Improvement to efficient counter-based broadcast scheme through random assessment delay adaptation for MANETs

Flooding, the process in which each node retransmits every uniquely received packet exactly once is the simplest and most commonly used mechanism for broadcasting in mobile ad hoc networks (MANETs). Despite its simplicity, it can result in high redundant retransmission, contention and collision, a phenomenon collectively referred to as broadcast storm problem. To mitigate this problem, several broadcast schemes have been proposed which are commonly divided into two categories; deterministic schemes and probabilistic schemes. Probabilistic methods are quite promising because they can reduce the number of redundant rebroadcast without any control overhead. In this paper, we investigate the performance of our earlier proposed efficient counter-based broadcast scheme by adapting its random assessment delay (RAD) mechanism to network congestion. Simulation results revealed that this simple adaptation achieves superior performance in terms of saved rebroadcast, end-to-end delay and reachability

Improving route discovery in on-demand routing protocols using local topology information in MANETs

Most existing routing protocols proposed for MANETs use flooding as a broadcast technique for the propagation of network control packets; a particular example of this is the dissemination of route requests (RREQs), which facilitate route discovery. In flooding, each mobile node rebroadcasts received packets, which, in this manner, are propagated network-wide with considerable overhead. This paper improves on the performance of existing routing protocols by reducing the communication overhead incurred during the route discovery process by implementing a new broadcast algorithm called the adjusted probabilistic flooding on the Ad-Hoc on Demand Distance Vector (AODV) protocol. AODV [3] is a well-known and widely studied algorithm which has been shown over the past few years to maintain an overall lower routing overhead compared to traditional proactive schemes, even though it uses flooding to propagate RREQs. Our results, as presented in this paper, reveal that equipping AODV with fixed and adjusted probabilistic flooding, instead, helps reduce the overhead of the route discovery process whilst maintaining comparable performance levels in terms of saved rebroadcasts and reachability as achieved by conventional AODV\@. Moreover, the results indicate that the adjusted probabilistic technique results in better performance compared to the fixed one for both of these metrics

Performance evaluation of adjusted probabilistic broadcasting in MANETs

Appropriate use of a probabilistic broadcasting method in MANETs can decrease the number of rebroadcasts, and as a result reduce the opportunity of contention and collision among neighbouring nodes. In this paper we evaluate the performance of adjusted probabilistic flooding by comparing it to "simple" flooding as used with the ad hoc on demand distance vector (AODV) routing protocol as well as a fixed probabilistic approach. The results reveal that the adjusted probabilistic flooding exhibits superior performance in terms of both reachability and saved rebroadcast

Dissimilarity metric based on local neighboring information and genetic programming for data dissemination in vehicular ad hoc networks (VANETs)

This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data dissemination schemes, which use the relative Euclidean distance among vehicles to determine the retransmission probability. The novel dissimilarity metric is obtained by applying a metaheuristic genetic programming approach, which provides a formula that maximizes the Pearson Correlation Coefficient between the novel dissimilarity metric and the Euclidean metric in several representative VANET scenarios. Findings show that the obtained dissimilarity metric correlates with the Euclidean distance up to 8.9% better than classical dissimilarity metrics. Moreover, the obtained dissimilarity metric is evaluated when used in well-known data dissemination schemes, such as p-persistence, polynomial and irresponsible algorithm. The obtained dissimilarity metric achieves significant improvements in terms of reachability in comparison with the classical dissimilarity metrics and the Euclidean metric-based schemes in the studied VANET urban scenarios

Performance evaluation of an efficient counter-based scheme for mobile ad hoc networks based on realistic mobility model

