Narrow Results

Congestion in communication networks is a topic of theoretical interest and practical importance. In this work, we propose a mixed routing strategy by considering the global static information (topology of the network) and local dynamic information (queue length of neighbor nodes). Under this routing strategy, the traffic capacity can be remarkably promoted compared with that by former efficient routing strategy [G. Yan et al., Phys. Rev. E73, 046108 (2006)]. Besides, the traffic capacity, the average packet number as well as the travel time are almost independent of a time delay in updating the local dynamic information.

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.

The link congestion based traffic model can more accurately reveal the traffic dynamics of many real complex networks such as the Internet, and heuristically optimizing each link's weight for the shortest path routing strategy can strongly improve the traffic capacity of network. In this work, we propose an optimal routing strategy in which the weight of each link is regulated incrementally to enhance the network traffic capacity by minimizing the maximum link betweenness of any link in the network. We also estimate more suitable value of the tunable parameter β for the efficient routing strategy under the link congestion based traffic model. The traffic load of network can be significantly balanced at the expense of increasing a bit average path length or average traffic load.

Global static routing is one kind of important routing algorithms for complex networks, especially in large communication networks. In this paper, we propose a heuristic global static routing algorithm to mitigate traffic congestion on two-layer complex networks. The proposed routing algorithm extends the relevant static weighted routing algorithm in the literature [Y. Zhou, Y. F. Peng, X. L. Yang and K. P. Long, Phys. Sci.84, 055802 (2011)]. Our routing path is constructed from a proper assignment of edge weights by considering the static information of both layers and an adjustable parameter α. When this routing algorithm is adopted on BA–BA two-layer networks with an appropriate parameter α, it can achieve the maximum network traffic capacity compared with the shortest path (SP) routing algorithm and the static weighted routing algorithm.

As the cascading failures in networked traffic systems are becoming more and more serious, research on cascade defense in complex networks has become a hotspot in recent years. In this paper, we propose a traffic-based cascading failure model, in which each packet in the network has its own source and destination. When cascade is triggered, packets will be redistributed according to a given routing strategy. Here, a global hybrid (GH) routing strategy, which uses the dynamic information of the queue length and the static information of nodes' degree, is proposed to defense the network cascade. Comparing GH strategy with the shortest path (SP) routing, efficient routing (ER) and global dynamic (GD) routing strategies, we found that GH strategy is more effective than other routing strategies in improving the network robustness against cascading failures. Our work provides insight into the robustness of networked traffic systems.

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.

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

To improve the traffic capacity of scale-free networks, we propose an improved local efficient routing (ILER) strategy based on node degree and network constraint index (NCI). NCI describes how closely a node is maintained directly or indirectly with other nodes, and it only considers the relationship between nodes and their neighbors, not the topology of the network. Both the node degree and NCI are a parameter to describe the importance of nodes, and the combination of the two can make up for their own shortcomings, making it particularly important. Under the ILER strategy, packets can bypass some central nodes in the network for transmission, so that the central nodes in the network are not prone to congestion, thereby increasing the network traffic capacity. Through simulation comparison, the network traffic capacity under ILER strategy is significantly higher than that under probability routing (PR) strategy and efficient routing (ER) strategy. Under the ILER strategy, the average path length (APL) of the network is also shorter than that under the PR and ER strategies. In addition, whether target attack or random attack, the network has strong robustness under ILER strategy.

We propose a new routing strategy for controlling packet routing on complex networks. The delivery capability of each node is adopted as a piece of local information to be integrated with the load traffic dynamics to weight the next route. The efficiency of transport on complex network is measured by the network capacity, which is enhanced by distributing the traffic load over the whole network while nodes with high handling ability bear relative heavier traffic burden. By avoiding the packets through hubs and selecting next routes optimally, most travel times become shorter. The simulation results show that the new strategy is not only effective for scale-free networks but also for mixed networks in realistic networks.

Using the theories of complex networks and gravitational field, we study the dynamic routing process under the framework of node gravitational field, define the equation of gravitation of travel path to data package and introduce two parameters α and γ for adjusting the dependences of transmission data on the unblocked degree of node, the transmission capacity of node and the path length. Based on the path's attraction, a gravitational field routing strategy under node connection ability constraint is proposed with considering the affect of node aggregation ability to transport process, and a parameter is used to adjust the control strength of routing process to node aggregation ability. In order to clarify the efficiency of suggested method, we introduce an order parameter η to measure the throughput of the network by the critical value of phase transition from free state to congestion state, and analyze the distribution of betweenness centrality and traffic jam. Simulation results show that, compared with the traditional shortest path routing strategy, our method greatly improve the throughput of a network, balance the network traffic load and most of the network nodes are used efficiently. Moreover, the network throughput is maximized under μ = -1, and the transmission performance of the algorithm is independent of the values of α and γ, which indicate the routing strategy is stable and reliable.

The real throughput of a network is dependent on the adopted routing algorithm. In this study, we further analyze the influence of real-time traffic condition and travel distance on network throughput in a dynamic transportation environment, and define a mathematical model to describe the routing cost for a packet spending to travel along a path with considering real-time traffic condition and travel distance. Based on the model, this paper proposes a routing strategy by imposing the minimum cost. Experimental results show that the proposed routing strategy is efficient in improving network throughput and balancing traffic load.

