Time-dependent analysis of an M / M / c preemptive priority system with two priority classes

Selen, Jori; Fralix, Brian

doi:10.1007/s11134-017-9541-2

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…The earliest studies derive expressions for the marginal distribution of each class, whereas we are interested in the joint distribution of the underlying Markov. More recently, attention has been given to systems with an arbitrary number of priority classes in Sleptchenko et al [102] or to multi-server priority systems in Wang, Baron, Scheller-Wolf [108] and Selen and Fralix [100].…”

Section: Takeawaysmentioning

confidence: 99%

Analysis of structured Markov processes

Adan¹,

Leeuwaarden²,

Selen³

2017

Preprint

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Markov processes are popular mathematical models, studied by theoreticians for their intriguing properties, and applied by practitioners for their flexible structure. With this book we teach how to model and analyze Markov processes. We classify Markov processes based on their structural properties, which in turn determine which analytic methods are required for solving them. In doing so, we start in each chapter with specific examples that naturally lead up to general theory and general methods. In this way the reader learns about Markov processes on the job.By studying this book, the reader becomes acquainted with the basic analytic methods that come into play when systems are modeled as structured Markov processes. These basic methods will likely prove useful, in real-time when studying the examples at hand, but more importantly for future encounters with Markov processes not covered in this book. Methods are more important than examples. The methods have a large scope of application, even outside the scope of Markov processes, in areas like probability theory, industrial engineering, mechanical engineering, physics and financial mathematics.This book arose from various courses taught in the last decade at master level and postgraduate level. We thank the students and colleagues that participated in these courses for their valuable feedback.iii Contents 4 Birth-and-death processes 4.

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Section: Takeawaysmentioning

confidence: 99%

Analysis of structured Markov processes

Adan¹,

Leeuwaarden²,

Selen³

2017

Preprint

Self Cite

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“…Their findings illustrated how well The instantaneous efficacy associated with the curved NHPP predictions forecasting. Within the industry, The prototypes from NHPP still remain in use [5,14]. Three important elements frequently affect software durability estimates: failure diagnosis, troubleshooting, and accessible profile.…”

Section: Introduction-mentioning

confidence: 99%

A Stochastic Analysis Of Computing Models In Computer System Reliability Based On Software

Ashish,

2024

eatp

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BackgroundThe backdrop concentrates on the research and creation of models for software dependability, with an emphasis on the utilization of Non-Homogeneous Poisson Process (NHPP) prototypes to forecast that rate of software malfunction. Software reliability analysis and simulation methodologies are getting better thanks to the efforts of researchers and academics in computer science, software engineering, and related fields. The significance of precise modelling for software reliability in terms of boosting software quality, making the most of testing, and boosting software systems' overall reliability. Software reliability can be anticipated and evaluated using a variety of models and methods, such as failure detection, fault repair techniques, and dependable growth assumptions. ObjectiveIn order to predict and identify software failure rates, the study paper will examine and assess a variety of software reliability models, including stochastic models such as Non-Homogeneous Poisson Process (NHPP) models. The paper's objectives are to examine multiple models in respect to the Theil statistic and performance indicators such as variance, bias, root median square prediction mistake and the mean square mistake. The analysis's findings will show how precise and well-suited the recommended methods are to more normative growth models of software reliability. In order to anticipate software dependability, the study also discusses the construction of multiple change-point extended queueing models that take time delays in fault detection and rectification processes and defect recovery rates into account. Developed throughout the previous three decades, software reliability growth models (SRGMs) are a valuable tool for estimating and forecasting software dependability. The majority of frequent SRGMs seem to think that errors will be corrected immediately. These expectations might not always be realistic or correct in real life. To debug software, programmers need to be able to replicate mistakes, identify their root causes, make the required adjustments, and then run the programme again. It takes time to complete this process. It's possible that the issue's clearance rate fluctuates as well may vary over time and between sites, according to some research or observations. Consequently, we shall look into the subject of how queueing models for mistake detection and correction define software development processes. We introduce an enhanced model for infinite server queuing that features numerous change-points to accurately estimate and assess software stability. The suggested model may be more accurate than traditional SRGMs in capturing the variance in fault rectification rates and influencing software development behaviour, according to empirical results and real failure statistics.

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A new look at a smart polling model

Fralix

2018

Math Meth Oper Res

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Time-dependent analysis of an M / M / c preemptive priority system with two priority classes

Cited by 6 publications

References 23 publications

Analysis of structured Markov processes

Analysis of structured Markov processes

A Stochastic Analysis Of Computing Models In Computer System Reliability Based On Software

A new look at a smart polling model

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