无标度复杂网络负载传输优化策略

提出了一种能够显著提高无标度复杂网络负载传输性能的优化路由策略.实现了负载在核心节点与边缘节点间的合理分配.分析表明该策略使得网络的负载处理能力正比于网络规模的平方,而与单个节点的度值无关.实验结果显示优化路由策略在保持了最短路由策略小世界效应的同时,成倍地提升了网络的负载传输能力,且随着网络平均节点度的增加其优势越趋显著.此外,与有效路由策略的比较进一步验证了优化路由策略的优异性能. 关键词： 优化路由策略 复杂网络 负载传输 网络阻塞     

一类基于随机行走机理的优化路由改进策略

在对随机行走过程的研究中发现:单个粒子通过某条特定路径的时间正比于该路径上所有节点度的连乘积.据此,文章提出基于随机行走机理的优化路由改进策略.该策略以节点度连乘积最小化为原则,通过调节可变参数,建立节点处理能力均匀分布的情况下最佳路由策略.通过分析比较不同路由策略条件下平均路由介数中心度,网络的临界负载量,平均路径长度以及平均搜索信息量等性能指标,研究结果表明,此改进路由策略在保证网络平均路径长度较少增加的前提下,使网络的传输能力获得最大幅度的提升. 关键词： 复杂网络 路由策略 负载传输     

Probability routing strategy for scale-free networks

This study proposes a probability routing strategy for improving traffic capability on scale-free networks. Compared with the shortest path routing strategy depending on central nodes largely and the efficient routing strategy avoiding hub routers as much as possible, the probability routing strategy makes use of hub routers more efficiently, transferring approximate average amount of packs of the whole network. Simulation results indicate that the probability routing strategy has the highest network capacity among the three routing strategies. This strategy provides network capacity that can be more than 30 times higher than that of the shortest path routing strategy and over 50% higher than that of the efficient routing strategy. In addition, the average routing path length of our proposed strategy is over 10% shorter than that of the efficient routing strategy and only about 10% longer than that of the shortest path routing strategy.     

A dynamic routing strategy with limited buffer on scale-free network

In this paper, we propose an integrated routing strategy based on global static topologyinformation and local dynamic data packet queue lengths to improve the transmissionefficiency of scale-free networks. The proposed routing strategy is a combination of aglobal static routing strategy (based on the shortest path algorithm) and local dynamicqueue length management, in which, instead of using an infinite buffer, the queue lengthof each node i in the proposed routing strategy is limited by acritical queue length Q_ic. When the networktraffic is lower and the queue length of each node i is shorter than itscritical queue length Q_ic, it forwardspackets according to the global routing table. With increasing network traffic, when thebuffers of the nodes with higher degree are full, they do not receive packets due to theirlimited buffers and the packets have to be delivered to the nodes with lower degree. Theglobal static routing strategy can shorten the transmission time that it takes a packet toreach its destination, and the local limited queue length can balance the network traffic.The optimal critical queue lengths of nodes have been analysed. Simulation results showthat the proposed routing strategy can get better performance than that of the globalstatic strategy based on topology, and almost the same performance as that of the globaldynamic routing strategy with less complexity.     

一种有效提高无标度网络负载容量的管理策略

现有研究表明明显的社团结构会显著降低网络的传输性能. 本文基于网络邻接矩阵的特征谱定义了链路对网络社团特性的贡献度, 提出一种通过逻辑关闭或删除对网络社团特性贡献度大的链路以提高网络传输性能的拓扑管理策略, 即社团弱化控制策略(CWCS 策略). 在具有社团结构的无标度网络上分别进行了基于全局最短路径路由和局部路由的仿真实验, 并与关闭连接度大的节点之间链路的HDF 策略进行了比较. 仿真实验结果显示, 在全局最短路径路由策略下, CWCS策略能更有效地提高网络负载容量, 并且网络的平均传输时间增加的幅度变小. 在局部路由策略下, 当调控参数0<α<2, 对网络负载容量的提升优于HDF策略. 关键词： 复杂网络 社团特性 负载容量 拓扑管理     

