An efficient routing strategy for coupled spatial networks

2021 ◽  
Author(s):  
Xing-Li Jing ◽  
Mao-Bin Hu ◽  
Cong-Ling Shi ◽  
Xiang Ling
Keyword(s):  
Capacity Allocation ◽  
Spatial Networks ◽  
Allocation Strategy ◽  
Traffic Dynamics ◽  
Traffic Characteristics ◽  
Routing Strategy ◽  
Topology Information ◽  
Traffic Systems ◽  
Heterogeneous Node ◽  
Better Than

The study of traffic dynamics on couple networks is important for the design and management of many real systems. In this paper, an efficient routing strategy on coupled spatial networks is proposed, considering both traffic characteristics and network topology information. With the routing strategy, the traffic capacity can be greatly improved in both scenarios of identical and heterogeneous node capacity allocation. Heterogeneous allocation strategy of node delivery capacity performs better than identical capacity allocation strategy. The study can help to improve the performance of real-world multi-modal traffic systems.

Delivering capacity allocation strategy for traffic dynamics on scale-free networks

2019 ◽  
Vol 31 (02) ◽  
pp. 2050029
Author(s):  
Jinlong Ma ◽  
Wei Sui ◽  
Changfeng Du ◽  
Xiangyang Xu ◽  
Guanghua Zhang
Keyword(s):  
Network Capacity ◽  
Capacity Allocation ◽  
Allocation Strategy ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Scale Free ◽  
Optimal Value ◽  
Scale Free Networks ◽  
Resource Allocation Strategy ◽  
Traffic Systems

The traffic dynamics of complex networks are largely determined by the node’s resource distribution. In this paper, based on the shortest path routing strategy, a node delivering capacity distribution mechanism is proposed into the traffic dynamics in Barabási and Albert (BA) scale-free networks; the efficiency of the mechanism on the network capacity measured by the critical point ([Formula: see text]) of phase transition from free flow to congestion is primarily explored. Based on the proposed strategy, the total delivering capacity is reallocated according to both degree and betweenness of each node, and an optimal value of parameter [Formula: see text] is found, leading to the maximum traffic capacity. The results of numerical experiments on scale-free networks suggest that the resource allocation strategy proposed here is capable of effectively enhancing the transmission capacity of networks. Furthermore, this study may provide novel insights into research on networked traffic systems.

Optimal resource allocation strategy for two-layer complex networks

2018 ◽  
Vol 32 (05) ◽  
pp. 1850054 ◽  
Author(s):  
Jinlong Ma ◽  
Lixin Wang ◽  
Sufeng Li ◽  
Congwen Duan ◽  
Yu Liu
Keyword(s):  
Complex Networks ◽  
Service Providers ◽  
Network Capacity ◽  
Capacity Allocation ◽  
Allocation Strategy ◽  
Traffic Dynamics ◽  
Traffic Capacity ◽  
Optimal Value ◽  
Optimal Resource ◽  
Resource Allocation Strategy

We study the traffic dynamics on two-layer complex networks, and focus on its delivery capacity allocation strategy to enhance traffic capacity measured by the critical value [Formula: see text]. With the limited packet-delivering capacity, we propose a delivery capacity allocation strategy which can balance the capacities of non-hub nodes and hub nodes to optimize the data flow. With the optimal value of parameter [Formula: see text], the maximal network capacity is reached because most of the nodes have shared the appropriate delivery capacity by the proposed delivery capacity allocation strategy. Our work will be beneficial to network service providers to design optimal networked traffic dynamics.

