The Best of Manets Works

As defined in [ 13 — 16 ] these routing protocols combines the features of both reactive and on-demand routing strategies. Basically, these kinds of routing protocols split the whole mobile network into group of clusters, also known as zones. Proactive routing strategy is performed inside the zone and it is responsible for the process of identifying the new routes and maintaining all the identified valid routes in intrazone. On the other side reactive routing strategy is performed between the clusters or zones.

Every cluster will be managed by one among the mobile nodes of a particular zone known as cluster head. Broadcasting is the simple and basic process in Mobile Ad Hoc Networks in which the same packet has been transmitted from the sender node to all the remaining nodes of the network. Hence, the packet which is transmitted from the valid mobile source cannot reach the target in a single hop.

So, here some other nodes of the network are required to forward the source transmitted packet to the destination. These nodes are often known as intermediate nodes. In MANET, the process of choosing the intermediate node is the most important factor because these nodes will use the valuable resources of the network like battery power and bandwidth. Also, the process of intermediate node selection will reduce or avoid the redundancy in packet forwarding process.

There are two basic models which are used in broadcasting with respect to physical layer, namely, one-to-many model in which the source transmitted packet will be sent to the other neighbor mobile nodes of the transmission initiated node neighbor nodes are the mobile nodes which come under the radio range of the source node and one-to-one model in which the source transmitted packet will be given to a specific neighbor only. As discussed in [ 17 , 18 ] the broadcasting process has many advantages with respect to the network layer. However, the broadcasting mechanism in Mobile Ad Hoc Network acts as a backbone of several protocols which are available in the network layer.

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The broadcasting serves several purposes like paging of a node, packet forwarding to the entire mobile network, network management, overhead control, route discovery, and maintenance. A reasonable number of broadcasting strategies are supported by several authors [ 19 , 20 ] which includes probability based routing, counter value based routing, location based routing, and neighbor knowledge based routing. In probabilistic based routing approach the intermediate nodes forward the packet to its neighbor based on some fixed probability value.

In this work, we have introduced a probabilistic based routing method which is commonly known as dynamic probabilistic route discovery. Here, the mobile nodes can calculate their forwarding probability for respective data packet in a dynamic manner and this calculation is performed by using probability function which depends on density of the local neighbor and the cumulative number of its neighbors. The task of including the neighbor information gathering algorithm to enable the functionalities of DPR scheme is a difficult one because the probability function PF of the DPR approach depends on the density and number of neighbor nodes of the corresponding node.

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The DPR approach first divides the network into two groups based on the density using local density of the corresponding node and which are known as sparse and dense networks. In [ 2 , 18 , 21 , 22 ] the broadcasting approaches are proposed with forwarding probability to coordinate the forwarding process of the broadcasted packet which is calculated based on the local density and the number of local neighbors.

With respect to the discussion made in [ 22 , 23 ] for the design and implementation of self- pruning approach, every node in the network e. The number of neighbor nodes of a corresponding node is calculated as 1-number of hops. Here, N R denotes the set of neighbor nodes of the node R. In [ 21 , 24 ], the authors proved that the network overhead with respect to data packet communication is high if the network uses 1-hop neighborhood information, especially in dense region of the mobile network. Hence, the authors suggested that each mobile node must have 2-hop neighborhood information for the purpose of reducing the quantity of mobile nodes involved in the process of forwarding the mobile data packet which could be attained by periodically exchanging the control packets among the neighbor nodes.

The developed efficient route discovery strategy will be useful for finding the shortest route to the targeted mobile node by avoiding the need of GPS receivers and global topological information while revealing aggressive system concert e. For the purpose of analyzing the performance of the proposed approach DPR, the traditional DSDV routing algorithm with neighborhood information gathering approach has been used.

The information gathering approach uses the periodic control packet transmission among the neighbor nodes to collect the 2-hop neighbor information at a corresponding node. Hence, in the DPR scheme, with respect to the equation shown in 1 , a node in the dense region where number of neighbor is greater than 25, i. Figure 1 shows the packet forwarding at four different nodes in typical dense network along with different number of neighbor sets. Let us consider the total number of neighbor mobile nodes at a node X as n and let the total number of neighbor mobile nodes of X that are located inside the radio range of X and which are covered by the broadcast as n c.

Then the forwarding probability at the mobile node X is. The performance evaluation and the result analysis are obtained by the DPR approach, with the implementation of AODV routing protocol in NS2 simulator [ 25 ] which has been modified to enhance the process of DPR approach.

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The simulation has been performed on DPR with respect to the varying density of the network and offered load at different levels. Performance metrics which are considered for this analysis are network overhead during the routing process, rate of collision which will be calculated during the packet transmission, network throughput which will be obtained by achieving the successful delivery of mobile data packet, and the end-to-end delay which will increase the delay in the successful packet delivery.

The following assumptions, which have been widely adapted, are used throughout this work and the simulation parameters are listed in Table 1. In this simulation, some threshold values are considered and used to perform the comparison of performance between the existing and proposed algorithms. The threshold values are chosen based upon the study performed in variety of existing results. These values are commonly used by many researchers. This part of simulation analyzes the effect of the network density which will be dynamically changing during the simulation process.

