Fractal Analysis of Resource Exhaustion in Real Time perating 资源枯竭的实时操作的分形分析.pptVIP

Software aging phenomenon “Software aging phenomenon implies that the state of the software system degrades with time. The degradation manifests itself in performance decline (excessive paging and swapping activity etc.), possibly leading to crash/hang failures or both. Degradation is caused, in particular, by the exhaustion of the operating system resources, such as the number of unused memory pages, the number of disk blocks available for page swapping, etc. Earlier studies of resource exhaustion Vaidyanathan and Trivedi describe the behavior of operating system recourses as a function of time Slope (trend) depends on the workload state of the system, Workload dynamics is modeled as semi-Markov process. However, in many workload states the dynamics of the resources demonstrates very high variance resulting in very broad confidence intervals. The highly irregular and oscillatory behavior of the data makes any linear trend model insufficient. Our research objectives Investigate correlation between fractal properties of the resource data and the system’s workload Develop fractal-based model of the resource exhaustion process Apply it to real-time operating systems. Investigate possibility of using such model for predicting system outages and for preventive maintenance planning Data collection Fractal signals: theory Most popularly known fractals are two-dimensional “beautiful pictures” (Mandelbrot, Julia sets Koch snowflake, Serpinski triangle, “ferns” etc.) exhibiting complex structure at every scale and self-similarity: zoom any fragment of it with any resolution and get a picture which resembles the whole set. Functions may also be fractal, i.e. have fractal graphs. Such functions are non-smooth, do not have a derivative at any point. Example of fractal function Weierstrass function: , a = 0.5, b = 3. Fractal signals: applications The study of fractal functions (i.e. those whose plots exhibit fractal properties)