5,654 research outputs found
Techniques for the Fast Simulation of Models of Highly dependable Systems
With the ever-increasing complexity and requirements of highly dependable systems, their evaluation during design and operation is becoming more crucial. Realistic models of such systems are often not amenable to analysis using conventional analytic or numerical methods. Therefore, analysts and designers turn to simulation to evaluate these models. However, accurate estimation of dependability measures of these models requires that the simulation frequently observes system failures, which are rare events in highly dependable systems. This renders ordinary Simulation impractical for evaluating such systems. To overcome this problem, simulation techniques based on importance sampling have been developed, and are very effective in certain settings. When importance sampling works well, simulation run lengths can be reduced by several orders of magnitude when estimating transient as well as steady-state dependability measures. This paper reviews some of the importance-sampling techniques that have been developed in recent years to estimate dependability measures efficiently in Markov and nonMarkov models of highly dependable system
Formal Availability Analysis using Theorem Proving
Availability analysis is used to assess the possible failures and their
restoration process for a given system. This analysis involves the calculation
of instantaneous and steady-state availabilities of the individual system
components and the usage of this information along with the commonly used
availability modeling techniques, such as Availability Block Diagrams (ABD) and
Fault Trees (FTs) to determine the system-level availability. Traditionally,
availability analyses are conducted using paper-and-pencil methods and
simulation tools but they cannot ascertain absolute correctness due to their
inaccuracy limitations. As a complementary approach, we propose to use the
higher-order-logic theorem prover HOL4 to conduct the availability analysis of
safety-critical systems. For this purpose, we present a higher-order-logic
formalization of instantaneous and steady-state availability, ABD
configurations and generic unavailability FT gates. For illustration purposes,
these formalizations are utilized to conduct formal availability analysis of a
satellite solar array, which is used as the main source of power for the Dong
Fang Hong-3 (DFH-3) satellite.Comment: 16 pages. arXiv admin note: text overlap with arXiv:1505.0264
Impact of SDN Controllers Deployment on Network Availability
Software-defined networking (SDN) promises to improve the programmability and
flexibility of networks, but it may bring also new challenges that need to be
explored. The purpose of this technical report is to assess how the deployment
of the SDN controllers affects the overall availability of SDN. For this, we
have varied the number, homing and location of SDN controllers. A two-level
modelling approach that is used to evaluate the availability of the studied
scenarios. Our results show how network operators can use the approach to find
the optimal cost implied by the connectivity of the SDN control platform by
keeping high levels of availability.Comment: Department of Telematics, NTNU, Tech. Rep., March 201
Rare event simulation for highly dependable systems with fast repairs
Stochastic model checking has been used recently to assess, among others, dependability measures for a variety of systems. However, the employed numerical methods, as, e.g., supported by model checking tools such as PRISM and MRMC, suffer from the state-space explosion problem. The main alternative is statistical model checking, which uses standard simulation, but this performs poorly when small probabilities need to be estimated. Therefore, we propose a method based on importance sampling to speed up the simulation process in cases where the failure probabilities are small due to the high speed of the system's repair units. This setting arises naturally in Markovian models of highly dependable systems. We show that our method compares favourably to standard simulation, to existing importance sampling techniques and to the numerical techniques of PRISM
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