We study the feasibility and time of communication in random geometric radio networks, where nodes fail randomly with positive correlation. We consider a set of radio stations with the same communication range, distributed in a random uniform way on a unit square region. In order to capture fault dependencies, we introduce the ranged spot model in which damaging events, called spots, occur randomly and independently on the region, causing faults in all nodes located within distance s from them. Node faults within distance 2s become dependent in this model and are positively correlated. We investigate the impact of the spot arrival rate on the feasibility and the time of communication in the fault-free part of the network. We provide an algorithm which broadcasts correctly with probability 1 - ε in faulty random geometric radio networks of diameter D in time O(D + log1/ε).
We present a tradeoff between the expected time for two identical agents to rendez-vous on a synchronous, anonymous, oriented ring and the memory requirements of the agents. In particular, we show that there exists a 2t state agent, which can achieve rendez-vous on an n node ring in expected time O( n 2/2 t ∈+∈2 t ) and that any t/2 state agent requires expected time Ω( n 2/2 t ). As a corollary we observe that Θ(loglogn) bits of memory are necessary and sufficient to achieve rendez-vous in linear time.
We present the first local approximation schemes for maximum independent set and minimum vertex cover in unit disk graphs. In the graph model we assume that each node knows its geographic coordinates in the plane (location aware nodes). Our algorithms are local in the sense that the status of each node v (whether or not v is in the computed set) depends only on the vertices which are a constant number of hops away from v. This constant is independent of the size of the network. We give upper bounds for the constant depending on the desired approximation ratio. We show that the processing time which is necessary in order to compute the status of a single vertex is bounded by a polynomial in the number of vertices which are at most a constant number of vertices away from it. Our algorithms give the best possible approximation ratios for this setting. The technique which we use to obtain the algorithm for vertex cover can also be employed for constructing the first global PTAS for this problem in unit disk graph which does not need the embedding of the graph as part of the input.
Given an integer k ≥ 2, we consider the problem of computing the smallest real number t(k) such that for each set P of points in the plane, there exists a t(k)-spanner for P that has chromatic number at most k. We prove that t(2)∈=∈3, t(3)∈=∈2, , and give upper and lower bounds on t(k) for k∈>∈4. We also show that for any ε>∈0, there exists a (1∈+∈ε)t(k)-spanner for P that has O(|P|) edges and chromatic number at most k. Finally, we consider an on-line variant of the problem where the points of P are given one after another, and the color of a point must be assigned at the moment the point is given. In this setting, we prove that t(2)∈=∈3, , , and give upper and lower bounds on t(k) for k∈>∈4.
Intrusion detection, area coverage and border surveillance are important applications of wireless sensor networks today. They can be (and are being) used to monitor large unprotected areas so as to detect intruders as they cross a border or as they penetrate a protected area. We consider the problem of how to optimally move mobile sensors to the fence (perimeter) of a region delimited by a simple polygon in order to detect intruders from either entering its interior or exiting from it. We discuss several related issues and problems, propose two models, provide algorithms and analyze their optimal mobility behavior.
It is well-known that the greedy algorithm produces high quality spanners and therefore is used in several applications. However, for points in d-dimensional Euclidean space, the greedy algorithm has cubic running time. In this paper we present an algorithm that computes the greedy spanner (spanner computed by the greedy algorithm) for a set of n points from a metric space with bounded doubling dimension in time using space. Since the lower bound for computing such spanners is Ω(n 2), the time complexity of our algorithm is optimal to within a logarithmic factor.
