Reliability of spare routing via intersectional minimal paths within budget and time constraints by simulation
Autor: | Yi-Kuei Lin, Cheng Fu Huang, Chin Chia Chang |
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Rok vydání: | 2021 |
Předmět: |
Mathematical optimization
021103 operations research Computer science Reliability (computer networking) 0211 other engineering and technologies Process (computing) General Decision Sciences 02 engineering and technology Management Science and Operations Research Transmission (telecommunications) Spare part Path (graph theory) Transmission time Routing (electronic design automation) Budget constraint |
Zdroj: | Annals of Operations Research. 312:345-368 |
ISSN: | 1572-9338 0254-5330 |
DOI: | 10.1007/s10479-020-03923-y |
Popis: | A stochastic flow network composed of multistate arcs can be utilized to describe several practical systems such as computer networks, where transmission time taken for sending data to a sink is an important index. Determining a path with minimum transmission time is known as the quickest path problem (QPP). All algorithms addressing the QPP assume that the determined minimal paths (MPs) are disjoint. Further, for the general case of intersectional MPs, if a congestion phenomenon occurs during the transmission process, these algorithms will lead to an incorrect outcome. Moreover, in practical scenarios, as a budget limit is considered, spare routing is applied to consolidate the system. The objective is to develop an algorithm based on Monte Carlo simulations (MCSs) for evaluating the system reliability while considering the congestion phenomenon. The system reliability is the probability that a specific amount of data can be transmitted successfully through multiple MPs under both time and budget constraints. Furthermore, spare routing to increase the system reliability is established in advance to specify the main and spare MPs. Experiments validate the evaluation of system reliability based on MCSs. The credibility and efficiency of the proposed algorithm are also discussed. |
Databáze: | OpenAIRE |
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