本文致力于提高非协作方式下IPv6接入网络拓扑发现的覆盖率,首先建立了描述IPv6接入网络的前缀聚合树模型(PATM,Prefix Aggregation Tree Model),然后提出了基于PATM模型的网络拓扑发现方法。最后给出了对华东某高校IPv6校园网的拓扑发...本文致力于提高非协作方式下IPv6接入网络拓扑发现的覆盖率,首先建立了描述IPv6接入网络的前缀聚合树模型(PATM,Prefix Aggregation Tree Model),然后提出了基于PATM模型的网络拓扑发现方法。最后给出了对华东某高校IPv6校园网的拓扑发现测试结果。通过对测试数据进行的分析和对比,验证了基于PATM模型的拓扑发现方法的有效性。展开更多
The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system.By analyzing the impact of the pandemic on the transportation system,the impact of the pandemic on the social ...The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system.By analyzing the impact of the pandemic on the transportation system,the impact of the pandemic on the social economy can be reflected to a certain extent,and the effect of anti-pandemic policy implementation can also be evaluated.In addition,the analysis results are expected to provide support for policy optimization.Currently,most of the relevant studies analyze the impact of the pandemic on the overall transportation system from the macro perspective,while few studies quantitatively analyze the impact of the pandemic on individual spatiotemporal travel behavior.Based on the license plate recognition(LPR)data,this paper analyzes the spatiotemporal travel patterns of travelers in each stage of the pandemic progress,quantifies the change of travelers'spatiotemporal behaviors,and analyzes the adjustment of travelers'behaviors under the influence of the pandemic.There are three different behavior adjustment strategies under the influence of the pandemic,and the behavior adjustment is related to the individual's past travel habits.The paper quantitatively assesses the impact of the COVID-19 pandemic on individual travel behavior.And the method proposed in this paper can be used to quantitatively assess the impact of any long-term emergency on individual micro travel behavior.展开更多
文摘本文致力于提高非协作方式下IPv6接入网络拓扑发现的覆盖率,首先建立了描述IPv6接入网络的前缀聚合树模型(PATM,Prefix Aggregation Tree Model),然后提出了基于PATM模型的网络拓扑发现方法。最后给出了对华东某高校IPv6校园网的拓扑发现测试结果。通过对测试数据进行的分析和对比,验证了基于PATM模型的拓扑发现方法的有效性。
基金supported by“Pioneer”and“Leading Goose”R&D Program of Zhejiang(2022C01042)the National Natural Science Foundation of China(Grant No.92046011)+1 种基金Center for Balance Architecture Zhejiang UniversityAlibaba-Zhejiang University Joint Research Institute of Frontier Technologies.
文摘The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system.By analyzing the impact of the pandemic on the transportation system,the impact of the pandemic on the social economy can be reflected to a certain extent,and the effect of anti-pandemic policy implementation can also be evaluated.In addition,the analysis results are expected to provide support for policy optimization.Currently,most of the relevant studies analyze the impact of the pandemic on the overall transportation system from the macro perspective,while few studies quantitatively analyze the impact of the pandemic on individual spatiotemporal travel behavior.Based on the license plate recognition(LPR)data,this paper analyzes the spatiotemporal travel patterns of travelers in each stage of the pandemic progress,quantifies the change of travelers'spatiotemporal behaviors,and analyzes the adjustment of travelers'behaviors under the influence of the pandemic.There are three different behavior adjustment strategies under the influence of the pandemic,and the behavior adjustment is related to the individual's past travel habits.The paper quantitatively assesses the impact of the COVID-19 pandemic on individual travel behavior.And the method proposed in this paper can be used to quantitatively assess the impact of any long-term emergency on individual micro travel behavior.