The number of valid communication links between the source and destination node has been considered and those links are randomly selected by the corresponding algorithm. The overhead in all the three routing protocols is linearly increased when the density of the network increases. However, DPR outperforms AODV and FP because of the fact that in DPR the forwarding probability FP is decided based on the local density of the mobile node and number of neighbor nodes, which causes redundancy in the number of control packet transmission and leads to the overall overhead reduction.

The piggybacked list of 2-hop neighbor information has been forwarded along with RREQ packets in DPR; as a result the overhead is amplified with respect to number of bytes of data transmitted. By considering this case, Figure 3 illustrates the operation of the considered routing protocols with respect to overhead in terms of bytes. Even though the DPR produces less overhead when compared to the remaining two protocols with respect to number of packets transmitted as revealed in Figure 2 , the decrease in overhead of DPR is comparatively low. In MANET, increasing in packet transmission also increases the traffic and congestion which leads to the packet collision.

Figure 4 shows the average collision rate of all the three routing protocols with respect to network density. Since the communication medium is shared by both control and data packet transmission, the probability of the collision also increases without having proper approach to control the retransmission of the route request packet.

Normalized throughput of the network which is plotted against the density of the network is shown in Figure 5. The figure proves that the throughput of the network is very low when the region of the network is sparse. The reason behind this is poor connectivity ratio among the mobile nodes of the sparse region Figure 6. On the other hand, the connectivity ratio is better, when the network becomes dense. This increases the number of control packet RREQ retransmission and leads to insufficient bandwidth for data packet transmission. Hence, there is a sudden drop of the network throughput even in the dense network.

Therefore, if there are any measures taken towards controlling the repeated retransmission of route request packet, then the degradation of the throughput could be reduced.

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Figure 7 gives an idea about the end-to-end delay in the dense and sparse area of the available mobile network. Also, it portrays that the delay is relatively high for all the three protocols in both sparse and dense regions of the network. This is because in sparse region the connectivity ratio is less. Due to this, the failure of RREQ packets to reach the destination is high. Subsequently, the end-to-end delay is also increased for every mobile node whereas in dense network, due to high contention which is rooted by massive unnecessary retransmission of control packets, the destination originated packets fail to reach the destination.

This leads to increase in delay. To analyze the performance of the mobile node with respect to the offered load of all the three routing protocols, here we have considered different number of source-to-destination connections known as flows. The load on the mobile network has been assorted like 1,5, 10,15,…, 60 flows. However, the proposed approach DPR performs well against all the other protocols in terms of both packet transmission and byte transmission.

The proposed approach outfits the route discovery operation only to smaller amount of mobile nodes which are contributing in the RREQ forwarding. As the overhead represented in the above section, collision rate also linearly increases for all the routing protocols when the dynamically given load has been increased as depicted in Figure The reason behind this is the number of flows has been amplified when increasing the load, which leads to generation and retransmission of route request packets. Hence, the collision rate automatically increases.

This is because the DPR drops the good number of route request packets which is forwarded by the forwarding mobile node which is based on the forwarding probability.

The FP is calculated based on the home density and the total number of contributing local neighbors. Hence, the channel contention is reduced which leads to less collision rate in DPR. In Figure 11 , we have demonstrated the throughput of the network with respect to offered load. Here the offered load has been increased by growing the number of participating flows from 1 to The protocol represented in the figure clearly discloses that the success rate of the network is high when the offered load is squat.

When we increase the offered load then the throughput also decreases, respectively, and it is reduced irrespective of routing algorithms. This is because when we increase the load, it increases the number of mobile nodes which will initiate the route discovery process. As a result, the generation and transmission of route request packet also increases and it leads to high contention in the data communication channel and packet collision. In Figure 12 , the connectivity success ratio is depicted and it reveals that the DPR outperforms when compared with all other routing protocols. As a result of high connectivity ratio with respect to result shown in Figure 12 , the DPR produces high throughput when compared with other protocols as depicted in Figure As shown in Figure 13 , the delay increases when the dynamic load increases.

A Dynamic Probabilistic Based Broadcasting Scheme for MANETs

The reason is when the load of the network is enlarged it will increase the contention on the network. Hence, the route failure occurs frequently, when the contention is high. However, the DPR performs relatively well when compared with other routing protocols.

The proposed schemes open a novel approach for probabilistic based broadcasting approach for route discovery known as dynamic probabilistic based routing DPR. In DPR, the packets are forwarded to the neighbor node with dynamically computed probability called as forwarding probability FP. The probability function is calculated based on the density of the local neighbors and cumulative amount of neighbor mobile nodes.

Hence, it is vital to identify the dense and sparse regions. The performance of the various routing protocols has been compared using various quality of service parameters of MANET, namely, overhead, average collision rate, end-to-end delay, and network throughput. The system parameters like impact of network density and impact of offered load are considered for assessing the performance of the planned routing approach.

The simulation results for impact of the varying network density for all the three considered routing methods with respect to the overhead and collision rate degrade the performance when the density is increased. Here, these performance measurements are analyzed by considering the packet transmission in terms of both packet and bytes. National Gallery of Art Washington, D. Portrait of Victorine Meurent. Museum of Fine Arts Boston. Young Man in the Costume of a Majo. The Dead Christ with Angels. National Gallery of Art Washington D. The Battle of the U. Philadelphia Museum of Art.

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1. Introduction

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