Reliability of spare routing via intersectional minimal paths within budget and time constraints by simulation
Yi-Kuei Lin,
Cheng-Fu Huang () and
Chin-Chia Chang
Additional contact information
Yi-Kuei Lin: National Chiao Tung University
Cheng-Fu Huang: Feng Chia University
Chin-Chia Chang: National Taiwan University of Science and Technology
Annals of Operations Research, 2022, vol. 312, issue 1, No 17, 345-368
Abstract:
Abstract 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.
Keywords: Spare routing; Budget; Monte Carlo simulation; Reliability; Intersectional minimal paths (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-020-03923-y
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