Multicast tree construction algorithm for dynamic traffic on software defined networks

Dynamic traffic of multicast communication in the Software Defined Network environment focused less though it is more natural and practical. In multicast communication, the traffic is dynamic due to the dynamic group memberships (i.e., participants join and leave the group anytime), which are not explored much in the previous research works. The multicast in dynamic traffic requires a method to handle dynamic group membership and minimum tree alteration for every join and leave of participants from the multicast group. This paper proposes a multicast tree construction algorithm, which considers receiving devices and network capability as base parameters to construct the multicast path. The proposed routing method uses Dijkstra’s Shortest Path algorithm for initial tree formation, identifies a multicast path, and processes the Shortest Path Tree to reduce the overall hop count and path cost. The multicast tree generated by the proposed enables the dynamic join and leaves of participating devices with reduced tree alteration using more common paths to reach the devices. The implementation and results show that the proposed method works efficiently in resource utilization with a reduced hop count and quality for multicast communication in static and dynamic scenarios. Also, the results demonstrate that the proposed method generates a stable common path for multicast communication.

Dynamic Traffic Assignment Model Based on GPS Data and Point of Interest (POI) in Shanghai

Dynamic traffic flow, which can facilitate the efficient operation of traffic road networks, is an important prerequisite for the application of reasonable assignment of traffic demands in an urban road network. In order to improve the accuracy of dynamic traffic flow assignment, this paper proposes a dynamic traffic flow assignment model based on GPS trajectory data and the influence of POI. First, this paper explores the impact patterns of POI on regional road network congestion during peak hours through qualitative and quantitative analysis. Then, based on the user equilibrium theory, a dynamic traffic flow assignment model, in which the effect of POI on links is reflected using the link-node impedance function, is proposed. Finally, the accuracy of the model is validated by the GPS trajectory data and origin–destination (OD) traffic data of motor vehicles in Xuhui District, Shanghai, China. The results show that the model can be used to coordinate and optimize the traffic assignment of the regional road network under the influence of POI during peak hours and alleviate the congestion of the road network. The findings can provide a powerful reference for developing scientific and rational traffic assignment decisions and management strategies for urban road network traffic.

Simulation-Based Dynamic Traffic Assignment with Continuously Distributed Value of Time for Heterogeneous Users

The value of time (VOT) attribute is usually utilized to represent the trade-off between time and monetary expenses in transportation problems. A good representation of VOT is essential for evaluation of any road pricing scheme. Conventionally, in dynamic traffic assignment models, VOT is considered as either constant or finite discrete among travelers because of memory and computational limitations, which in turn could introduce bias in the results. This research explicitly models the individual bi-criteria dynamic user equilibrium (IBDUE) problem and presents a distinct simulation-based solution algorithm that enables individual-based traffic assignment within reasonable run time with a successful implementation of variable and continuously distributed VOT in a simulation-based dynamic traffic assignment package. Numerical analysis reveals that the constant and discrete VOT models tend to overestimate toll road usage compared with the continuous VOT model when the toll charge is low, and underestimate it when the toll charge is high, which reflects previous studies. In the meantime, an experiment on a real-world congestion pricing scheme demonstrates the capability of the proposed algorithm on evaluating flow-dependent pricing schemes.