Traffic resource allocation for complex networks

In this paper, an optimal resource allocation strategy is proposed to enhance traffic dynamics in complex networks. The network resources are the total node packet-delivering capacity and the total link bandwidth. An analytical method is developed to estimate the overall network capacity by using the concept of efficient betweenness (ratio of algorithmic betweenness and local processing capacity). Three network structures (scale-free, small-world, and random networks) and two typical routing protocols (shortest path protocol and efficient routing protocol) are adopted to demonstrate the performance of the proposed strategy. Our results show that the network capacity is reversely proportional to the average path length for a particular routing protocol and the shortest path protocol can achieve the largest network capacity when the proposed resource allocation strategy is adopted.     

Optimization of transport protocols in complex networks

In this paper, an optimal routing strategy is proposed to enhance the traffic capacity of complex networks. In order to avoid nodes overloading, the new algorithm is derived on the basis of generalized betweenness centrality which gives an estimate of traffic handled by the node for a route set. Since the nodes with large betweenness centrality are more susceptible to traffic congestion, the traffic can be improved, as our strategy, by redistributing traffic load from nodes with large betweenness centrality to nodes with small betweenness centrality in the proceeding of computing collective routing table. Particularly, depending on a parameter that controls the optimization scale, the new routing can not only enlarge traffic capacity of networks more, but also enhance traffic efficiency with smaller average path length. Comparing results of previous routing strategies, it is shown that the present improved routing performs more effectively.     

Adaptive local routing strategy on a scale-free network

Due to the heterogeneity of the structure on a scale-free network, making the betweennesses of all nodes become homogeneous by reassigning the weights of nodes or edges is very difficult. In order to take advantage of the important effect of high degree nodes on the shortest path communication and preferentially deliver packets by them to increase the probability to destination, an adaptive local routing strategy on a scale-free network is proposed, in which the node adjusts the forwarding probability with the dynamical traffic load (packet queue length) and the degree distribution of neighbouring nodes. The critical queue length of a node is set to be proportional to its degree, and the node with high degree has a larger critical queue length to store and forward more packets. When the queue length of a high degree node is shorter than its critical queue length, it has a higher probability to forward packets. After higher degree nodes are saturated (whose queue lengths are longer than their critical queue lengths), more packets will be delivered by the lower degree nodes around them. The adaptive local routing strategy increases the probability of a packet finding its destination quickly, and improves the transmission capacity on the scale-free network by reducing routing hops. The simulation results show that the transmission capacity of the adaptive local routing strategy is larger than that of three previous local routing strategies.     

Traffic dynamics based on a traffic awareness routing strategy on scale-free networks

By incorporating local traffic information into the shortest path routing strategy, we numerically investigate the effectiveness of the traffic awareness routing strategy for scale-free networks with different clustering. In order to characterize the efficiency of the packet-delivery process, we introduce an order parameter and an average transmission time that allow us to measure the network capacity by the critical value of phase transition from free flow to congestion. Compared with the shortest path routing protocol, the network capacity is greatly enhanced by the traffic awareness routing strategy. We also find that there exists an optimum value for the tunable parameter in the congestion awareness strategy. Moreover, simulation results show that the more clustered the network, the less efficient the packet-delivery process.     

Optimal routing strategy based on the minimum information path

In this paper, we propose a new routing strategy based on the minimum information path, named the optimal routing (OR) strategy, to improve the transportation capacity of scale-free networks. We define the average routing centrality degree of the node to analyze the traffic load on nodes of different degree. We analyze the transportation capacity by using the critical values of R_c, the average packet travel time, and the average path length. Both theoretical and experimental results show that the capacity of the network under our strategy will be maximized when the packet-delivery rate of the node is directly proportional to the degree.     

