This paper focuses on the distribution of passenger flow in Huoying Station,Line 13 of Beijing subway system.The transformation measures taken by Line 13 since operation are firstly summarized.Then the authors elabora...This paper focuses on the distribution of passenger flow in Huoying Station,Line 13 of Beijing subway system.The transformation measures taken by Line 13 since operation are firstly summarized.Then the authors elaborate the facilities and equipment of this station,especially the node layout and passenger flow field.An optimization scheme is proposed to rapidly distribute the passenger flow in Huoying Station by adjusting the operation time of the escalator in the direction of Xizhimen.The authors adopt Queuing theory and Anylogic simulation software to simulate the original and the optimized schemes of Huoying Station to distribute the passenger flow.The results of the simulation indicate that the optimized scheme could effectively alleviate the traffic congestion in the hall of Huoying Station,and the pedestrian density in other places of the hall is lowered;passengers could move freely in the hall and no new congestion points would form.The rationality of the scheme is thus proved.展开更多
Benefited from the design of separating control plane and data plane,software defined networking(SDN)is widely concerned and applied.Its quick response capability to network events with changes in network policies ena...Benefited from the design of separating control plane and data plane,software defined networking(SDN)is widely concerned and applied.Its quick response capability to network events with changes in network policies enables more dynamic management of data center networks.Although the SDN controller architecture is increasingly optimized for swift policy updates,the data plane,especially the prevailing ternary content-addressable memory(TCAM)based flow tables on physical SDN switches,remains unoptimized for fast rule updates,and is gradually becoming the primary bottleneck along the policy update pipeline.In this paper,we present RuleTris,the first SDN update optimization framework that minimizes rule update latency for TCAM-based switches.RuleTris employs the dependency graph(DAG)as the key abstraction to minimize the update latency.RuleTris efficiently obtains the DAGs with novel dependency preserving algorithms that incrementally build rule dependency along with the compilation process.Then,in the guidance of the DAG,RuleTris calculates the TCAM update schedules that minimize TCAM entry moves,which are themain cause of TCAM update inefficiency.In evaluation,RuleTris achieves a median of<12 ms and 90-percentile of<15ms the end-to-end perrule update latency on our hardware prototype,outperforming the state-of-the-art composition compiler CoVisor by～20 times.展开更多
The advent of Big Data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks such as MPI,MapReduce,and Spark.An important step for any parallel clus...The advent of Big Data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks such as MPI,MapReduce,and Spark.An important step for any parallel clustering algorithm is the distribution of data amongst the cluster nodes.This step governs the methodology and performance of the entire algorithm.Researchers typically use random,or a spatial/geometric distribution strategy like kd-tree based partitioning and grid-based partitioning,as per the requirements of the algorithm.However,these strategies are generic and are not tailor-made for any specific parallel clustering algorithm.In this paper,we give a very comprehensive literature survey of MPI-based parallel clustering algorithms with special reference to the specific data distribution strategies they employ.We also propose three new data distribution strategies namely Parameterized Dimensional Split for parallel density-based clustering algorithms like DBSCAN and OPTICS,Cell-Based Dimensional Split for dGridSLINK,which is a grid-based hierarchical clustering algorithm that exhibits efficiency for disjoint spatial distribution,and Projection-Based Split,which is a generic distribution strategy.All of these preserve spatial locality,achieve disjoint partitioning,and ensure good data load balancing.The experimental analysis shows the benefits of using the proposed data distribution strategies for algorithms they are designed for,based on which we give appropriate recommendations for their usage.展开更多
基金This research is supported by Beijing Municipal Natural Science Foundation(9204023)Ministry of Education“Tiancheng Huizhi”Innovation and Education Promotion Foundation(2018A01012).
文摘This paper focuses on the distribution of passenger flow in Huoying Station,Line 13 of Beijing subway system.The transformation measures taken by Line 13 since operation are firstly summarized.Then the authors elaborate the facilities and equipment of this station,especially the node layout and passenger flow field.An optimization scheme is proposed to rapidly distribute the passenger flow in Huoying Station by adjusting the operation time of the escalator in the direction of Xizhimen.The authors adopt Queuing theory and Anylogic simulation software to simulate the original and the optimized schemes of Huoying Station to distribute the passenger flow.The results of the simulation indicate that the optimized scheme could effectively alleviate the traffic congestion in the hall of Huoying Station,and the pedestrian density in other places of the hall is lowered;passengers could move freely in the hall and no new congestion points would form.The rationality of the scheme is thus proved.
基金supported by National Key R&D Program of China under Grant No.2017YFB0801703the Key Research and Development Program of Zhejiang Province under Grant No.2018C01088
文摘Benefited from the design of separating control plane and data plane,software defined networking(SDN)is widely concerned and applied.Its quick response capability to network events with changes in network policies enables more dynamic management of data center networks.Although the SDN controller architecture is increasingly optimized for swift policy updates,the data plane,especially the prevailing ternary content-addressable memory(TCAM)based flow tables on physical SDN switches,remains unoptimized for fast rule updates,and is gradually becoming the primary bottleneck along the policy update pipeline.In this paper,we present RuleTris,the first SDN update optimization framework that minimizes rule update latency for TCAM-based switches.RuleTris employs the dependency graph(DAG)as the key abstraction to minimize the update latency.RuleTris efficiently obtains the DAGs with novel dependency preserving algorithms that incrementally build rule dependency along with the compilation process.Then,in the guidance of the DAG,RuleTris calculates the TCAM update schedules that minimize TCAM entry moves,which are themain cause of TCAM update inefficiency.In evaluation,RuleTris achieves a median of<12 ms and 90-percentile of<15ms the end-to-end perrule update latency on our hardware prototype,outperforming the state-of-the-art composition compiler CoVisor by～20 times.
文摘The advent of Big Data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks such as MPI,MapReduce,and Spark.An important step for any parallel clustering algorithm is the distribution of data amongst the cluster nodes.This step governs the methodology and performance of the entire algorithm.Researchers typically use random,or a spatial/geometric distribution strategy like kd-tree based partitioning and grid-based partitioning,as per the requirements of the algorithm.However,these strategies are generic and are not tailor-made for any specific parallel clustering algorithm.In this paper,we give a very comprehensive literature survey of MPI-based parallel clustering algorithms with special reference to the specific data distribution strategies they employ.We also propose three new data distribution strategies namely Parameterized Dimensional Split for parallel density-based clustering algorithms like DBSCAN and OPTICS,Cell-Based Dimensional Split for dGridSLINK,which is a grid-based hierarchical clustering algorithm that exhibits efficiency for disjoint spatial distribution,and Projection-Based Split,which is a generic distribution strategy.All of these preserve spatial locality,achieve disjoint partitioning,and ensure good data load balancing.The experimental analysis shows the benefits of using the proposed data distribution strategies for algorithms they are designed for,based on which we give appropriate recommendations for their usage.
