Anna Pięta

A Model of a System for Stream Data Storage and Analysis Dedicated to Sensor Networks of Embankment Monitoring

Contemporary monitoring systems are a source of data streams. Processing of this data is an interesting issue from both a performance and data storage perspective. It is worth paying attention to the concept of stream database management systems, which are a hybrid that allows for efficient analysis of the data stream and provide a set of implemented statistical methods.

Analysis of selected component technologies efficiency for parallel and distributed seismic wave field modeling

In this article efficiency of using component-based software for seismic wave field modeling is presented. The most common component solutions like: .NET, Java and Mono were analyzed for various operating systems and hardware platform combinations. Obtained results clearly indicate that the component approach is able to give satisfactory results in this kind of applications, but global solution efficiency can strongly depends on operating system and hardware. The most important conclusion of this work is that for this kind of computations and at this stage of component technology development there are almost no differences between commercial and free platforms.

A Concept of Time Windows Length Selection in Stream Databases in the Context of Sensor Networks Monitoring

Monitoring systems are a source of large amounts of data. These streams of data flow down as information which, in the case of sensor networks is often associated with the measurement of the selected physical signals. Processing of these data is a non-trivial issue, because accurate calculations often require dedicated solutions and large computing power.

The Performance of Geothermal Field Modeling in Distributed Component Environment

An implementation and performance analysis of heat transfer modeling using most popular component environments is a scope of this article. The computational problem is described, and the proposed solution of decomposition for parallelization is shown. The implementation is prepared for MS .NET, Sun Java and Mono. Tests are done for various operating systems and hardware platform combinations. The performance of calculations is experimentally indicated and analyzed. The most interesting issue is the communication tuning in distributed component software – proposed method can speed up computational time, but the final time depends also on the network connections performance in component environments. These results are presented and discussed.

Random Set Method Application to Flood Embankment Stability Modelling

Abstract In this work the application of random set theory to flood embankment stability modelling ispresented. The objective of this paper isto illustrate amethod ofuncertainty analysis in areal geotechnical problem.

COMPARING PARALLEL PROGRAMMING ENVIRONMENTS FOR THE JOINT INVERSION OF GEOELECTRICAL DATA

The article presents the comparison of the implementation of the inverse problem in geoelectricalmethods in two different parallel computational environments. Combination of MonteCarlo method and Multistart algorithm was applied in the inversion process. Parallelizationwas done by fine grain decomposition. Execution time, speed-up and efficiency received forparallel algorithms in both computational environments were presented and analyzed.

Parallel implementation of stochastic inversion of seismic tomography data

In this paper parallel implementation of stochastic inversion of seismic tomography data was presented. Classical approach to travel time tomography assumes straight line of seismic rays between sources and receives points and isotropy of geological medium. Such simplifications are potential sources of inaccuracy of the obtained results of travel time tomography. Stochastic methods can be free from these simplifications. On the other hand, this kind of algorithms requires huge number of time consuming calculations. In this work parallelization of two stochastic methods is presented. Different parallel algorithms was applied to presented inversion problems. Obtained results show significant differences in parallel performance of presented inversion algorithms.

A Proposal of Hybrid Spatial Indexing for Addressing the Measurement Points in Monitoring Sensor Networks

One of the important features of data analysis methods in the area of continuous surveillance systems is a computation time. This article contains a research that is focused on improving the performance of processing by the most efficient possible indexation of spatial data. The authors proposed a structure of indexes implementation based on layered grouping of sensors, so as to reduce the amount of data in time windows. This allows to compare data at the layer-layer level, thereby reducing the problem of comparisons between all sensors.