The escalation of network traffic drives it imperative to enhance network traffic capacity and alleviate congestion. We propose a novel routing strategy in accordance with the properties of sine function. In simulation experiments, our strategy is compared with the efficient routing (ER) strategy. The phase change point of network from free state to congestion state can accurately define network traffic capacity. By using the optimal parameter of our strategy, the traffic capacity of network can be enhanced and the average path length can be reduced under each network size. What’s more, load variance and total load under our strategy are lower, which indicates that the total load is smaller and the load distribution is more uniform when compared to the case of ER strategy.

Networks, acting as infrastructure for information communication, play an important role in modern society, therefore, the elements affecting the efficiency of network traffic are worthy of deep research. In this paper, we investigate numerically the problem of traffic congestion in complex networks through the use of various routing strategies. Three types of complex networks structures, namely Poisson random networks, small-world networks and scale-free networks, are considered. Three different routing strategies are used on networks: deterministic routing strategy, preferential routing strategy and shortest path routing strategy. We evaluate the efficiency of different routing strategies on different network topologies and show how the network structures and routing strategies influence the traffic congestion status.

With the development of information technology, networks become a crucial part in modern society. Therefore, the improvement in routing strategy of networks is of great importance and significance. For the purpose of improving the efficiency of network traffic, we propose a new routing strategy with two tunable parameters based on local information of network. In our strategy, we include the static information, node degree, and dynamic information, buffer queue length, to guide the selection of the next transmission node. Since the importing of buffer queue length information, packets can be distributed more evenly in the network, which can reduce the congestion possibility of network. In addition, for the sake of evaluation of a routing strategy, we propose four criterions to assess the performance of network. Based on the four criterions, we first compare the experimental results of our strategy with the original strategy only including node degree information and then give some insights of our new strategy according to the simulation results.

Interconnections between networks make the traffic condition in interconnected networks more complicated than that in an isolated network. They make the load and capacity of nodes mismatch and restrict the traffic performance accordingly. To improve the performance, in this paper, we propose a hybrid routing strategy, which distinguishes the traffic within each individual network and the traffic across multiple networks and uses different routing rules for these two types of traffic. Simulation results show that this routing strategy can achieve better traffic performance than traditional strategies when networks are coupled by a small number of interconnected links, which is the case in most of real-world interconnected networks. Therefore, the proposed hybrid routing strategy can find applications in the planning and optimization of practical interconnected networks.

An efficient routing strategy can deliver packets quickly to improve the network capacity. Node congestion and transmission path length are inevitable real-time factors for a good routing strategy. Existing dynamic global routing strategies only consider the congestion of neighbor nodes and the shortest path, which ignores other key nodes’ congestion on the path. With the development of detection methods and techniques, global traffic information is readily available and important for the routing choice. Reasonable use of this information can effectively improve the network routing. So, an improved global dynamic routing strategy is proposed, which considers the congestion of all nodes on the shortest path and incorporates the waiting time of the most congested node into the path. We investigate the effectiveness of the proposed routing for scale-free network with different clustering coefficients. The shortest path routing strategy and the traffic awareness routing strategy only considering the waiting time of neighbor node are analyzed comparatively. Simulation results show that network capacity is greatly enhanced compared with the shortest path; congestion state increase is relatively slow compared with the traffic awareness routing strategy. Clustering coefficient increase will not only reduce the network throughput, but also result in transmission average path length increase for scale-free network with tunable clustering. The proposed routing is favorable to ease network congestion and network routing strategy design.

Traffic capacity of a network is very vital to a variety of complex networks, such as communication networks and road networks, in which the bandwidth of every link is limited or finite. In this work, inspired by the deployment process of nodes and links in real networks, we assume the bandwidth of every link is composed of a constant part and a degree-related one that can be updated iteratively with the network hardware update. We propose a link bandwidth-based routing mechanism to enhance the network traffic capacity. Extensive simulations in both scale-free networks and random networks are done to confirm the effectiveness of our proposed method. Comparing results with the shortest path routing and a weighted routing, our method achieves better network traffic capacity among all used routing strategies without obvious extra cost including the network diameter, average path length and average packet traveling time. Our work studies network routing from a very new perspective and might have potential applications in real network systems such as the communication networks.

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.

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.

The research on efficient routing strategies holds paramount importance in mitigating network congestion and enhancing the transmission capacity of complex networks. A Hierarchical Routing Optimization (HRO) strategy is proposed for dual-layer networks featuring both logical and physical layer structures. This strategy employs distinct methods for packet transmission at the logical and physical layers to optimize the utilization of network resources. Comparison with the improved static-weighted routing strategy (ISWR) and the improved effective routing strategy (IER) involves analyzing the relationship between the transmission capacity of the dual-layer network and the coupling method under these three routing strategies. This analysis aims to determine the optimal coupling method for the routing strategy, thereby enhancing overall network capacity. The simulation results reveal that the random coupling method proves most effective when employing the ISWR strategy, the assortative coupling method excels with the IER strategy, and the dissortative coupling method stands out when implementing the HRO strategy. In evaluating the ISWR strategy, IER strategy, and HRO strategy, it becomes evident that the HRO strategy substantially amplifies the transmission capacity of the dual-layer network. Furthermore, the HRO strategy exhibits heightened robustness against both random and deliberate attacks compared to the IER strategy.