首页> 外文会议>Asian International Workshop on Advanced Reliability Modeling >ENHANCING INTERNET NETWORK RELIABILITY BY INTEGRATED FRAMEWORK OF MULTI-OBJECTIVE GENETIC ALGORITHM MONTE CARLO SIMULATION
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ENHANCING INTERNET NETWORK RELIABILITY BY INTEGRATED FRAMEWORK OF MULTI-OBJECTIVE GENETIC ALGORITHM MONTE CARLO SIMULATION

机译:通过多目标遗传算法和蒙特卡罗模拟的综合框架提高互联网网络可靠性

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This paper presents a combined framework of Multi-Objective Generic Algorithm (MOGA)and Monte Carlo Simulation (MCS) in order to improve backbone topology by leveraging the Virtual Link (VL) system in an hierarchical Link-State (LS) routing domain. Given that the sound backbone topology structure has a great impact on the overall routing performance in a hierarchical LS domain, the importance of this research is evident. The proposed decision model is to find an optimal configuration of VLs that properly meets two-pronged engineering goals in installing and maintaining VLs: i.e., operational costs and network reliability. The experiment results clearly indicates that it is essential to the effective operations of hierarchical LS routing domain to consider not only engineering aspects but also specific benefits from systematical layout of VLs, thereby presenting the validity of the decision model and MOGA with MCS.
机译:本文介绍了多目标通用算法(MOGA)和蒙特卡罗模拟(MCS)的组合框架,以便通过利用分层链路状态(LS)路由域中的虚拟链路(VL)系统来改善骨干拓扑。鉴于声骨干拓扑结构对分层LS域中的整体路由性能产生了很大影响,这项研究的重要性是显而易见的。所提出的决策模型是找到vls的最佳配置,可在安装和维护VLS时适当地满足双管齐下的工程目标:即运营成本和网络可靠性。实验结果清楚地表明,对于分层LS路由域的有效操作至关重要,不仅考虑工程方面,而且来自VLS的系统布局的特定益处,从而呈现决策模型和MCS的有效性。

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