639 research outputs found

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

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    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

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

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    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

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

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

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    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

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

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    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

    Hybrid probabilistic broadcast schemes for mobile ad hoc networks

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    Broadcasting is one of the fundamental data dissemination mechanisms in mobile ad hoc network (MANET), which is, for instance, extensively used in many routing protocols for route discovery process. The dynamic topology and limited communication bandwidth of such networks pose a number of challenges in designing an efficient broadcasting scheme for MANETs. The simplest approach is flooding, where each node retransmit every unique received packet exactly once on each outgoing link. Although flooding ensures that broadcast packet is received by all network nodes, it generates many redundant transmissions which can trigger high transmission collision and contention in the network, a phenomenon referred to as the broadcast storm. Several probabilistic broadcast algorithms have been proposed that incur low communication overhead to mitigate the broadcast storm problem and tend to show superior adaptability in changing environments when compared to deterministic (i.e., non-probabilistic) schemes. However, most of these schemes reduce redundant broadcasts at the expense of reachability, a requirement for near-global network topological information or support from additional hardware. This research argues that broadcast schemes that combine the important features of fixed probabilistic and counter-based schemes can reduce the broadcast storm problem without sacrificing reachability while still achieving better end-to-end delay. To this end, the first part of this research investigate the effects of forwarding probabilities and counter threshold values on the performance of fixed probabilistic and counter-based schemes. The findings of this investigation are exploited to suggest a new hybrid approach, the Probabilistic Counter-Based Scheme (PCBS) that uses the number of duplicate packets received to estimate neighbourhood density and assign a forwarding probability value to restrict the generation of so many redundant broadcast packets. The simulation results reveal that under various network conditions PCBS reduces the number of redundant transmissions, collision rate and end-to-end delay significantly without sacrificing reachability when compared against counter-based, fixed probabilistic and flood broadcasting. Often in MANETs, there are regions of different node density due to node mobility. As such, PCBS can suffer from a degree of inflexibility in terms of rebroadcast probability, since each node is assigned the same forwarding probability regardless of its local neighbourhood conditions. To address this shortcoming, the second part of this dissertation proposes an Adjusted Probabilistic Counter-Based Scheme (APCBS) that dynamically assigns the forwarding probability to a node based on its local node density using a mathematical function. Thus, a node located in a sparse region of the network is assigned a high forwarding probability while a node located in denser region is assigned a relatively lower forwarding probability. These combined effects enhance end-to-end delay, collision rate and reachability compared to PCBS variant. The performance of most broadcasting schemes that have been suggested for MANETs including those presented here, have been analysed in the context of “pure” broadcast scenarios with relatively little investigation towards their performance impact on specific applications such as route discovery process. The final part of this thesis evaluates the performance of the well-known AODV routing protocol when augmented with APCBS route discovery. Results indicate that the resulting route discovery approach reduces the routing overhead, collision rate and end-to-end delay without degrading the overall network throughput compared to the existing approaches based on flooding, counterbased and fixed probabilistic route discovery

    Bandwidth and Energy-Efficient Route Discovery for Noisy Mobile Ad-Hoc Networks

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    Broadcasting is used in on-demand routing protocols to discover routes in Mobile Ad-hoc Networks (MANETs). On-demand routing protocols, such as Ad-hoc On-demand Distance Vector (AODV) commonly employ pure flooding based broadcasting to discover new routes. In pure flooding, a route request (RREQ) packet is broadcast by the source node and each receiving node rebroadcasts it. This continues until the RREQ packet arrives at the destination node. Pure flooding generates excessive redundant routing traffic that may lead to the broadcast storm problem (BSP) and deteriorate the performance of MANETs significantly. A number of probabilistic broadcasting schemes have been proposed in the literature to address BSP. However, these schemes do not consider thermal noise and interference which exist in real life MANETs, and therefore, do not perform well in real life MANETs. Real life MANETs are noisy and the communication is not error free. This research argues that a broadcast scheme that considers the effects of thermal noise, co-channel interference, and node density in the neighbourhood simultaneously can reduce the broadcast storm problem and enhance the MANET performance. To achieve this, three investigations have been carried out: First, the effect of carrier sensing ranges on on-demand routing protocol such as AODV and their impact on interference; second, effects of thermal noise on on-demand routing protocols and third, evaluation of pure flooding and probabilistic broadcasting schemes under noisy and noiseless conditions. The findings of these investigations are exploited to propose a Channel Adaptive Probabilistic Broadcast (CAPB) scheme to disseminate RREQ packets efficiently. The proposed CAPB scheme determines the probability of rebroadcasting RREQ packets on the fly according to the current Signal to Interference plus Noise Ratio (SINR) and node density in the neighbourhood. The proposed scheme and two related state of the art (SoA) schemes from the literature are implemented in the standard AODV to replace the pure flooding based broadcast scheme. Ns-2 simulation results show that the proposed CAPB scheme outperforms the other schemes in terms of routing overhead, average end-to-end delay, throughput and energy consumption
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