Dependability Modeling

Dependability Modeling

Paulo R. M. Maciel (Federated University of Pernambuco, Brazil), Kishor S. Trivedi (Duke University, USA), Rivalino Matias (Federal University of Uberlândia, Brazil) and Dong Seong Kim (Duke University, USA)
DOI: 10.4018/978-1-60960-794-4.ch003
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This chapter presents modeling method and evaluation techniques for computing dependability metrics of systems. The chapter begins providing a summary of seminal works. After presenting the background, the most prominent model types are presented, and the respective methods for computing exact values and bounds. This chapter focuses particularly on non-state space models although state space models such as Markov models and hierarchical models are also presented. Case studies are then presented in the end of the chapter.
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Due to ubiquitous provision of services on the Internet, dependability has become an attribute of prime concern in hardware/software development, deployment, and operation. Providing fault tolerant services is inherently related to adoption of redundancy. Redundancy can be exploited either in time or in space. Replication of services is usually provided through distributed hosts across the world, so that whenever the service, the underlying host or network fails, another service is ready to take over (Gorbenko, A., Kharchenko, A., Romanovsky, A. 2007). Dependability of a system can be understood as the ability to deliver a specified functionality that can be justifiably trusted (Laprie, J. C. 1992). Functionality might be a set of roles or services (functions) observed by an outside agent (a human being, another system etc) that interacts with system at its interfaces; and the specified functionality of a system is what the system is intended for. This chapter aims to provide an overview of dependability modeling. The chapter starts briefly describing some early and seminal work, their motivations and the succeeding advances. Afterwards, a set of fundamental concepts and definitions are introduced. Subsequently, the modeling techniques are classified, defined and introduced as well as a representative set of evaluation methods is presented. Later on, case studies are discussed, modeled and evaluated.

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