Efficient packet routing strategy in complex networks

We investigate a new efficient packet routing strategy which mitigates traffic congestion on complex networks. In order to avoid congestion, we minimize the maximum betweenness, which is a measure for concentration of routing paths passing through a node in the network. Danila et al. propose a packet routing strategy in which, instead of shortest paths, they used efficient paths, which are the paths with the minimum total summations of weights assigned to nodes in the respective paths. They use a heuristic algorithm in which the weights are updated step by step by using the information of betweenness of each node in every step and the respective total summations of weights for paths through the nodes with large degrees become comparatively large. Thus passage through such nodes, where congestion almost occurs, is likely to be avoided in their algorithm. The convergence time by their algorithm is, however, quite long. In this paper, we propose a new efficient heuristic algorithm which balances traffic on networks by achieving minimization of the maximum betweenness in the much smaller number of iteration steps for convergence than that by the algorithm of Danila et al.     

Improved routing strategy based on gravitational field theory

Routing and path selection are crucial for many communication and logistic applications. We study the interaction between nodes and packets and establish a simple model for describing the attraction of the node to the packet in transmission process by using the gravitational field theory, considering the real and potential congestion of the nodes. On the basis of this model, we propose a gravitational field routing strategy that considers the attractions of all of the nodes on the travel path to the packet. In order to illustrate the efficiency of proposed routing algorithm, we introduce the order parameter to measure the throughput of the network by the critical value of phase transition from a free flow phase to a congested phase,and study the distribution of betweenness centrality and traffic jam. Simulations show that, compared with the shortest path routing strategy, the gravitational field routing strategy considerably enhances the throughput of the network and balances the traffic load, and nearly all of the nodes are used efficiently.     

Incremental routing strategy on scale-free networks

The most important function of a network is for transporting traffic. Due to the low traffic capacity of network systems under the global shortest path routing, plenty of heuristic routing strategies are emerging. In this paper, we propose a heuristic routing strategy called the incremental routing algorithm to improve the traffic capacity of complex networks. We divide the routing process into N$N$(the network size) steps and, at each step, we heuristically calculate all the routes for one source node considering both the dynamic efficient betweenness centrality and node degree information. We do extensive simulations on scale-free networks to confirm the effectiveness of the proposed incremental routing strategy. The simulation results show that the traffic capacity has been enhanced by a substantial factor at the expense of a slight lengthening in the average path.     

面向成本-收益好的无标度耦合网络构建方法

较大平均路径长度的网络会带来较大的网络延迟, 难以支持时间敏感业务与应用. 通过增加连接可以降低源和目的节点之间的跳数, 进而降低网络平均延迟, 使得更加快速地传播信息, 但是增加连接的同时也增加了网络构建成本. 分层网络是研究网络耦合的一个有效方法, 但目前网络构建过程中将每层网络分别处理并认为每层网络之间没有强相关性. 本文提出了一种面向成本-收益的无标度网络动态构建方法. 此方法将网络分为多层, 基于连续论在高层网络中添加连接, 使得网络演化为无标度网络. 此连续过程包括节点度增加过程和局部网络半径增长两个连续过程, 在增加连接的过程中引入表征网络构建成本和收益的成本-收益指标. 模拟结果表明引入成本-收益指标的无标度耦合网络构建方法能够在合理范围内有效降低网络平均路径长度, 提升网络性能, 并且本文给出了耦合网络的动态业务性能, 通过调整高层网络避免网络拥塞.     

复杂网络的一种加权路由策略研究

复杂网络的传输能力是其功能正常运转的重要保障,提高网络的吞吐量有着重要意义.提出一种新的高效路由策略,以提高复杂网络的传输能力,称之为加权路由策略.即对网络的每一条边加权,权值与该边的两端节点的度相关,然后数据包按照这个加权网络的最短路径路由.这样的路径可以更均匀地经过各个节点,发挥它们的传输能力,极大地提高网络的吞吐量.可以避免数据包集中地通过个别度大的节点,在这些节点发生拥塞.仿真显示,该策略比传统的最短路径策略优越,对很多结构的网络,可以提高几十倍的吞吐量. 关键词： 复杂网络 路由策略 吞吐量 拥塞     

Integrating network structure and dynamic information for better routing strategy on scale-free networks

