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TAPAS: a Tool for Stochastic Evaluation of Large Interdependent Composed Models with Absorbing States

Published: 06 June 2022 Publication History

Abstract

TAPAS is a new tool for efficient evaluation of dependability and performability attributes of systems composed of many interconnected components. The tool solves homogeneous continuous time Markov chains described by stochastic automata network models structured in submodels with absorbing states. The measures of interest are defined by a reward structure based on submodels composed through transition-based synchronization. The tool has been conceived in a modular and flexible fashion, to easily accommodate new features. Currently, it implements an array of state-based solvers that addresses the state explosion problem through powerful mathematical techniques, including Kronecker algebra, Tensor Trains and Exponential Sums. A simple, yet representative, case study is adopted, to present the tool and to show the feasibility of the supported methods, in particular frommemory consumption point of view.

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  1. TAPAS: a Tool for Stochastic Evaluation of Large Interdependent Composed Models with Absorbing States

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      cover image ACM SIGMETRICS Performance Evaluation Review
      ACM SIGMETRICS Performance Evaluation Review  Volume 49, Issue 4
      March 2022
      130 pages
      ISSN:0163-5999
      DOI:10.1145/3543146
      Issue’s Table of Contents
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Publication History

      Published: 06 June 2022
      Published in SIGMETRICS Volume 49, Issue 4

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      Author Tags

      1. absorbing states
      2. dependability
      3. performability
      4. state explosion problem
      5. stochastic automata network
      6. stochastic modeling and evaluation

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