This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.

/pdf/basic-concepts-and-taxonomy-of-dependable-and-secure-4u8aflogtd.pdf

Basic concepts and taxonomy of dependable and secure computing

Basic Concepts and Taxonomy of Dependable and Secure Computing

1. Introduction 2. Background 3. Performance evaluation process algebra 4. Modelling study: multi-server multi-queue systems 5. Notions of equivalence 6. Isomorphism and weak isomorphism 7. Strong bisimilarity 8. Strong equivalence 9. Conclusions Bibliography Index.

/pdf/a-compositional-approach-to-performance-modelling-4ybheka1a7.pdf

A Compositional Approach to Performance Modelling

If the performance of a computing system is "degradable," performance and reliability issues must be dealt with simultaneously in the process of evaluating system effectiveness. For this purpose, a unified measure, called "performability," is introduced and the foundations of performability modeling and evaluation are established. A critical step in the modeling process is the introduction of a "capability function" which relates low-level system behavior to user-oriented performance levels. A hierarchical modeling scheme is used to formulate the capability function and capability is used, in turn, to evaluate performability. These techniques are then illustrated for a specific application: the performability evaluation of an aircraft computer in the environment of an air transport mission.

On Evaluating the Performability of Degradable Computing Systems

SPNP, a powerful GSPN package that allows the modeling of complex system behaviors, is presented. Advanced constructs are available in SPNP such as marking-dependent arc multiplicities, enabling functions, arrays of places or transitions, and subnets; the full expressive power of the C programming language is also available to increase the flexibility of the net description. Sophisticated steady-state and transient solvers are available including cumulative and up-to-absorption measures. The user is not limited to a predefined set of measures; detailed expressions reflecting exactly the measures sought can be easily specified. The authors conclude by comparing SPNP with two other SPN-based packages, Great SPN and METASAN. >

SPNP: stochastic Petri net package

Performability modeling and evaluation methods are applied to the SIFT computer in the computational environment of an air transport mission. User-visible performance of the "total system" (SIFT plus its environment) is modeled as a random variable taking values in a set of "accomplishment levels." These levels are defined in terms of four attributes of total system behavior: safety, no change in mission profile, no operational penalties, and no economic penalties. The "base model" of the total system is a stochastic process whose states describe the internal structure of SIFT as well as relevant conditions of its environment. Base model state trajectories are related to accomplishment levels via a "capability function" which is formulated in terms of a three-level model hierarchy. Solution methods are then applied to determine the performability of the total system for various choices of computer and environment parameter values.

/pdf/performability-evaluation-of-the-sift-computer-2qnf7ttw1i.pdf

Performability Evaluation of the SIFT Computer

An algorithm is developed for solving a broad class of performability models wherein system performance is identified with "reward." More precisely, for a system S and a utilization period T, the performance variable of the model is the reward derived from using S during T. The state behavior of S is represented by a finite-state stochastic process (the base model); reward is determined by reward rates associated with the states of the base model. Restrictions on the base model assume that the system in question is not repaired during utilization. It is also assumed that the corresponding reward model is a nonrecoverable process in the sense that a future state (reward rate) of the model cannot be greater than the present state. For this model class, we obtain a general method for determining the probability distribution function of the performance (reward) variable and, hence the performability of the corresponding system. Moreover, this is done for bounded utilization periods. The result is an integral expression which can be solved either analytically or numerically.

A Performability Solution Method for Degradable Nonrepairable Systems

A reliability analysis method for computing systems is considered in which the underlying criteria for "success" are based on the computations the system must perform in the use environment. Beginning with a general model of a "computer with faults," intermediate concepts of a "tolerance relation" and an "environment space" are introduced which account for the computational needs of the user and the probabilistic nature of the use environment. These concepts are then incorporated to obtain a precisely defined class of computation-based reliability measures. Formulation of a particular measure is illustrated and results, applying this measure, are compared with those of a typical structure-based analysis.

/pdf/computation-based-reliability-analysis-3l2c2prykc.pdf

Computation-Based Reliability Analysis

If computing system performance is degradable, then as recognized in a number of recent studies, system evaluation must deal simultaneously with aspects of both performance and reliability. One approach is the evaluation of a system's "performability," which relative to a specified performance variable Y, generally requires solution of the probability distribution function of Y. In this paper we examine the feasibility of closed-form solutions of performability when Y is continuous. In particular, we consider the modeling of a degradable buffer/multiprocessor system whose performance Y is the (normalized) average throughput rate realized during a bounded interval of time. Employing an approximate decomposition of the model, we show that a closed-form solution can indeed be obtained.

/pdf/closed-form-solutions-of-performability-4njf2tvug6.pdf

Closed-Form Solutions of Performability

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