In this paper, a novel architecture for a streaming intrusion detection system for Grid computing environments is presented. Detection mechanisms based on traditional log-files or single host databases are replaced by a streaming database approach. The streaming architecture allows processing of temporal attack data across multiple sites and offers the potential for performance benefits in large scale systems, since data is processed during its natural flow and only stored as long as necessary for analysis. Two cross-site example attacks in a Grid environment and the streaming detection logic for these attacks are presented to illustrate the approach. Experimental results of a prototypical implementation are presented.

Static collision checking amounts to testing a given configuration of objects for overlaps. In contrast, the goal of dynamic checking is to determine whether all configurations along a continuous path are collision-free. While there exist effective methods for static collision detection, dynamic checking still lacks methods that are both reliable and efficient. A common approach is to sample paths at some fixed, prespecified resolution and statically test each sampled configuration. But this approach is not guaranteed to detect collision whenever one occurs, and trying to increase its reliability by refining the sampling resolution along the entire path results in slow checking. This paper introduces a new method for testing path segments in c-space or collections of such segments, that is both reliable and efficient. This method locally adjusts the sampling resolution by comparing lower bounds on distances between objects in relative motion with upper bounds on lengths of curves traced by points of these moving objects. Several additional techniques and heuristics increase the checker's efficiency in scenarios with many moving objects (e.g., articulated arms and/or multiple robots) and high geometric complexity. The new method is general, but particularly well suited for use in probabilistic roadmap (PRM) planners, where it is critical to determine as quickly as possible whether given path segments collide, or not. Extensive tests, in particular on randomly generated path segments and on multisegment paths produced by PRM planners, show that the new method compares favorably with a fixed-resolution approach at "suitable" resolution, with the enormous advantage that it never fails to detect collision.

It is shown that structural similarity between proteins can be decided well with much less information than what is used in common similarity measures. The full Cα representation contains redundant information because of the inherent chain topology of proteins and a limit on their compactness due to excluded volume. A wavelet analysis on random chains and proteins justifies approximating subchains by their centers of mass. For not too compact chain-like structures in general, and proteins in particular, similarity measures that use this approximation are highly correlated to the exact similarity measures and are therefore useful, e.g., as fast filters. Experimental results with such simplified similarity measures in two applications, nearest neighbor search and automatic structural classification show a significant speed up.

The kinematic chain is a ubiquitous and extensively studied representation in robotics as well as a useful model for studying the motion of biological macro-molecules. Both fields stand to benefit from algorithms for efficient maintenance and collision detection in such chains. This paper introduces a novel hierarchical representation of a kinematic chain allowing for efficient incremental updates and relative position calculation. A hierarchy of oriented bounding boxes is superimposed on this representation, enabling high performance collision detection, self-collision testing, and distance computation. This representation has immediate applications in the field of molecular biology, for speeding up molecular simulations and studies of folding paths of proteins. It could be instrumental in path planning applications for robots with many degrees of freedom, also known as hyper-redundant robots. A comparison of the performance of the algorithm with the current state of the art in collision detection is presented for a number of benchmarks.

We present an exact and practical incremental method for general translational assembly planning. In practical cases, an exact and complete representation of the relevant free regions in the high-dimensional assembly configuration space becomes amenable by incrementally computing an arrangement of cells in d-dimensional space. Here we introduce a novel reduction scheme, D-node reduction, that allows for online defragmentation of the computed cell decomposition and thus significant speedup and reduction of storage requirements. Experimental results for both two- and three-dimensional assemblies show the practicality of the proposed approach and illustrate the impact of the new reduction scheme.

We address the problem of efficiently determining if the intersection of a given set of d-dimensional halfspaces is unbounded. It is shown that detecting unboundedness can be reduced to a single linear range computation followed by a single linear feasibility test. In contrast, detecting unboundedness is at least as hard as linear feasibility testing and maximization. Our analysis suggests that algorithms for establishing linear unboundedness can be used as a basis of simple and practical algorithms in motion planning, insertability analysis and assembly planning. We show that m-handed assembly planning can be reduced to testing for unboundedness. A valid motion sequence can be computed in polynomial time, if the parts are not already separated in their initial placement. No polynomial algorithms were previously known for this problem. We present experimental results obtained with an implementation of our algorithms.

An exact and practical method for translational motion planning with many degrees of freedom is derived. It it shown that certain D-dimensional arrangements of hyperplanes can be searched in the following way: only a single connected component is traversed during the search, and the arrangement is searched as an arrangement of surface patches rather than full hyperplanes. This reduction in search effort allows for polynomial time bounds in appropriate cases. Heuristic and randomized planners cannot return an information about infeasibility of planning problems. The new method is exact and complete. Experiments obtained with an implementation suggest that it is capable of reaching the performance of the most advanced random planning schemes. In addition, insolvability can be established in practical cases.