5 research outputs found

    Communication Over a Wireless Network With Random Connections

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    A network of nodes in which pairs communicate over a shared wireless medium is analyzed. We consider the maximum total aggregate traffic flow possible as given by the number of users multiplied by their data rate. The model in this paper differs substantially from the many existing approaches in that the channel connections in this network are entirely random: rather than being governed by geometry and a decay-versus-distance law, the strengths of the connections between nodes are drawn independently from a common distribution. Such a model is appropriate for environments where the first-order effect that governs the signal strength at a receiving node is a random event (such as the existence of an obstacle), rather than the distance from the transmitter. It is shown that the aggregate traffic flow as a function of the number of nodes n is a strong function of the channel distribution. In particular, for certain distributions the aggregate traffic flow is at least n/(log n)^d for some d≫0, which is significantly larger than the O(sqrt n) results obtained for many geometric models. The results provide guidelines for the connectivity that is needed for large aggregate traffic. The relation between the proposed model and existing distance-based models is shown in some cases

    Techniques for Analyzing Random Graph Dynamics and Their Applications

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    Impact of directional antennas on routing and neighbor discovery in wireless ad-hoc networks

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    Wireless ad-hoc networks are data networks that are deployed without a fixed infrastructure nor central controllers such as access points or base stations. In these networks, data packets are forwarded directly to the destination node if they are within the transmission range of the sender or sent through a multi-hop path of intermediary nodes that act as relays. This paradigm where a fixed infrastructure is not needed, is tolerant to topology changes and allows a fast deployment have been considered as a promissory technology that is suitable for a large number of network implementations, such as mobile hand-held devices, wireless sensors, disaster recovery networks, etc. Recently, smart directional antennas have been identified as a robust technology that can boost the performance of wireless ad-hoc networks in terms of coverage, connectivity, and capacity. Contrary to omnidirectional antennas, which can radiate energy in all directions, directional antennas can focus the energy in a specific direction, extending the coverage range for the same power level. Longer ranges provide shorter paths to destination nodes and also improve connectivity. Moreover, directional antennas can reduce the number of collisions in a contention-based access scheme as they can steer the main lobe in the desired direction and set nulls in all the others, thereby they minimize the co-channel interference and reduce the noise level. Connections are more reliable due to the increased link stability and spatial diversity. Shorter paths, as well as alternative paths, are also available as a consequence of the use of directional antennas. All these features combined results in a higher network capacity. Most of the previous research has focused on adapting the existing medium access control and routing protocols to utilize directional communications. This research work is novel because it improves the neighbor discovery process as it allows to discover nodes in the second neighborhood of a given node using a gossip based procedure and by sharing the relative position information obtained during this stage with the routing protocol with the aim of reducing the number of hops between source and destination. We have also developed a model to evaluate the energy consumed by the nodes when smart directional antennas are used in the ad-hoc network. This study has demonstrated that by adapting the beamwidth of the antennas nodes are able to reach furthest nodes and consequently, reduce the number of hops between source and destination. This fact not only reduces the end-to-end delay and improves the network throughput but also reduces the average energy consumed by the whole network
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