An efficient routing strategy on spatial scale-free networks

2014 ◽  
Vol 25 (07) ◽  
pp. 1450017 ◽  
Author(s):  
Xiang-Min Guan ◽  
Xue-Jun Zhang ◽  
Yanbo Zhu ◽  
Inseok Hwang ◽  
Deng-Feng Sun
Keyword(s):  
Spatial Scale ◽  
Euclidean Distance ◽  
Network Capacity ◽  
Traffic Load ◽  
System Throughput ◽  
Traffic Dynamics ◽  
Space Factor ◽  
Scale Free ◽  
Routing Strategy ◽  
Traffic Systems

Traffic dynamics has drawn much more attention recently, but most current research barely considers the space factor, which is of critical importance in many real traffic systems. In this paper, we focus our research on traffic dynamics of a spatial scale-free network with the restriction of bandwidth proportional to link Euclidean distance, and a new routing strategy is proposed with consideration of both Euclidean distance and betweenness centralities (BC) of edges. It is found that compared with the shortest distance path (SDP) strategy and the minimum betweenness centralities (MBC) of links strategy, our strategy under some parameters can effectively balance the traffic load and avoid excessive traveling distance which can improve the spatial network capacity and some system behaviors reflecting transportation efficiency, such as average packets traveling time, average packets waiting time and system throughput, traffic load and so on. Besides, though the restriction of bandwidth can trigger congestion, the proposed routing strategy always has the best performance no matter what bandwidth becomes. These results can provide insights for research on real networked traffic systems.

Improved efficient routing strategy on two-layer complex networks

2016 ◽  
Vol 27 (04) ◽  
pp. 1650044 ◽  
Author(s):  
Jinlong Ma ◽  
Weizhan Han ◽  
Qing Guo ◽  
Shuai Zhang ◽  
Junfang Wang ◽  
...  
Keyword(s):  
Complex Networks ◽  
Research Topic ◽  
Global Awareness ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Transport Efficiency ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Traffic Performance ◽  
Simulation Results

The traffic dynamics of multi-layer networks has become a hot research topic since many networks are comprised of two or more layers of subnetworks. Due to its low traffic capacity, the traditional shortest path routing (SPR) protocol is susceptible to congestion on two-layer complex networks. In this paper, we propose an efficient routing strategy named improved global awareness routing (IGAR) strategy which is based on the betweenness centrality of nodes in the two layers. With the proposed strategy, the routing paths can bypass hub nodes of both layers to enhance the transport efficiency. Simulation results show that the IGAR strategy can bring much better traffic capacity than the SPR and the global awareness routing (GAR) strategies. Because of the significantly improved traffic performance, this study is helpful to alleviate congestion of the two-layer complex networks.

scholarly journals Routing Strategies in Survivable Optical Networks

2013 ◽  
Vol 9 (2) ◽  
pp. 1055-1062
Author(s):  
Ifrah Amin ◽  
Gulzar Ahmad dar ◽  
Hrdeep singh Saini
Keyword(s):  
Optical Networks ◽  
Blocking Probability ◽  
Optical Network ◽  
Routing And Wavelength Assignment ◽  
Wavelength Assignment ◽  
Routing Problem ◽  
Routing Strategy ◽  
Survivable Optical Networks ◽  
Conventional Algorithm ◽  
Better Than

Routing and wavelength assignment problem is one of the main problem in optical networks. The foremost problem is the routing problem after which the wavelength assignment is to be decided. In this paper we have proposed a routing strategy for optimization of the performance of the optical network in terms of blocking probability. The strategy proposed is better than the conventional algorithm in terms of blocking. 

Data-Driven Methods for Detecting Traffic Jams in Vehicular Traffic Systems

2020 ◽  
Author(s):  
Amin Ghadami ◽  
Charles R. Doering ◽  
Bogdan I. Epureanu
Keyword(s):  
Dynamical Systems ◽  
Complex Systems ◽  
Critical Point ◽  
Traffic Flow ◽  
Traffic Dynamics ◽  
Traffic Jams ◽  
Forecasting Methods ◽  
Traffic Flow Management ◽  
Traffic Systems ◽  
Emergent Behaviors

