On the performance of probabilistic flooding in wireless mobile ad hoc networks

Broadcasting in MANET’s has traditionally been based on flooding, but this can induce broadcast storms that severely degrade network performance due to redundant retransmission, collision and contention. Probabilistic flooding, where a node rebroadcasts a newly arrived one-to-all packet with some probability, p, was an early suggestion to reduce the broadcast storm problem. The first part of this thesis investigates the effects on the performance of probabilistic flooding of a number of important MANET parameters, including node speed, traffic load and node density. It transpires that these parameters have a critical impact both on reachability and on the number of so-called “saved rebroadcast packets” achieved. For instance, across a range of rebroadcast probability values, as network density increases from 25 to 100 nodes, reachability achieved by probabilistic flooding increases from 85% to 100%. Moreover, as node speed increases from 2 to 20 m/sec, reachability increases from 90% to 100%. The second part of this thesis proposes two new probabilistic algorithms that dynamically adjust the rebroadcasting probability contingent on node distribution using only one-hop neighbourhood information, without requiring any assistance of distance measurements or location-determination devices. The performance of the new algorithm is assessed and compared to blind flooding as well as the fixed probabilistic approach. It is demonstrated that the new algorithms have superior performance characteristics in terms of both reachability and saved rebroadcasts. For instance, the suggested algorithms can improve saved rebroadcasts by up to 70% and 47% compared to blind and fixed probabilistic flooding, respectively, even under conditions of high node mobility and high network density without degrading reachability. The final part of the thesis assesses the impact of probabilistic flooding on the performance of routing protocols in MANETs. Our performance results indicate that using our new probabilistic flooding algorithms during route discovery enables AODV to achieve a higher delivery ratio of data packets while keeping a lower routing overhead compared to using blind and fixed probabilistic flooding. For instance, the packet delivery ratio using our algorithm is improved by up to 19% and 12% compared to using blind and fixed probabilistic flooding, respectively. This performance advantage is achieved with a routing overhead that is lower by up to 28% and 19% than in fixed probabilistic and blind flooding, respectively

Probabilistic Mean Energy Flooding to increase the survivability of MANET

Wireless mobile ad hoc stations have limited battery capacity, hence, Ad Hoc routing protocols ought to be energy conservative. Route discovery is a common operation in routing to resolve many issues relating to energy conservation. In a Mobile Ad Hoc Networks (MANETs) in particular, due to host mobility, such operations are expected to be executed more frequently and a straightforward broadcasting by flooding is usually very costly and will result in serious redundancy, contention, and collision. In this paper, an algorithm is proposed to improve the flooding performance of an Ad Hoc On–Demand Distance Vector (AODV) routing protocol called, Probabilistic–Mean–Energy–Flooding (PMEF) which periodically performs an averaging algorithm Calculate–Average–Energy (CAE) to estimate the average energy Eavg. This algorithm is used in route discovery process to make a rebroadcast decision by the node. Route request message is rebroadcast with a probability that depends on the difference between the residual energy Er and the calculated average energy. Our simulation results show an improvement in the network lifetime and the throughput compared to traditional AODV

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 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

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

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

Neighbour coverage: a dynamic probabilistic route discovery for mobile ad hoc networks

Blind flooding is extensively use in ad hoc routing protocols for on-demand route discovery, where a mobile node blindly rebroadcasts received route request (RREQ) packets until a route to a particular destination is established. This can potentially lead to high channel contention, causing redundant retransmissions and thus excessive packet collisions in the network. Such a phenomenon induces what is known as broadcast storm problem, which has been shown to greatly increase the network communication overhead and end-to-end delay. In this paper, we show that the deleterious impact of such a problem can be reduced if measures are taken during the dissemination of RREQ packets. We propose a generic probabilistic method for route discovery, that is simple to implement and can significantly reduce the overhead associated with the dissemination of RREQs. Our analysis reveals that equipping AODV with probabilistic route discovery can result in significant reduction of routing control overhead while achieving good throughput

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