Accession Number : ADA117653

Title :   Workload, Performance, and Reliability of Digital Computing Systems.

Descriptive Note : Final rept.,

Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE

Personal Author(s) : Castillo,Xavier

PDF Url : ADA117653

Report Date : 01 Dec 1980

Pagination or Media Count : 97

Abstract : In this paper a new modeling methodology to characterize failure processes in Time-Sharing systems due to hardware transients and software errors is summarized. The basic assumption made is that the instantaneous failure rate of a system resource can be approximated by a deterministic function of time plus a zero-mean stationary Gaussian process, both depending on the usage of the resource considered. The probability density function of the time to failure obtained under this assumption has a decreasing hazard function, partially explaining why other decreasing hazard function densities such as the Weibull fit experimental data so well. Furthermore, by considering the Kernel of the Operating System as a system resource, this methodology sets the basis for independent methods of evaluating the contribution of software to system unreliability, and gives some non obvious hints about how system reliability could be improved. A real system has been characterized according to this methodology, and an extremely good fit between predicted and observed behavior has been found. Also, the predicted system behavior according to this methology is compared with the predictions of other models such as the exponential, Weibull, and periodic failure rate. (Author)

Descriptors :   *FAULT TOLERANT COMPUTING, *DIGITAL COMPUTERS, *MATHEMATICAL MODELS, *FAILURE(ELECTRONICS), *WORK MEASUREMENT, TIME SHARING, COMPUTER PROGRAM RELIABILITY, PROBABILITY DENSITY FUNCTIONS, RELIABILITY(ELECTRONICS), METHODOLOGY, ERRORS, COMPARISON, PREDICTIONS, DIGITAL SYSTEMS, STOCHASTIC PROCESSES, WEIBULL DENSITY FUNCTIONS, PERIODIC FUNCTIONS, EXPONENTIAL FUNCTIONS, DETERMINANTS(MATHEMATICS), POISSON DENSITY FUNCTIONS, PARAMETRIC ANALYSIS, AUTOCORRELATION

Subject Categories : Statistics and Probability
      Computer Programming and Software
      Computer Hardware
      Computer Systems

Distribution Statement : APPROVED FOR PUBLIC RELEASE