• Impact of gateways placement on clustering algorithms in wireless mesh networks

      Waharte, Sonia; Boutaba, Raouf; Anelli, Pascal (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2009)
      Abstract—In wireless mesh networks, designing algorithms that efficiently balance the traffic loads among a given set of network gateways is a challenging problem. Links interfere, transfer capacity is limited, and traffic demands vary overtime. The position of the gateways also affects the overall network performance as a result of its direct impact on the way routers are associated to gateways. In this paper, we investigate the performance of several routers-to-gateways association heuristics in relation with different gateway placement algorithms.We show that if bounds on the number of hops between routers and gateways exist, load-based heuristics perform the best. In general cases however, interference-based approaches provide better load balancing.
    • Probabilistic search with agile UAVs

      Waharte, Sonia; Symington, Andrew; Trigoni, Niki (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010)
      Through their ability to rapidly acquire aerial imagery, Unmanned Aerial Vehicles (UAVs) have the potential to aid target search tasks. Many of the core algorithms which are used to plan search tasks use occupancy grid-based representations and are often based on two main assumptions. Firstly, the altitude of the UAV is constant. Secondly, the onboard sensors can measure the entire state of an entire grid cell. Although these assumptions are sufficient for fixed-wing, high speed UAVs, we do not believe that they are appropriate for small, lightweight, low speed and agile UAVs such as quadrotors. These platforms have the ability to change altitude and their low speed means that multiple measurements may easily overlap multiple cells for substantial periods of time. In this paper we extend a framework for probabilistic search based on decision making to incorporate multiple observations of grid cells and changes in UAV altitude. We account for observation areas that completely and partially cover multiple grid cells. We show the resultant impact on a number of simulation examples.
    • Probabilistic target detection by camera-equipped UAVs

      Symington, Andrew; Waharte, Sonia; Julier, Simon; Trigoni, Niki (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010)
      This paper is motivated by the real world problem of search and rescue by unmanned aerial vehicles (UAVs). We consider the problem of tracking a static target from a bird's-eye view camera mounted to the underside of a quadrotor UAV. We begin by proposing a target detection algorithm, which we then execute on a collection of video frames acquired from four different experiments. We show how the efficacy of the target detection algorithm changes as a function of altitude. We summarise this efficacy into a table which we denote the observation model. We then run the target detection algorithm on a sequence of video frames and use parameters from the observation model to update a recursive Bayesian estimator. The estimator keeps track of the probability that a target is currently in view of the camera, which we refer to more simply as target presence. Between each target detection event the UAV changes position and so the sensing region changes. Under certain assumptions regarding the movement of the UAV, the proportion of new information may be approximated to a value, which we then use to weight the prior in each iteration of the estimator.