Wireless backbone networks represent an attractive alternative to wired networks in situations where cost, speed of deployment, and flexibility in network design are important. In typical configurations, users connect to wireless routers of the backbone network, which then redirect the traffic to one of the existing network gateways. To improve the network performance, wireless backbone routers redirect their traffic to the network gateways so as to maximize amount of traffic that can be supported by the network. In this paper, we prove that this problem is NP-hard as a result of the wireless interference that is created between geographically close transmission links. We consequently design and investigate the performance of interference-aware algorithms suitable for multi-channel environments against more traditional routing approaches. We evaluate their performance in simulated environments based on data taken from existing networks, and show that interference-based heuristics exhibit advantageous performance in non-uniform deployment.

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. Through a series of experiments we show how the value of the prior for unseen regions, the altitude of the UAV and the camera sampling rate affect the accuracy of the estimator. Our results indicate that there is no single optimal sampling rate for all tested scenarios. We also show how the prior may be used as a mechanism for tuning the estimator according to whether a high false positive or high false negative probability is preferable.

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.

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.

Multihop wireless mesh networks are an attractive solution for providing last-mile connectivity. However, the shared nature of the transmission medium makes it challenging to fully exploit these networks. In an attempt to improve the radio resource utilization, several muting metrics have been specifically designed for wireless mesh networks. However, although some evaluations have been conducted to assess the performance of these metrics in some contrived scenarios, no overall comparison has been performed. We therefore studied the performance of the most popular routing metrics currently used in wireless mesh networks; Hop Count, Blocking Metric, Expected Tran- mission Count (ETX), Expected Transmission Tune (ETT), Modified ETX (mETX), Network Allocation Vector Count (NAVC) and Metric of Inteiference and Channel-Switching (MIC). We showed under various simulation scenarios that although all the metrics except NAVC offer the same end- to-end delay and packet loss ratio, differences can he distinguished in terms of traffic load repartition. In particular, the congestion-avoidance strategies of ETX, mETX, and MIC prevent the starvation of flows following longer paths and consequently provide a more uniform traffic repartition.

Multihop wireless mesh networks are an attractive solution for providing last-mile connectivity. However, the shared nature of the transmission medium makes it challenging to fully exploit these networks. Nodes interfere with each other, resulting in packet loss and degraded network performance. In this paper, a routing metric specifically designed for WMNs is proposed. The Interference-Aware Routing metric (IAR) uses MAC-level information to measure the share of the channel that each link is able to utilize effectively. As a result, paths are selected that exhibit the least interference. Simulations show that utilizing this metric provides significant performance improvements in terms of end-to-end delay compared to several existing metrics.

Users' demand of seamless connectivity has pushed for the development of alternatives to traditional infrastructure networks. Potential solutions should be low-cost, easily deployable and adaptive to the environment. One approach that has gained tremendous attention over the past few years consists in deploying a backbone of access points wirelessly interconnected, offering users access to the wired infrastructure via multi-hop communication. However, the limited transfer capacities and the interference resulting from a shared transmission medium can prevent further deployment if the network performance does not meet users' expectations. In this work, we explore different ways to improve the nominal network capacity while accounting for the phenomena of intra-interference (interference on a single path) and inter-interference (interference among flows on different paths). In particular, under the assumptions of splitable traffic flows, we present an interference-aware linear- programming formulation of the min-max congestion problem with and without constraints on the path length. Finally, we evaluate via simulations the potential bandwidth capacity gain resulting from the implementation of these different approaches.

Spreading traffic over multiple paths has been shown to enhance network performance compared to single path routing. However, the route coupling effect specific to wireless environments (consequent to the shared transmission medium) can significantly reduce the benefits of such an approach. In this paper, we focus on the 2-path routing problem in a non-mobile and non energy-constrained network. We evaluate the network performance and the effect of interference in a single source-destination pair scenario and for multiple source-destinations pairs. In the former case, we provide an analytical evaluation of the throughput and propose a position-based algorithm to iteratively find a path between a source and a destination. In the latter case, we demonstrate how interference can significantly degrade the nominal network capacity and void the benefits of multipath routing.