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In this paper, we propose a dependability evaluation tool for IoT applications, when hardware faults and permanent link faults are considered.
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This paper presents an integrated environment, namely, ASTRO, which contemplates: (i) Reliability Block Diagrams (RBDs), Stochastic Petri Nets (SPN) and continuous-time Markov chains (CTMC) for dependability evaluation; and (ii) a method based on life-cycle assessment (LCA) for quantification of sustainability impact.
Dependability evaluation is an important issue in designing and exploiting embedded systems.
Security, dependability evaluation, security evaluation, performability evaluation, stochastic modeling.
In industry, performing dependability evaluation along with other analyses allows anticipating and making trade-offs.
Dependability evaluation of embedded systems due to the integration of hardware and software parts is difficult to analyze.
However, the dependability evaluation methods that are currently exploited are not appropriate, given the level of complexity of such industrial systems.
Dependability evaluation is crucial to controlling the risks associated with system failure, and for this reason, it is one of the fundamental steps in automated system design.
The justification for using these instruments in safety applications is not fully proven and the dependability evaluation of such systems is not trivial.
It also contains several examples of system dependability evaluation.
MMB & DFT 2014 cover all aspects of performance and dependability evaluation of systems including networks, computer architectures, distributed systems, workflow systems, software, fault-tolerant and secure systems.
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