Helenos: A realistic benchmark for distributed transactional memory

Transactional memory (TM) is an approach to concurrency control that aims to make writing parallel programs both effective and simple. The approach has been initially proposed for nondistributed multiprocessor systems, but it is gaining popularity in distributed systems to synchronize tasks at large scales. Efficiency and scalability are often the key issues in TM research; thus, performance benchmarks are an important part of it. However, while standard TM benchmarks like the Stanford Transactional Applications for Multi‐Processing suite and STMBench7 are available and widely accepted, they do not translate well into distributed systems. Hence, the set of benchmarks usable with distributed TM systems is very limited, and must be padded with microbenchmarks, whose simplicity and artificial nature often makes them uninformative or misleading. Therefore, this paper introduces Helenos, a realistic, complex, and comprehensive distributed TM benchmark based on the problem of the Facebook inbox, an application of the Cassandra distributed store.     

Language models for detection of unknown attacks in network traffic

In this paper, we propose a method for network intrusion detection based on language models. Our method proceeds by extracting language features such as n-grams and words from connection payloads and applying unsupervised anomaly detection—without prior learning phase or presence of labeled data. The essential part of this procedure is linear-time computation of similarity measures between language models of connection payloads. Particular patterns in these models decisive for differentiation of attacks and normal data can be traced back to attack semantics and utilized for automatic generation of attack signatures. Results of experiments conducted on two datasets of network traffic demonstrate the importance of high-order n-grams and variable-length language models for detection of unknown network attacks. An implementation of our system achieved detection accuracy of over 80% with no false positives on instances of recent remote-to-local attacks in HTTP, FTP and SMTP traffic.     

Two-constraint domain decomposition with Space Filling Curves

In scientific computing, Space Filling Curves are a widely used tool for one-constraint domain decomposition. They provide a mechanism to sort multi-dimensional data in a locality preserving way, and, in this way, a (one dimensional) list of mesh elements is established which is subsequently split into 3 partitions under consideration of the constraint. This procedure has a runtime of O(NlogN) (N is the number of mesh elements) while nearly perfect load balancing can be established with reasonable partition surface sizes.In this work, we discuss the extensibility of this procedure to two-constraint settings which is desirable, since the methodology is extremely fast. Here, the splitting operation is subject to two constraints, and, unlike to the one-constraint case, obtaining near perfect balancing is often hard to establish, and is, even more as in the one-constraint case, in conflict with the induced surface sizes (or edge-cuts). We discuss multiple strategies to tackle the splitting, and we present a fast, O(NlogN) splitting heuristic algorithm which provides an integer σ that allows to trade off between balancing and surface sizes which results in a O(NlogN) two-constraint decomposition method. Results are compared to the multi-constraint domain decomposition abilities implemented in the Metis software package, and show that the method produces higher surface sizes, but is orders of magnitudes faster which makes the method superior for certain applications.     

Patch layout from feature graphs

The structuring of surface meshes is a labor intensive task in reverse engineering. For example, in CAD, scanned triangle meshes must be divided into characteristic/uniform patches to enable conversion into high-level spline surfaces. Typical industrial techniques, like rolling ball blends, are very labor intensive.We provide a novel, robust and quick algorithm for the automatic generation of a patch layout based on a topology consistent feature graph. The graph separates the surface along feature lines into functional and geometric building blocks. Our algorithm then thickens the edges of the feature graph and forms new regions with low varying curvature. Further, these new regions-so-called fillets and node patches-will have highly smooth boundary curves, making the algorithm an ideal preprocessor for a subsequent spline fitting algorithm.     

QuadCover - Surface Parameterization using Branched Coverings

We introduce an algorithm for the automatic computation of global parameterizations on arbitrary simplicial 2-manifolds, whose parameter lines are guided by a given frame field, for example, by principal curvature frames. The parameter lines are globally continuous and allow a remeshing of the surface into quadrilaterals. The algorithm converts a given frame field into a single vector field on a branched covering of the 2-manifold and generates an integrable vector field by a Hodge decomposition on the covering space. Except for an optional smoothing and alignment of the initial frame field, the algorithm is fully automatic and generates high quality quadrilateral meshes.     

Model predictive control of a rotary cement kiln

A first principles model of a cement kiln is used to control and optimize the burning of clinker in the cement production process. The model considers heat transfer between a gas and a feed state via convection and radiation. Furthermore, it contains effects such as chemical reactions, feed transport, energy losses and energy input. A model predictive controller is used to stabilize a temperature profile along the rotary kiln, guarantee good combustion conditions and maximize production. Moving horizon estimation was used for online estimation of selected model parameters and unmeasured states. Results from the pilot site are presented.     

Framework for application management with dynamic aspects J-EARS case study

The cost of computer system maintenance rises together with the increasing complexity of such systems. The use of an autonomic system architecture saves money by delegating some forms of maintenance to the systems themselves. The aim of this paper is to describe the results of creating a tool which introduces elements of adaptivity to Java applications using dynamic aspects. The impact of introducing aspects on the performance of various Application Servers is also discussed. Finally, benefits and problems arising from the use of the tool are presented, basing on sample use cases.     

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