A simulation approach with heuristic rules for reliability estimation of two-terminal multi-state networks based on minimal cuts and parallel computations
IF 3.5 2区 计算机科学Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0
Abstract
Both the system reliability and the resilience evaluation of multi-state flow networks (MFNs) play a crucial role in designing and analyzing these networks. The system reliability at level is the probability of successfully transmitting at least units of flow. In turn, system resilience allows us to analyze the ability of systems to withstand and bounce back from disruptive events. The paper presents a new simulation approach based on minimal cuts (MCs) and parallel computations to compute the system reliability for all possible non-integer levels. An extension with a time attribute is also considered to investigate the reliability degradation with time. Moreover, it also introduces a novel heuristic that for a given integer and a state vector , finds an MC for which the capacity under the system state is the smallest among MCs containing some of coordinates of with the smallest capacities. It is also shown how this approach can be used to compute the network resilience at a given time and the system integrated resilience metric is introduced. Numerical experiments are conducted to demonstrate the efficiency and advantages of the presented algorithm.
期刊介绍:
The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling.
The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas.
Paper submission is solicited on:
• theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.;
• methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.;
• simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.;
• distributed and real-time simulation, simulation interoperability;
• tools for high performance computing simulation, including dedicated architectures and parallel computing.