and Y Coordinate values of node N at current time t current (V X N V Y N ) The velocity of node N along the direction of the Xand Yaxes at time T last (included in the previous becon) T last T current The time of the last beacon broadcast The current time Table Common Notations for Dynamicity prediction Consider the node N was in the position (x l n,y l n )with velocity (V X N,V Y N ).That known position already updated to neighbor nodes by beacon packet send at time T last.after some time interval t current the node moved to new position (xp n,yp n ). To find out the new co ordinate values we can use kinematic equations 56

3 M was transmitting data packets, then they will not consider each other while selecting the next hop until their local topology will not be updated. Figure3.1.1 An example of dynamicity prediction Xp n = x l n + (t current - T last ) *V X N Yp n = Y l N + (t current - T last ) * V Y N We assume that the nodes are located in a twodimensional coordinate system with the location indicated by the X and y coordinates, velocity V and time T. If nodes moves from the position (x l n,y l n ) to (xp n,yp n ). To find out whether the node is having high/low rate of mobility deviation distance should calculate. n D DEV = (x l - xp n ) 2 n +( y l - yp n ) 2 If the deviation distance between the current position and previous position of node is above the threshold value,the new position coordinates (xp n,yp n ) will update by sending a new beacon to neighboring nodes. If deviation value is less than threshold no beacon will send and neighboring node use the position information (x l n,y l n ) that send by beacon at time T last. The dynamicity prediction rule, thus try to broadcasting a beacon only when the predicted location information based on the previous beacon becomes inaccurate and relative location difference is grater than the acceptable range. This change the time duration of the beacon updation for nodes from periodic to non periodic. This rule further reduce the number of beacon and increase the energy efficiency. Neighbor can easily adapt to rapid topology changes and able to update new routing paths On- Demand rule The dynamicity prediction rule, may not be sufficient for maintaining an accurate topology. Consider the following situations refer figure Node N moves from P1 to P2 at a constant speed. Now, assume that node N has sent a beacon packet while at P1. Consider if node M is unaware of the existence of node N and did not receive this packet. Assume that the deviation range is sufficiently large such that when node N moves from P1 to P2 the dynamicity prediction rule is never initiated. 2. After a significant mobility node N over inside the transmission range of M.Even then, neither node N nor node M will be aware of each other presence in the transmission range. Now, in situations where node N or node figure3.1.2.an example illustrating a disadvantage of the dynamicity prediction rule In some extreme situations like link broken case and assume no other nodes were in the vicinity of transmission range, the data packets would not be forwarded at all. So to maintain a more accurate and updated local topology in those regions of the network where major data forwarding activities are on-going. According to this rule, whenever a node overhears a message transmission from a new neighbor node, it sends a beacon packet as a response and node waits for a small time interval before responding with the new beacon to avoid collisions with other beacons. If the data packet follows piggybacking system and contains the actual position information of the final destination along with data,then any node that overhears a data packet also checks its current position and checks if the destination is within its transmission range. In such a situation destination node will added to the list of neighboring node only if the destination node is a new entry. 3.2 Simulation Evaluation We evaluate the performance of the proposed protocol in terms of the data throughput, the packet delivery ratio and the average energy conception with well-known on demand routing protocols DSR in wireless sensor networks We compare each nods previous position details and its topology changes, and gets an idea that whether the node is highly mobile or not. If the node shows low mobility characteristics then we select the node for forwarding the data packet. While selecting the next node, we consider those nodes which are very nearer to the destination and far from the source. So that the number of nodes needs to deliver the data from the source to destination is reduced. Demand source routing is used for the effective data transmission for 48 nodes. Set val(rp) DSR ;# Routing Protocol Set val(nn) 48 ;# number of mobile nodes Topology creation is the following step Set topo [new Topography] $topo load_flatgrid $val(x) $val(y) 57

