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

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

GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks

Wireless sensor networks (WSN) have recently received an increasing interest. They are now expected to be deployed for long periods of time, thus requiring software updates. Updating the software code automatically on a huge number of sensors is a tremendous task, as ''by hand'' updates can obviously not be considered, especially when all participating sensors are embedded on mobile entities. In this paper, we investigate an approach to automatically update software in mobile sensor-based application when no localization mechanism is available. We leverage the peer-to-peer cooperation paradigm to achieve a good trade-off between reliability and scalability of code propagation. More specifically, we present the design and evaluation of GCP ({\emph Gossip-based Code Propagation}), a distributed software update algorithm for mobile wireless sensor networks. GCP relies on two different mechanisms (piggy-backing and forwarding control) to improve significantly the load balance without sacrificing on the propagation speed. We compare GCP against traditional dissemination approaches. Simulation results based on both synthetic and realistic workloads show that GCP achieves a good convergence speed while balancing the load evenly between sensors

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 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

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

Requirement analysis for building practical accident warning systems based on vehicular ad-hoc networks

An Accident Warning System (AWS) is a safety application that provides collision avoidance notifications for next generation vehicles whilst Vehicular Ad-hoc Networks (VANETs) provide the communication functionality to exchange these notifi- cations. Despite much previous research, there is little agreement on the requirements for accident warning systems. In order to build a practical warning system, it is important to ascertain the system requirements, information to be exchanged, and protocols needed for communication between vehicles. This paper presents a practical model of an accident warning system by stipulating the requirements in a realistic manner and thoroughly reviewing previous proposals with a view to identify gaps in this area