Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The major goal of this article was to evaluate the efficiency of Linux operating system using statistical self-similarity and multifractal analysis. In order to collect the necessary data, thetools available in Linux such as vmstat, top and iostat were used. The measurement data collected witht hose tools had to be converted into a format acceptable by applications which analyze statistical selfsimilarity and multifractal spectra. Measurements collected while using the MySQL database systemin a host operating system were therefore analyzed with the use of statistical self-similarity and allowedto determine the occurrence of long-range dependencies. Those dependencies were analyzed with theuse of adequately graduated diagrams. Multifractal analysis was conducted with the help of FracLab application. Two methods were applied to determine the multifractal spectra. The obtained spectra were analyzed in order to establish the multifractal dependencies.
Wydawca
Rocznik
Tom
Strony
65--75
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
- Rzeszów University of Technology, Faculty of Electrical and Computer Engineering, Department of Distributed Systems, u. Wincentego Pola 2, 35-959 Rzeszów, Poland
autor
- Rzeszów University of Technology, Faculty of Electrical and Computer Engineering, Department of Distributed Systems, u. Wincentego Pola 2, 35-959 Rzeszów, Poland
autor
- Rzeszów University of Technology, Faculty of Electrical and Computer Engineering, Department of Distributed Systems, u. Wincentego Pola 2, 35-959 Rzeszów, Poland
Bibliografia
- [1] Strzałka B., Mazurek M., Strzałka D., Queue Performance in Presence of Long-Range Dependencies – an Empirical Study, International Journal of Information Science 2(4) (2012): 47.
- [2] Grabowski F., Strzałka D., Simple, complicated and complex systems – the brief introduction. in: 2008 Confer-ence On Human System Interactions, Vol. 1 and 2 (2008): 576.
- [3] Field A. J., Harder U., Harrison P. G., Measurement and modeling of self-similar traffic in computer network, IEE Proc. Commun. 151(4) (2004).
- [4] Martyn T., Fraktale i obiektowe algorytmy ich wizualizacji. Nakom (1996).
- [5] Dymora P., Mazurek M., Strzałka D., Statistical mechanics of memory pages reads during man–computer system interaction, Metody Informatyki Stosowanej 1(26) (2011).
- [6] Strzałka D., Non-extensive statistical mechanics – a possible basis for modeling processes in computer memory system, Acta Physica Polonica A 117(4) (2010): 652.
- [7] Mazurek M., Dymora P., Network anomaly detection based on the statistical self-similarity factor for HTTP protocol, Przegląd elektrotechniczny, ISSN 0033-2097, R. 90 NR 1/2014 (2014): 127.
- [8] Dymora P., Mazurek M., Strzałka D., Piękoś M., Influence of batch structure on cluster computing perfor-mance - complex systems approach, Annales UMCS Informatica XII (1) (2012).
- [9] Jędruś S., Modelowanie multifraktalne natężenia ruchu sieciowego z uwzględnieniem samopodobieństwa statystycznego, Telekomunikacja cyfrowa – Technologie i Usługi 4 (2001).
- [10] Cheng Q., Agterberg F. P., Multifractal Modeling and Spatial Statistics, Matematical Geology 28(1) (1996).
- [11] Dymora P., Mazurek M., Strzałka D., Long-range dependencies in memory pages reads during man-compute system interaction, Annales UMCS Informatica XII (2) (2012).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6fb9ef56-7897-464f-851e-e618c956c083