arXiv subjects

Rui Jiang

Publications and source records attributed to Rui Jiang.

96 records · Page 6Linked to original sources

arXiv2007

Traffic dynamics of packets generated with non-homogeneously selected sources and destinations in scale-free networks

In this paper, we study traffic dynamics in scale-free networks in which packets are generated with non-homogeneously selected sources and destinations, and forwarded based on the local routing strategy. We consider two situations of packet generation: (i) packets are more likely generated at high-degree nodes; (ii) packets are more likely generated at low-degree nodes. Similarly, we consider two situations of packet destination: (a) packets are more likely to go to high-degree nodes; (b) packets are more likely to go to low-degree nodes. Our simulations show that the network capacity and the optimal value of $α$ corresponding to the maximum network capacity greatly depend on the configuration of packets' sources and destinations. In particular, the capacity is greatly enhanced when most packets travel from low-degree nodes to high-degree nodes.

physics.soc-ph↗

arXiv2006

The effect of bandwidth in scale-free network traffic

We model information traffic on scale-free networks by introducing the bandwidth as the delivering ability of links. We focus on the effects of bandwidth on the packet delivering ability of the traffic system to better understand traffic dynamic in real network systems. Such ability can be measured by a phase transition from free flow to congestion. Two cases of node capacity C are considered, i.e., C=constant and C is proportional to the node's degree. We figured out the decrease of the handling ability of the system together with the movement of the optimal local routing coefficient $α_c$, induced by the restriction of bandwidth. Interestingly, for low bandwidth, the same optimal value of $α_c$ emerges for both cases of node capacity. We investigate the number of packets of each node in the free flow state and provide analytical explanations for the optimal value of $α_c$. Average packets traveling time is also studied. Our study may be useful for evaluating the overall efficiency of networked traffic systems, and for allevating traffic jam in such systems.

physics.soc-ph↗

arXiv2006

Urban Traffic Dynamics: A Scale-Free Network Perspective

This letter propose a new model for characterizing traffic dynamics in scale-free networks. With a replotted road map of cities with roads mapped to vertices and intersections to edges, and introducing the road capacity L and its handling ability at intersections C, the model can be applied to urban traffic system. Simulations give the overall capacity of the traffic system which is quantified by a phase transition from free flow to congestion. Moreover, we report the fundamental diagram of flow against density, in which hysteresis is found, indicating that the system is bistable in a certain range of vehicle density. In addition, the fundamental diagram is significantly different from single-lane traffic model and 2-D BML model with four states: free flow, saturated flow, bistable and jammed.

physics.soc-ph↗

arXiv2006

A Unified Framework for the Pareto Law and Matthew Effect using Scale-Free Networks

We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth $P(m)\sim m^{-(v+1)}$ with $1.6 < v <2.0$ (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.

physics.soc-ph↗

arXiv2005

Analytical investigation of oscillations in intersecting flows of pedestrian and vehicle traffic

In two intersecting many-particle streams, one can often find the emergence of oscillatory patterns. Here, we investigate the interaction of pedestrians with vehicles, when they try to cross a road. A numerical study of this coupled pedestrian-vehicle delay problem has been presented in a previous paper. Here, we focus on the analytical treatment of the problem, which requires to use a simplified car-following model. Our analytical results for the phase transition to oscillatory pedestrian and traffic flows and the average waiting times are well supported by numerical evaluations and give a detailed picture of the collective dynamics emerging when pedestrians try to cross a road. The mathematical expressions allow one to identify the dependence on model parameters such as the vehicle or pedestrian arrival rate, and the safety factor of pedestrian gap acceptance. We also calculate a formula for the vehicle time gap distribution, which corresponds to the departure time distribution of a M/D/1 queue.

physics.soc-ph↗

arXiv2005

Inefficient emergent oscillations in intersecting driven many-particle flows

Oscillatory flow patterns have been observed in many different driven many-particle systems. The conventional assumption is that the reason for emergent oscillations in opposing flows is an increased efficiency (throughput). In this contribution, however, we will study intersecting pedestrian and vehicle flows as an example for inefficient emergent oscillations. In the coupled vehicle-pedestrian delay problem, oscillating pedestrian and vehicle flows form when pedestrians cross the street with a small time gap to approaching cars, while both pedestrians and vehicles benefit, when they keep some overcritical time gap. That is, when the safety time gap of pedestrians is increased, the average delay time of pedestrians decreases and the vehicle flow goes up. This may be interpreted as a slower-is-faster effect. The underlying mechanism of this effect is explained in detail.

cond-mat.stat-mech↗