A security management scheme for failure detector distributed systems based on self-tuning control theory

Information security management has become an important research issue in distributed systems, and the detection of failures is a fundamental issue for fault tolerance in large distributed systems. Recently, many people have come to realize that failure detection ought to be provided as some form of generic service, similar to IP address lookup. However, this has not been successful so far; one of the reasons being the fact that classical failure detectors were not designed to satisfy several application requirements simultaneously. More specifically, traditional implementations of failure detectors are often tuned for running over local networks and fail to address some important problems found in wide-area distributed systems with a large number of monitored components, such as Grid systems. In this paper, we study the security management scheme for failure detector distributed systems. We first identify some of the most important QoS problems raised in the context of large wide-area distributed systems. Then we present a novel failure detector scheme combined with self-tuning control theory that can help in solving or optimizing some of these problems. Furthermore, this paper discusses the design and analysis of implementing a scalable failure detection service for such large wide-area distributed systems considering dynamically adjusting the heartbeat streams, so that it satisfies the bottleneck router requirements. The basic z-transformation stability test is used to achieve the stability criterion, which ensures the bounded rate allocation without steady state oscillation. We further show how the online failure detector control algorithm can be used to design a controller, analyze the theoretical aspects of the proposed algorithm and verify its agreement with the simulations in the LAN and WAN case. Simulation results show the efficiency of our scheme in terms of high utilization of the bottleneck link, fast response and good stability of the bottleneck router buffer occupancy as well as of the controlled sending rates. In conclusion, the new security management failure detector algorithm provides a better QoS than an algorithm that is proposed by Stelling et al. (Proceedings of 7th IEEE symposium on high performance distributed computing, pp. 268–278, 1998), Foster et al. (Int J Supercomput Appl, 2001).     

A Sketch-Based Interface for Clothing Virtual Characters

This interactive system for garment creation determines a garment's shape and how the character wears it based on a user-drawn sketch. The system then uses distances between the 2D garment silhouette and the character model to infer remaining distance variations in 3D     

The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics

In a competitive business environment, the textile industrialists intend to propose diversified products according to consumers preference. For this purpose, the integration of sensory attributes in the process parameters choice seems to be a useful alternative. This paper provides fuzzy and neural models for the prediction of sensory properties from production parameters of knitted fabrics. The prediction accuracy of these models was evaluated using both the root mean square error (RMSE) and mean relative percent error (MRPE). The results revealed the models ability to predict tactile sensory attributes based on the production parameters. The comparison of the prediction performances showed that the neural models are slightly powerful than the fuzzy models.     

Parallel Training of An Improved Neural Network for Text Categorization

This paper studies parallel training of an improved neural network for text categorization. With the explosive growth on the amount of digital information available on the Internet, text categorization problem has become more and more important, especially when millions of mobile devices are now connecting to the Internet. Improved back-propagation neural network (IBPNN) is an efficient approach for classification problems which overcomes the limitations of traditional BPNN. In this paper, we utilize parallel computing to speedup the neural network training process of IBPNN. The parallel IBNPP algorithm for text categorization is implemented on a Sun Cluster with 34 nodes (processors). The communication time and speedup for the parallel IBPNN versus various number of nodes are studied. Experiments are conducted on various data sets and the results show that the parallel IBPNN together with SVD technique achieves fast computational speed and high text categorization correctness.     

Quantitative analysis of location management and QoS in wireless networks

As a fundamental component in wireless networks, location management consists of two operations: location update and paging. These two supplementary operations enable the mobile user ubiquitous mobility. However, in case of failed location update, a significant consequence is the obsolete location identity in the network databases and thereafter the incapability in establishing the valid route for the potential call connection, which will seriously degrade the network quality-of-service (QoS). This issue is not theoretically studied in the literature. In this paper, we perform a quantitative analysis of the location management effect on QoS in the wireless networks. The metrics call blocking probability and the average number of blocked calls are introduced to reflect the QoS. For the sake of general applicability, the performance metrics are formulated with the relaxed tele-traffic parameters. Namely, the call inter-arrival time, cell residence time, location area residence time and location update inter-arrival time follow a general probability density function. The formulae are additionally specified in the static and several dynamic location management mechanisms. Numerical examples are presented to show the interaction between the performance metrics and location management schemes. The discussions on the sensitivity of tele-parameters are also given.     

Vertical distribution of fauna in the bed sediment of three running water sites: Influence of physical and trophic factors

Relationships between invertebrates, substrate characteristics and trophic factors were investigated, with special emphasis on the hyporheic habitat, in order to characterize the functioning of different running waters ecosystems. Three contrasting study sites were chosen in catchments exhibiting different features: (1) a meandering reach of the Loire River in its alluvial floodplain, upstream of the ‘Bec d'Allier’; (2) a reach of the Galaure with a fairly developed riparian corridor, a small sinuous foothill river; and (3) a braided reach of the Drac, an alpine torrential stream. Each site was sampled once using the freezing-core technique with previous electro-positioning of the invertebrates. In each site, four 60 cm cores were extracted, each one from different morphodynamic units. In the Loire and Galaure rivers, most invertebrates are found in the first 15 cm of the sediment, with the exception of some particular taxa or morphodynamic units (riffle head). Conversely, in the Drac lotic units, maximum density of invertebrates occurs between 15 and 30 cm and more than 75 per cent of all organisms are found at a depth > 15 cm. The vertical distribution of organisms does not follow a uniform pattern in different streams. In the substrate, the vertical distribution of macroinvertebrates is very closely related to porosity in contrast with trophic parameters that always decrease with depth. The porosity is negatively correlated with the percentage of sand in the sediment and seems to be important in determining the vertical distribution of fauna, and should be integrated in a functional typology of running waters. The trophic parameters and the structure of invertebrate community with its dominant feeding groups allow discrimination of the different sites.     

Capture of carbon dioxide by an ion-exchange resin: Influence of gas humidity on capture mechanisms

This paper evaluates moisture content effects on CO₂ capture of an ion-exchange resin (IER) functionalised with a primary amine group. IER capacities were determined by breakthrough with an inlet gas containing 10 vol% CO₂, nitrogen and various moisture contents. Three types of behaviour were identified according to humidity level. In saturated air conditions, the stoichiometry could be justified by carbonates and bicarbonates fixation. In dry conditions, we suspect a joint physical adsorption and reaction mechanism. For intermediate humidity, the stoichiometry of 1 CO₂ for 1 amine group is consistent with a bicarbonate fixation or carbamic acid formation.