Flooding is the simplest and commonly used mechanism for broadcasting in mobile ad hoc networks (MANETs). Despite its simplicity, it can result in high redundant retransmission, contention and collision in the network, a phenomenon referred to as broadcast storm problem. Several probabilistic broadcast schemes have been proposed to mitigate this problem inherent with flooding. Recently, we have proposed a hybrid-based scheme as one of the probabilistic scheme, which combines the advantages of pure probabilistic and counter-based schemes to yield a significant performance improvement. Despite these considerable numbers of proposed broadcast schemes, majority of these schemes’ performance evaluation was based on random waypoint model. In this paper, we evaluate the performance of our broadcast scheme using a community based mobility model which is based on social network theory and compare it against widely used random waypoint mobility model. Simulation results have shown that using unrealistic movement pattern does not truly reflect on the actual performance of the scheme in terms of saved-rebroadcast, reachability and end to end delay

An efficient counter-based broadcast scheme for mobile ad hoc networks

In mobile ad hoc networks (MANETs), broadcasting plays a fundamental role, diffusing a message from a given source node to all the other nodes in the network. Flooding is the simplest and commonly used mechanism for broadcasting in MANETs, where each node retransmits every uniquely received message exactly once. Despite its simplicity, it however generates redundant rebroadcast messages which results in high contention and collision in the network, a phenomenon referred to as broadcast storm problem. Pure probabilistic approaches have been proposed to mitigate this problem inherent with flooding, where mobile nodes rebroadcast a message with a probability p which can be fixed or computed based on the local density. However, these approaches reduce the number of rebroadcasts at the expense of reachability. On the other hand, counter-based approaches inhibit a node from broadcasting a packet based on the number of copies of the broadcast packet received by the node within a random access delay time. These schemes achieve better throughput and reachability, but suffer from relatively longer delay. In this paper, we propose an efficient broadcasting scheme that combines the advantages of pure probabilistic and counter-based schemes to yield a significant performance improvement. Simulation results reveal that the new scheme achieves superior performance in terms of saved-rebroadcast, reachability and latency

Performance evaluation of flooding in MANETs in the presence of multi-broadcast traffic

Broadcasting has many important uses and several mobile ad hoc networks (MANETs) protocols assume the availability of an underlying broadcast service. Applications, which make use of broadcasting, include LAN emulation, paging a particular node. However, broadcasting induces what is known as the "broadcast storm problem" which causes severe degradation in network performance, due to excessive redundant retransmission, collision, and contention. Although probabilistic flooding has been one of the earliest suggested approaches to broadcasting. There has not been so far any attempt to analyse its performance behaviour in MANETs. This paper investigates using extensive ns-2 simulations the effects of a number of important parameters in a MANET, including node speed, pause time and, traffic load, on the performance of probabilistic flooding. The results reveal that while these parameters have a critical impact on the reachability achieved by probabilistic flooding, they have relatively a lower effect on the number of saved rebroadcast packets

Adaptive Broadcasting Method Using Neighbor Type Information in Wireless Sensor Networks

Flooding is the simplest and most effective way to disseminate a packet to all nodes in a wireless sensor network (WSN). However, basic flooding makes all nodes transmit the packet at least once, resulting in the broadcast storm problem in a worst case, and in turn, network resources are severely wasted. Particularly, power is the most valuable resource of WSNs as nodes are powered by batteries, then the waste of energy by the basic flooding lessens the lifetime of WSNs. In order to solve the broadcast storm problem, this paper proposes a dynamic probabilistic flooding that utilizes the neighbor information like the numbers of child and sibling nodes. In general, the more sibling nodes there are, the higher is the probability that a broadcast packet may be sent by one of the sibling nodes. The packet is not retransmitted by itself, though. Meanwhile, if a node has many child nodes its retransmission probability should be high to achieve the high packet delivery ratio. Therefore, these two terms—the numbers of child and sibling nodes—are adopted in the proposed method in order to attain more reliable flooding. The proposed method also adopts the back-off delay scheme to avoid collisions between close neighbors. Simulation results prove that the proposed method outperforms previous flooding methods in respect of the number of duplicate packets and packet delivery ratio