We investigate the problem of locally coloring and constructing special spanners of location aware Unit Disk Graphs (UDGs). First we present a local approximation algorithm for the vertex coloring problem in UDGs which uses at most four times as many colors as required by an optimal solution. Then we look at the colorability of spanners of UDGs. In particular we present a local algorithm for constructing a 4-colorable spanner of a unit disk graph. The output consists of the spanner and the 4-coloring. The computed spanner also has the properties that it is planar, the degree of a vertex in the spanner is at most 5 and the angles between two edges are at least π/3. By enlarging the locality distance (i.e. the size of the neighborhood which a vertex has to explore in order to compute its color) we can ensure the total weight of the spanner to be arbitrarily close to the weight of a minimum spanning tree. We prove that a local algorithm cannot compute a bipartite spanner of a unit disk graph and therefore our algorithm needs at most one color more than any local algorithm for the task requires. Moreover, we prove that there is no local algorithm for 3-coloring UDGs or spanners of UDGs, even if the 3-colorability of the graph (or the spanner respectively) is guaranteed in advance.
The paper proposes to integrate performance analysis in the early phases of the model-driven development process for Software Product Lines (SPL). We start by adding generic performance annotations to the UML model representing the set of core reusable SPL assets. The annotations are generic and use the MARTE Profile recently adopted by OMG. A first model transformation realized in the Atlas Transformation Language (ATL), which is the focus of this paper, derives the UML model of a specific product with concrete MARTE performance annotations from the SPL model. A second transformation generates a Layered Queueing Network performance model for the given product by applying an existing transformation approach named PUMA, developed in previous work. The proposed technique is illustrated with an e-commerce case study that models the commonality and variability in both structural and behavioural SPL views. A product is derived and the performance of two design alternatives is compared.
We present two results for path traversal in trees, where the traversal is performed in an asymptotically optimal number of I/Os and the tree structure is represented succinctly. Our first result is for bottom-up traversal that starts with a node in the tree T and traverses a path to the root. For blocks of size B, a tree on N nodes, and for a path of length K, we design data structures that permit traversal of the bottom-up path in O(K/B) I/Os using only bits, for an arbitrarily selected constant, ε, where 0∈<∈ε<∈1. Our second result is for top-down traversal in binary trees. We store T using (3∈+∈q)N∈+∈o(N) bits, where q is the number of bits required to store a key, while top-down traversal can still be performed in an asymptotically optimal number of I/Os.
Usable security has unique usability challenges because the need for security often means that standard human-computerinteraction approaches cannot be directly applied. An important usability goal for authentication systems is to support users in selecting better passwords, thus increasing security by expanding the effective password space. In click-based graphical passwords, poorly chosen passwords lead to the emergence of hotspots ' portions of the image where users are more likely to select click-points, allowing attackers to mount more successful dictionary attacks. We use persuasion to influence user choice in click-based graphical passwords, encouraging users to select more random, and hence more secure, click-points. Our approach is to introduce persuasion to the Cued Click-Points graphical password scheme (Chiasson, van Oorschot, Biddle, 2007). Our resulting scheme significantly reduces hotspots while still maintaining its usability.
This doctoral thesis presents a complete framework for automated detection of anomalies in clinical thermal IR images. Within that framework, it addresses two fundamental problems: the automated segmentation of a main object from the background; and the automated extraction of relevant, potentially abnormal Regions of Interest. A first segmentation approach called cued morphological processing of edge maps (CMpEm) is introduced, that uses a minimum amount of a priori information about a region to constrain the morphological processing of edge components. It is shown to outperform existing segmentation methods, especially when dealing with faint regions in challenging conditions. A second segmentation approach based on the classification of edge components is presented that is able to recover missing contours when other methods fail. A third segmentation strategy based on a rule-based fusion and morphological post-processing of segmented contours from different techniques is proposed and shown to improve significantly the performance of the global segmentation task. Furthermore, a new approach for automated extraction of anatomical Regions of Interest in clinical IR images is introduced. It is based on a robust landmark identification algorithm that produces more accurate landmark locations on smooth contours than state-of-the-art algorithms. Various aspects of the anomaly detection framework, including blind extraction of potentially abnormal Regions of Interest, are tested on a collection of thermal IR databases acquired in the course of this thesis, in order to demonstrate the key advantages of the framework.