Availability and Reliability Modeling for Computer Systems

doi:10.1016/S0065-2458(08)60154-0

Advances in Computers

Volume 31, 1990, Pages 175-233

https://doi.org/10.1016/S0065-2458(08)60154-0 Get rights and content

Publisher Summary

Dependability calculates the capability of a product to deliver its intended level of service to the user, especially in light of failures or other incidents that impinge on its performance, and combines various underlying ideas, such as reliability, maintainability, availability, and user demand patterns, into a basic overall measure of quality, which customers use along with cost and performance to evaluate products. This chapter describes the computer system dependability analysis and its types, different classes of dependability measures, Markov and Markov reward models commonly involved for dependability analysis and their solution methods. The three classes of dependability measures are system availability measures, system reliability measures, and task completion measures. The chapter also describes four types of dependability analyses: evaluation, sensitivity analysis, specification determination, and tradeoff analysis. A model-based evaluation, or sometimes a hybrid approach based on a judicious combination of models and measurements, is used for cost-effective dependability analysis. The chapter discusses the determination of the parameters, such as failure rates, coverage probabilities, repair rates, and reward rates as well as model verification and validation. The chapter also demonstrates the use of these methods, a detailed dependability analysis on a full-system example representative of existing computer systems.

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Citation Excerpt :
With regards to analytic models, different types can be distinguished depending on the nature of their constitutive elements and solution techniques. The models that are considered in this paper are based on state–space methods due to their flexibility and power in capturing dependence conditions in the system [5–7]. The state–space approach is a very general approach and can handle more cases in dependability and performance modeling than any other analytic method [8].
Quality standards impose increasingly stringent requirements and constraints on quality of service attributes and measures. As a consequence, aspects, phenomena, and behaviors, hitherto approximated or neglected, have to be taken into account in quantitative assessment in order to provide adequate measures satisfying smaller and smaller confidence intervals and tolerances. With specific regards to reliability and availability, this means that interferences and dependencies involving the components of a system can no longer be neglected. Therefore, in order to support such a trend, specific techniques and tools are required to adequately deal with dynamic aspects in reliability and availability assessment.
The main goal of this paper is to demonstrate how state–space based techniques can satisfy such a demand. For this purpose some examples of specific dynamic reliability behaviors, such as common cause failure and load sharing, are considered applying state–space based techniques to study the corresponding reliability models. Different repair policies in availability contexts are also explored. Both Markovian and non-Markovian models are studied via phase type expansion and renewal theory in order to adequately represent and evaluate the considered dynamic reliability aspects in case of generally distributed lifetimes and times to repair.
Availability modeling of energy management systems
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Energy management system (EMS) computer architectures have changed significantly over the recent past increasing the difficulty and the need for a priori assessment of system performance and dependability. The old practice based on measurements is no longer acceptable because of the flexibility accrued with the deployment of the new distributed computer-based systems. The number of “what if” questions increased since EMS systems are now implemented using multiple workstations that can be interconnected in various different ways.
In this paper we show how alternative configurations can be modeled and analyzed, before proposing and purchasing any equipment, with the assistance of Markov reward models. We review the concept of Markov reward models and show how they can be applied in the availability analysis of SCADA/EMS computer systems. The paper also presents a software tool that facilitates automatic generation and solution of large Markov reward models. The input language of this modeling tool uses a variation of stochastic Petri nets called stochastic reward nets, which are also reviewed. We believe this is the first time a detailed quantitative model of a SCADA/EMS computer system is proposed and solved in the general literature.
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Detailed dependability models of various disk array organizations are developed taking into account both the hard disk failures and transient errors. Various error and failure modes of individual disks and the disk array are identified. A small proportion of transient errors account for uncovered failures in a disk array. This leads to analytic computation of probability of disk failures based on several factors including byte error rate of a disk and ECC code etc. Traditionally used measures like MTTDL and data availability remain virtually unchanged with change in mean recovery time. New dependability measures such as degraded capacity time are considered to bring out the effect of mean recovery time on dependability of disk arrays. Our analysis also reveals that mirrored disk organization has higher MTTDL than other disk array organizations if the only failure mode considered is data loss while catastrophic errors are ignored. However, if catastrophic errors are taken into account, then RAID-3,4,5 organizations have higher data-integrity than other disk array schemes. We also develop models that take into account the reliability of support hardware components and different placement schemes for arranging support hardware such as power supply. Our analysis reveals that RAID-1 benefits the most from orthogonal placement of support hardware.
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The need for reduced time to market of new designs has mandated the development of a new generation of computer-aided design tools and design methodologies. The active pursuit of a substantial time reduction in the design process is encompassed in rapid system prototyping. This chapter introduces the field and the disciplines it comprises, and presents extensive examples of research activities in many key disciplines. New technologies, such as field programmable gate arrays, and new methodologies, such as subsystem reusability, are presented. The directions in formalizing the process of system design from specifications through delivery of a functional system are also discussed.
A uniform approach to software and hardware fault tolerance
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In recent years, various attempts have been made to combine software and hardware fault tolerance in critical computer systems. In these systems, software and hardware faults may occur in many different sequences. The problem of how to incorporate these sequences in a fault-tolerant system design has been largely neglected in previous work. In this article, a uniform software-based fault tolerance method is proposed to distinguish and tolerate various sequences of software and hardware faults. This method can be based on the recovery block or the n-version programming scheme, two fundamental software fault tolerance schemes. The concept of fault identification and system reconfiguration tree is proposed to represent the procedure of fault identification and system reconfiguration in a systematic way.
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This paper investigates two mathematical models based on structural computer systems. There are two types of operating environment in computer namely DOS and UNIX. Central Processing Unit (CPU) is the brain of the computer and it guides the monitor and dumb terminal (DT) according to the sequence of instructions as given by operator. A sensitive volume due to micro-chips, exists in the computer. An electromagnetic interfrence with this sensitive volume changes the operating behaviour of computer. These changes generate the partial and complete failure states. Several cost related reliability measures of the system effectiveness are studied by using the regenerative point technique.

