On modelling the performance and reliability of multimode computer systems (original) (raw)
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There are many applications of the computer systems where in the system availability has to be ensured. The evaluation of the availability is very vital before a computer system is being put into operation in such critical applications. In the case of hardware faults, high degree of reliability can be achieved by hardware redundancy. For microprocessor systems good additional feature is fault tolerance. By the use of dedicated customized hardware, fault tolerance can be achieved which is cost effective. A stochastic modeling of the microprocessor based computer system has been carried out and the lifetime availability is estimated. This evaluation is always being during the entire process of system design. The modeling framework used for the Multiprocessor system is based on an extension of Petri nets called Stochastic Activity Networks (SAN). A major contribution of this paper is that a SAN based comprehensive model for computer system using Mobius simulation tool has been developed which can be extensively used for the lifetime evaluation of systems of various architectures and hardware designs.
Reliability modelling for some computer systems
Microelectronics Reliability, 1994
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. software systems and the use of computer to control vital and complicated functions. Several researchers [2,3,4,7] have studied the models related to computer systems and they have analysed the same for reliability and availability only, but not much more. The main aim of present study is to introduce and analyse the computer systems (DOS & UNIX) for reliability more measures. In DOS computer system, there are two compartments drive-C and drive-A. Here it is assumed that drive-C /drive-A may work with reduced efficiency due to minor hardware problem.This state of the system is called partially failed state, from this state it may be attained its original state or it reaches to totally failed state due to major hardware problem.
Advances in systems science and applications, 2018
This paper discusses a unified approach to reliability, availability and performability analysis of complex engineering systems. Theoretical basis of this approach is continuous-time discrete state Markov processes with rewards. From reliability modeling point of view complex systems are the systems with static and dynamic redundancy, imperfect fault coverage, various recovery strategies, multilevel operation and varying severity of failure states. We propose a unified method of calculating the reliability, availability and performability indices based on the definition of special forms of reward matrix. This method proved to be effective in calculating both cumulative and instantaneous measures in steady-state and transient cases. We describe special analytical software which implements suggested method. We demonstrate the flexibility of the proposed method and software by analyzing multilevel process unit with protection and demand-based warm standby system.
The completion time of a job on multimode systems
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In this paper we present a general model of the completion time of a single job on a computer system whose state changes according to a semi-Markov process with possibly infinite state-space. When the state of the system changes the job service is preempted. The job service is then resumed or restarted (with or without resampling) in the new state at, possibly, a different service rate. Different types of preemption disciplines are allowed in the model. Successive aggregation and transform techniques are used to obtain the Laplace–Stieltjes transform of the job completion time. We specialize to the case of Markovian structure-state process. We demonstrate the use of the techniques developed here by means of two applications. In the first we derive the distribution of the response time in an M/M/1 queueing system under the processor-sharing discipline (PS). In the second we derive the distribution of the completion time of a job when executed on a system subject to mixed types of bre...
Stochastic Modelling of a Computer System with Hardware Redundancy
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In this paper, an effort for the stochastic analysis of a computer system has been made considering the idea of hardware redundancy in cold standby. The hardware and software failures occur independently in the computer system with some probability. A single server is employed immediately to conduct hardware repair and software upgradation on need basis. The repair and up-gradation activities performed by the server are perfect. The time to hardware and software failures follows negative exponential distribution, whereas the distributions of hardware repair and software upgradation times are taken as arbitrary with different probability density functions. The expressions for various reliability measures are derived in steady state using semi-Markov process and regenerative point technique. The graphs are drawn for arbitrary values of the parameters to depict the behaviour of some important performance measures of the system model.
The performance and reliability modelling language mosel and its application
International Journal of …, 2003
In this paper we demonstrate the applicability of the new and powerful high-level modelling language MOSEL (MOdeling, Specification and Evaluation Language) using examples from queueing networks with finite capacity, retrial systems, and mobile networks. MOSEL allows the modelling of the functional and temporal behaviour as well as the specification of complex performance and reliability measures of many real-world systems in a straight and simple way. The core of MOSEL consists of a set of constructs to specify the possible states and state changes of the system. Additional syntax is dedicated to the description of the conditions under which transitions are allowed or prohibited. In order to model the temporal behaviour of the system properly, possible state changes can either occur immediately or after an exponentially distributed delay. In contrast to many specification languages of existing performance modelling and analysis tools, which often tend to be too verbose, most MOSEL specifications are compact but anyhow easy to understand. Moreover, MOSEL provides means by which many interesting performance or reliability measures and the graphical presentation of them can be specified straightforwardly. It is especially easy to analyse a model with different sets of system parameters. The benefit of MOSEL-especially for the practitioner from the industry-lies in its modelling environment: A MOSEL model is automatically translated into various tool-specific system descriptions and then analyzed by the appropriate tools. This exempts the modeller from the time-consuming task of learning different modelling languages. The presented examples originate from different application areas: First, we investigate models of queueing networks with finite capacity which are very important in the performance modelling of computer and manufacturing systems. Then we model a retrial system, which for example is suitable to describe the situation at airports when aircrafts are waiting for landing permission. Next, we specify a reliability model for a multiprocessor system. As a fourth example we present a model of a real system from wireless communications: The call admission control protocol in a Third Generation (3G) wireless mobile network. In all examples, the interesting performance and reliability measures are calculated after a Continuous Time Markov Chain (the underlying stochastic process of the MOSEL model) has automatically been generated and solved by standard numerical solution methods. The graphical representations of these results were created by the utility IGL (Intermediate Graphical Language) which is part of the MOSEL modelling environment.
Sensitivity Analysis of Reliability and Performability Measures for Multiprocessor Systems
Sigmetrics Performance Evaluation Review, 1988
Traditional evaluation techniques for multiprocessor systems use Markov chains and Markov reward models to compute measures such as mean time to failure, reliability, performance, and performability. In this paper, we discuss the extension of Markov models to include parametric sensitivity analysis. Using such analysis, we can guide system optimization, identify parts of a system model sensitive to error, and find system reliability and performability bottlenecks.