Abstract Ground vehicle traffic jams are a serious issue in today’s society. Despite advances in traffic flow management in recent years, predicting traffic jams is still a challenge. Recently, novel techniques have been developed in complex systems theory to enable forecasting emergent behaviors in dynamical systems. Forecasting methods have been developed based on exploiting the phenomenon of critical slowing down, which occurs in dynamical systems near certain types of bifurcations and phase transitions. Herein, we explore recently developed tools of tipping point forecasting in complex systems, namely early warning indicators and bifurcation forecasting methods, and investigate their application to predict traffic jams on roads. The measurements required for forecasting are recorded dynamical features of the system such as headways between cars in traffic or density of cars on road. Forecasting approaches are applied to simulated and experimental traffic flow conditions. Results show that one can successfully predict proximity to the critical point of congestion as well as traffic dynamics after this critical point using the proposed approaches. The methodologies presented can be used to analyze stability of traffic models and address challenges related to the complexity of traffic dynamics.

Traffic Dynamics Based on Local Routing Strategy in a Weighted Scale-Free Network

2009 ◽  
pp. 733-738
Author(s):  
Mao-Bin Hu ◽  
Yong-Hong Wu ◽  
Rui Jiang ◽  
Qing-Song Wu ◽  
Wen-Xu Wang
Keyword(s):  
Scale Free Network ◽  
Traffic Dynamics ◽  
Scale Free ◽  
Routing Strategy ◽  
Free Network ◽  
Local Routing

An efficient improved routing strategy for multilayer networks

2020 ◽  
pp. 2150078
Author(s):  
Jinlong Ma ◽  
Min Li ◽  
Yaming Li ◽  
Xiangyang Xu ◽  
Weizhan Han ◽  
...  
Keyword(s):  
Multilayer Structure ◽  
High Speed ◽  
Multilayer Networks ◽  
Traffic Dynamics ◽  
The Core ◽  
Transmission Process ◽  
Routing Strategy ◽  
Traffic Capacity ◽  
Average Transmission ◽  
Simulation Results

Traffic dynamics of multilayer networks draws continuous attention from different communities since many systems are actually proved to have a multilayer structure. Since the core nodes of network are prone to congested, an effective routing strategy is of great significance to alleviate the congestion of the multilayer networks. In this paper, we propose an efficient improved routing strategy, with which the core nodes that can reasonably avoid congestion at the high-speed layer in the transmission process of packets, and can also make the most of the traffic resources of the low-speed layer nodes to optimize the traffic capacity of multilayer networks. The simulation results show that the proposed routing strategy can not only improve the network traffic capacity, but also shorten the average path length and average transmission time.

Limited static and dynamic delivering capacity allocations in scale-free networks

2017 ◽  
Vol 28 (11) ◽  
pp. 1750140 ◽  
Author(s):  
N. Ben Haddou ◽  
H. Ez-Zahraouy ◽  
A. Rachadi
Keyword(s):  
Dynamic Properties ◽  
Minimum Cost ◽  
Network Capacity ◽  
Capacity Allocation ◽  
Traffic Information ◽  
Node Degree ◽  
Scale Free ◽  
Routing Strategy ◽  
The Impact ◽  
Allocation Strategies

In traffic networks, it is quite important to assign proper packet delivering capacities to the routers with minimum cost. In this respect, many allocation models based on static and dynamic properties have been proposed. In this paper, we are interested in the impact of limiting the packet delivering capacities already allocated to the routers; each node is assigned a packet delivering capacity limited by the maximal capacity [Formula: see text] of the routers. To study the limitation effect, we use two basic delivering capacity allocation models; static delivering capacity allocation (SDCA) and dynamic delivering capacity allocation (DDCA). In the SDCA, the capacity allocated is proportional to the node degree, and for DDCA, it is proportional to its queue length. We have studied and compared the limitation of both allocation models under the shortest path (SP) routing strategy as well as the efficient path (EP) routing protocol. In the SP case, we noted a similarity in the results; the network capacity increases with increasing [Formula: see text]. For the EP scheme, the network capacity stops increasing for relatively small packet delivering capability limit [Formula: see text] for both allocation strategies. However, it reaches high values under the limited DDCA before the saturation. We also find that in the DDCA case, the network capacity remains constant when the traffic information available to each router was updated after long period times [Formula: see text].

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