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Availability and Reliability Modeling for Computer Systems

Publisher Summary

Computers and Operations Research

European J. Operations Research

Fault Injection for Dependability Validation of Fault-Tolerant Computing Systems

Nineteenth Int. Symp. Fault-Tolerant Computing, Chicago

Statistical Methods in Computer Performance Analysis

Analysis of Typical Fault-Tolerant Architectures Using HARP

IEEE Trans. Reliability

Reliability of Interconnection Networks Using Hierarchical Composition

IEEE Trans. Reliability

Sensitivity Analysis of Reliability and Performability for Multiprocessor Systems

Proc. 1988 ACM SIGMETRICS Conf. Santa Fe, New Mexico

An Aggregation Technique for the Transient Analysis of Stiff Markov Chains

IEEE Trans. Computers

Computation of the Distribution of the Completion Time When the Work Requirement is a PH Random Variable

Stochastic Models

An Approach to Solving Large Reliability Models

1988 IEEE/AIAA DASC Symp., San Diego

Solution of Large GSPN Models

Proc. First Int. Workshop on Numerical Solution of Markov Chains. Raleigh, NC

SPNP Stochastic Petri Net Package

Proc. Third Int. Workshop Petri Nets and Performance Models PNPM

Performability Analysis Using Semi-Markov Reward Processes

IEEE Trans. Computers

Introduction to Stochastic Processes

Monte Carlo Simulation of Computer System Availability/Reliability Models

Proc. Seventeenth Int. Symp. Fault-Tolerant Computing

A Use of Complex Probabilities in the Theory of Stochastic Processes

Proc. Camb. Phil. Soc

Coverage Modeling for Dependability Analysis of Fault-Tolerant Systems

IEEE Trans. Computers

The Hybrid Automated Reliability Predictor

AIAA J. Guid., Control, and Dynamics

Ultra-High Reliability Prediction for Fault-Tolerant Computer Systems

IEEE Trans. Computers

Probabilistic Modeling of Computer System Availability

Annals of Operations Research

The System Availability Estimator

Proc. Sixteenth Int. Symp. Fault-Tolerant Computing

Why Do Computers Stop and What Can Be Done About It?

Proc. Fifth Symp. Reliability in Distributed Software and Database Systems

VAXcluster-System Availability—Measurements and Analysis

A Markov Model for VAXcluster System Availability

IEEE Trans. Reliability

Dynamic Probabilistic Systems, Vol. II: Semi-Markov and Decision Processes

Performability Modeling Based on Real Data: A Case Study

IEEE Trans. Computers

Approximate Availability Analysis of VAXcluster Systems

IEEE Trans. Reliability