Reliability SHARPE Reliability and SHARPE

Outline 1. What is Reliability? 2. How can you evaluate it? 3. What is SHARPE? 4. Usage of SHARPE

What is Reliability? how long a system is continuously operational ability to function correctly over a specified period of time

Why is it so important? if system is unreliable, suffer a great loss affect the performance no system is perfect, so we need to evaluate how reliable of it and make improvement

Types of reliability For a computer system, we can define 2 types: Hardware reliability Software reliability

How can you evaluate it? simulation model - program whose execution mimics the dynamic behavior or the modeled system analytic model - Make a mathematical prediction of the system reliability

Simulation Advantages: predict system behavior without having to build and measure a system Disadvantages: time consuming

What is SHARPE? Symbolic Hierarchical Automated Reliability and Performance Evaluator allows users to construct and analyze performance, reliability, availability and performability models

Advantages once set up the model, it can obtain the information easily and quickly easy to carry out sensitivity analysis not time-consuming easy to write the input file

How to use? After building the analytic model, then write a input file for the model input file contains: - state the model type - describe the system - analyze the result

Example Below is the reliability block diagram of a system consisting 8 components: AB C C C D D E

Input file 1 block block1a 2 comp A exp(0.05) 3 comp B exp(0.01) 4 comp C exp(0.3) 5 comp D exp(0.25) 6 comp E exp(0.1) 7 parallel threeC C C C 8 parallel twoD D D 9 series sys1 A B threeC twoD E 10 end cdf(block1a) 13 expr value(10; block1a) 14 end

Analysis After an input file is ready, run the SHARPE and it will produce the result carry out sensitivity analysis by changing different mean to failure rate, you can obtain different combinations of result

How does it link to my research? in my research, SHARPE is used to analyze the reliability of network- centric environment with different combinations of probability function, compared with the traditional computing environment