As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and...As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and hence has been applicated in edge computing scenarios. In this paper, we propose a reinforced virtual optical network embedding(R-VONE) algorithm based on deep reinforcement learning(DRL) to optimize network embedding policies automatically. The network resource attributes are extracted as the environment state for model training, based on which DRL agent can deduce the node embedding probability. Experimental results indicate that R-VONE presents a significant advantage with lower blocking probability and higher resource utilization.展开更多
以塔式起重机为研究对象,基于先进虚拟仿真软件开发平台EON Professional 6.0的动力学组件实现了虚拟塔吊动力学仿真;提出EON中钢丝绳柔性体建模和仿真方法;构建了一个虚拟施工场景,测试了虚拟塔吊整机动力学仿真效果;建立了塔吊动力学...以塔式起重机为研究对象,基于先进虚拟仿真软件开发平台EON Professional 6.0的动力学组件实现了虚拟塔吊动力学仿真;提出EON中钢丝绳柔性体建模和仿真方法;构建了一个虚拟施工场景,测试了虚拟塔吊整机动力学仿真效果;建立了塔吊动力学分析模型以及相关动力学方程,辅助实现了特殊工况下的钢丝绳摆动以及钢丝绳崩断效果仿真。结果表明:基于EON Professional6.0的动力学组件以及建立辅助动力学方程的虚拟塔吊整机动力学仿真策略和方法是可行的。展开更多
基金supported in part by the National Natural Science Foundation of China(62001422)Henan Scientific and Technology Innovation Talents(22HASTIT016).
文摘As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and hence has been applicated in edge computing scenarios. In this paper, we propose a reinforced virtual optical network embedding(R-VONE) algorithm based on deep reinforcement learning(DRL) to optimize network embedding policies automatically. The network resource attributes are extracted as the environment state for model training, based on which DRL agent can deduce the node embedding probability. Experimental results indicate that R-VONE presents a significant advantage with lower blocking probability and higher resource utilization.
文摘以塔式起重机为研究对象,基于先进虚拟仿真软件开发平台EON Professional 6.0的动力学组件实现了虚拟塔吊动力学仿真;提出EON中钢丝绳柔性体建模和仿真方法;构建了一个虚拟施工场景,测试了虚拟塔吊整机动力学仿真效果;建立了塔吊动力学分析模型以及相关动力学方程,辅助实现了特殊工况下的钢丝绳摆动以及钢丝绳崩断效果仿真。结果表明:基于EON Professional6.0的动力学组件以及建立辅助动力学方程的虚拟塔吊整机动力学仿真策略和方法是可行的。