4 Initially the position of 48 nodes is same then we deploy each node by inputting some values to x and y coordinates. We create some sink nodes as intermediate nodes and CBR is assigned. To create the local topology we calculate distance between the neighbor nodes. According to the acceptable error range value we decide whether we need to update the new positional coordinates as a new beacon. First we assign one node as source and another as destination. In order to select the next node we consider the distance between each node and select a node which is far away from source and nearer to the destination. Fig Packet Delivery Ratio Packet delivery ratio: this metric represents the ratio of the number of successfully reached data from source to destination from the simulation its very clear that successful data delivery in proposed system is in significant number compared to DSR. Fig Throughput graph We evaluated the data throughput of the route from a source to the destination of by using the number of packets per second delivered by considering the factors such as the network protocols used, the capabilities of routers and switches, and the type of cabling, used to create a network. Adaptive beacon forwarding strategy is having high throughput compared to DSR. Fig Average energy conservation The energy conception in proposed system is significantly large because number of beacon packet is considerably less. 4.conclusion In this paper, we have identified the need to adapt the beacon forwarding policy employed in geographic routing protocols to the node mobility dynamic characteristics, We proposed the Adaptive beacon forwarding strategy to address these problems. It aims at increasing forwarding opportunities by giving different contention priorities to the bi directional nodes. Our various experimental results showed that the proposed protocol has better performance than the DSR protocols. References 1. Heissenbuttel, M.; Braun, T.; Bernoulli, T.; Wachli, M. BLR: Beacon-Less Routing Algorithm for Mobile Ad-Hoc Networks. Comput. Commun. J. ECC 2004, 27, Witt, M.; Turau, V. BGR: Blind Geographic Routing for Sensor Networks. In Proceedings of the Third Workshop on Intelligent Solutions in Embedded Systems (WISES), Hamburg, Germany,20 May Sanchez, J.A.; Marin-Perez, R.; Ruiz, P.M. BOSS: Beaconless on demand strategy for geographic routing in wireless sensor networks. In Proceedings of the 4th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS), Pisa, Italy, 8 11 October 2007; pp. 4. Rosario, D.; Zhao, Z.; Braun, T.; Cerqueira, E.; Santos, A.; Li, Z. Assessment of a Robust Opportunistic Routing for Video Transmission in Dynamic Topologies. In Proceedings of the IEEE Wireless Days (WD) Conference, Valencia, Spain, November Rosario, D.; Zhao, Z.; Braun, T.; Cerqueira, E.; Santos, A.; Alyafa, I. Opportunistic Routing for Multi-flow Video Dissemination over Flying Ad-Hoc Networks. In Proceedings of the 15th International Symposium ona World of Wireless, Mobile and Multimedia Networks (WoWMoM),Sydney, Australia, June Fuessler, H.; Widmer, J.; Kasemann, M.; Mauve, M.; Hartenstein, H. Contention-Based Forwarding for Mobile Ad Hoc Networks. Ad Hoc Netw. 2003, 1, Sanchez, J.A.; Marin-Perez, R.; Ruiz, P.M. Beacon-Less Geographic Routing in Real Wireless Sensor Networks. J. Comput. Sci. Technol. 2008, 23, Sanchez, J.A.; Ruiz, P.M.; Marin-Perez, R. Beacon-less Geographic Routing Made Practical: Challenges, Design Guidelines, and Protocols. IEEE Commun. Mag. 2009, 47, Marin-Perez, R.; Ruiz, P.M. SBGR: A Simple Self- Protected Beaconless Geographic Routing for Wireless Sensor Networks. In Proceedings of the IEEE International Conference on Mobile Adhocand Sensor Systems (MASS), Valencia, Spain, October 2011; pp [10] P. Casari, M. Nati, C. Petrioli and M.Zorzi. Efficient Non Planar Routing around Dead Ends in Sparse Topologies using Random Forwarding, in Proceedings of IEEE ICC, pp Scotland, UK, June [11] S. Basagni, M. Nati, C. Petrioli and R. Petroccia ROME: routing over mobile elements in WSNs, in Proceedings of the 28 th IEEE conference on Global telecommunications (GLOBECOM), pp Honolulu, Hawaii, USA, December,

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