In this paper, we give new techniques for designing efficient algorithms for computational geometry problems that are too large to be solved in internal memory, and we use these techniques to develop optimal and practical algorithms for a number of important largescale problems. We discuss our algorithms primarily in the contex't of single processor/single disk machines, a domain in which they are not only the first known optimal results but also of tremendous practical value. Our methods also produce the first known optimal algorithms for a wide range of two-level and hierarchical muir{level memory models, including parallel models. The algorithms are optimal both in terms of I/0 cost and internal computation.

With the continued proliferation of wireless networks, e.g., based on such evolving standards as WAP and Bluetooth, visionaries predict that the Internet will soon extend to billions of wireless devices, or objects. A substantial fraction of these will offer their changing positions to the (location-based) services, they either use or support. As a result, software technologies that enable the management of the positions of objects capable of continuous movement are in increasingly high demand. This paper assumes what we consider a realistic Internet-service scenario where objects that have not reported their position within a specified duration of time are expected to no longer be interested in, or of interest to, the service. In this scenario, the possibility of substantial quantities of "expiring" objects introduces a new kind of implicit update, which contributes to rendering the database highly dynamic. The paper presents an R-tree based technique for the indexing of the current positions of such objects. Extensive performance experiments explore the properties of the types of bounding regions that are candidates for being used in the internal entries of the index, and they show that, when compared to the approach where the objects are not assumed to expire, the new indexing technique can improve the search performance by as much as a factor of two or more without sacrificing update performance.

We introduce the area of remote physical device fingerprinting, or fingerprinting a physical device, as opposed to an operating system or class of devices, remotely, and without the fingerprinted device’s known cooperation. We accomplish this goal by exploiting small, microscopic deviations in device hardware: clock skews. Our techniques do not require any modification to the fingerprinted devices. Our techniques report consistent measurements when the measurer is thousands of miles, multiple hops, and tens of milliseconds away from the fingerprinted device, and when the fingerprinted device is connected to the Internet from different locations and via different access technologies. Further, one can apply our passive and semi-passive techniques when the fingerprinted device is behind a NAT or firewall, and also when the device’s system time is maintained via NTP or SNTP. One can use our techniques to obtain information about whether two devices on the Internet, possibly shifted in time or IP addresses, are actually the same physical device. Example applications include: computer forensics; tracking, with some probability, a physical device as it connects to the Internet from different public access points; counting the number of devices behind a NAT even when the devices use constant or random IP IDs; remotely probing a block of addresses to determine if the addresses correspond to virtual hosts, e.g., as part of a virtual honeynet; and unanonymizing anonymized network traces.

: The user's conceptual model of a database system for geometric data should be simple and precise: easy to learn and understand, with clearly defined semantics, expressive: allow to express with ease all desired query and data manipulation tasks, efficiently implementable. To achieve these goals we propose to extend relational database management systems by integrating geometry at all levels: At the conceptual level, relational algebra is extended to include geometric data types and operators. At the implementation level, the wealth of algorithms and data structures for geometric problems developed in the past decade in the field of Computational Geometry is exploited. - The paper starts from a view of relational algebra as a many-sorted algebra which allows to easily embed geometric data types and operators. A concrete algebra for two-dimensional applications is developed. It can be used as a highly expressive retrieval and data manipulation language for geometric as well as standard...

. We use known data structures for ray-shooting and linear-programming queries to derive new output-sensitive results on convex hulls, extreme points, and related problems. We show that the f -face convex hull of an n-point set P in a fixed dimension d # 2 can be constructed in O(n log f + (nf) 1-1/(#d/2#+1) log O(1) n) time; this is optimal if f = O(n 1/#d/2# / log K n) for some sufficiently large constant K . We also show that the h extreme points of P can be computed in O(n log O(1) h + (nh) 1-1/(#d/2#+1) log O(1) n) time. These results are then applied to produce an algorithm that computes the vertices of all the convex layers of P in O(n 2-# ) time for any constant #<2/(#d/2# 2 + 1). Finally, we obtain improved time bounds for other problems including levels in arrangements and linear programming with few violated constraints. In all of our algorithms the input is assumed to be in general position. 1. Introduction Let P be a set of n points in d-dimen...

Let F 3 (n; m) be a random 3-SAT formula formed by selecting uniformly, independently, and with replacement, m clauses among all 8 \Gamma n 3 \Delta possible 3-clauses over n variables. It has been conjectured that there exists a constant r 3 such that for any ffl ? 0, F 3 (n; (r 3 \Gamma ffl)n) is almost surely satisfiable, but F 3 (n; (r 3 + ffl)n) is almost surely unsatisfiable. The best lower bounds for the potential value of r 3 have come from analyzing rather simple extensions of unit-clause propagation. Recently, it was shown [2] that all these extensions can be cast in a common framework and analyzed in a uniform manner by employing differential equations. Here, we determine optimal algorithms expressible in that framework, establishing r 3 ? 3:26. We extend the analysis via differential equations, and make extensive use of a new optimization problem we call "max-density multiple-choice knapsack". The structure of optimal knapsack solutions elegantly characterizes the choi...

The theme of this paper is a rather simple method that has proved very potent in the analysis of the expected performance of various randomized algorithms and data structures in computational geometry. The method can be described as "analyze a randomized algorithm as if it were running backwards in time, from output to input." We apply this type of analysis to a variety of algorithms, old and new, and obtain solutions with optimal or near optimal expected performance for a plethora of problems in computational geometry, such as computing Delaunay triangulations of convex polygons, computing convex hulls of point sets in the plane or in higher dimensions, sorting, intersecting line segments, linear programming with a fixed number of variables, and others. 1 Introduction The curious phenomenon that randomness can be used profitably in the solution of computational tasks has attracted a lot of attention from researchers in recent years. The approach has proved useful in such diverse area...

In this paper, we show that the universal covering space of a surface can be used to unify previous results on computing paths in a simple polygon. We optimize a given path among obstacles in the plane under the Euclidean and link metrics and under polygonal convex distance functions. Besides revealing connections between the minimum paths under these three distance functions, the framework provided by the universal cover leads to simplified linear-time algorithms for shortest path trees, for minimum-link paths in simple polygons, and for paths restricted to c given orientations. 1 Introduction If a wire, a pipe, or a robot must traverse a path among obstacles in the plane, then one might ask what is the best route to take. For the wire, perhaps the shortest distance is best; for the pipe, perhaps the fewest straight-line segments. For the robot, either might be best depending on the relative costs of turning and moving. In this paper, we find shortest paths and shortest closed curve...

We study several variations on one basic approach to the task of simplifying a plane polygon or subdivision: Fatten the given object and construct an approximation inside the fattened region. We investigate fattening by convolving the segments or vertices with disks and attempt to approximate objects with the minimum number of line segments, or with near the minimum, by using efficient greedy algorithms. We give some variants that have linear or O(n log n) algorithms approximating polygonal chains of n segments. We also show that approximating subdivisions and approximating with chains with no self-intersections are NP-hard.

The management of geometric objects is a prime example of an application where efficiency is the bottleneck; this bottleneck cannot be eliminated without using suitable access structures. The most popular approach for handling complex spatial objects in spatial access methods is to use their minimum bounding boxes as a geometric key. Obviously, the rough approximation by bounding boxes provides a fast but inaccurate filter for the set of answers to a query. In order to speed up the query processing by a better approximation quality, we investigate six different types of approximations. Depending on the complexity of the objects and the type of queries, the approximations 5-corner, ellipse and rotated bounding box clearly outperform the bounding box. An important ingredient of our approach is to organize these approximations in efficient spatial access