We study information packet routing processes on scale-free networks by mimicking the Internet traffic delivery strategies. We incorporate both the global network structure information and local queuing information in the dynamic processes. We propose several new routing strategies to guide the packet routing. The performance of the routing strategies is measured by the average transit time of the packets as well as their dependence on the traffic amount. We find that the routing strategies which integrate both global network structure information and local dynamic information perform much better than the traditional shortest-path routing protocol which takes into account only the global topological information. Moreover, from comparative studies of these routing strategies, we observe that some of our proposed methods can decrease the average transit time of packets but the performance is closely dependent on the total amount of traffic while some other proposed methods can have good performance independent of the total amount of traffic with hyper-excellent average transit time of packets. Also, numerical results show that our proposed methods integrating network structure information and local dynamic information can work much better than the methods recently proposed in [S. Sreenivasan, R. Cohen, E. López, Z. Toroczkai, H.E. Stanley, Phys. Rev. E 75 (2007) 036105, Zhi-Xi Wu, Gang Peng, Eric W.M. Wong, Kai-Hau Yeung, J. Stat. Mech. (2008) P11002.], which only considered network structure information.     

基于局部路由策略的复杂网络拥塞控制

提出一种复杂网络上的局部路由策略,算法采用节点收缩法评估节点的重要度,发送节点根据邻居节点的重要度及网络的状态自适应地调整向邻居节点转发数据包的概率.在网络处于自由流通状态时充分发挥关键节点的优势,保证数据包快速到达目的地;在网络处于即将拥塞时分散业务,根据节点重要度准确识别网络中的关键节点,通过有效分流予以保护.仿真结果表明:在网络处于自由流通状态时,该局部路由策略能充分发挥网络中关键节点的枢纽作用,保持较低的传输时延;在网络部分关键节点出现拥塞时,该局部路由策略能有效避开拥挤严重的节点,将数据包均匀地分布在各个节点上,有效抑制网络拥塞,提高网络的容量.     

Routing and wavelength assignment algorithms for translucent optical networks

Due to transmission impairments, optical regeneration is needed to extend the length of a lightpath beyond its transparent length. Spare transmitter (Tx) and receiver (Rx) modules in an optical network node can be used for optical regeneration. A Max-spare algorithm for locating the regeneration nodes for a lightpath is proposed and compared with a Greedy algorithm in conjunction with two routing algorithms, namely, wavelength weighted (WW) and length weighted (LW) routing algorithms. Through simulation we find that significant number of lightpaths that cannot be established due to the violation of transparent length can be established if the regeneration algorithm is used to select transit nodes that have spare Tx and Rx for 3R regeneration. The translucent optical network with limited number of transceivers can still perform close to a transparent optical network with full set of transceivers. We find that for the same routing algorithm, the Max-spare algorithm yields better results than the Greedy algorithm. In addition; for the same regeneration nodes selection algorithm, the WW algorithm has better performance than the LW algorithm.     

一种基于分层的量子分组传输方案及性能分析

大规模量子通信网络中,采用量子分组传输技术能有效提升发送节点的吞吐量,提高网络中链路的利用率,增强通信的抗干扰性能.然而量子分组的快速传输与路由器性能息息相关.路由器性能瓶颈将严重影响网络的可扩展性和链路的传输效率.本文提出一种量子通信网络分层结构,并根据量子密集编码和量子隐形传态理论,给出一种基于分层的量子分组信息传输方案,实现端到端的量子信息传输.该方案先将量子分组按照目的地址进行聚类,再按聚类后的地址进行传输.仿真结果表明,基于分层的量子分组信息传输方案能够有效减少量子分组信息在量子通信网络中的传输时间,并且所减少的时间与量子路由器性能与发送的量子分组数量有关.因此,本文提出的量子分组信息传输方案适用于大规模量子通信网络的构建.     

WDM网状网中动态域间流量疏导策略

对波分复用(Wavelength Division Multiplexing,WDM)网状网中的动态域间流量疏导问题进行了深入研究.在源路由模式下,提出了一种基于固定备选路由方式的动态域间流量疏导算法,并在其基础上提出了只考虑波长均衡和同时考虑波长均衡与业务均衡的改进方法.该算法可以有效地避免路由环,得到较低的阻塞率,节省全网的收发器数目和波长资源.仿真结果表明,这种算法可以有效地改善网络性能.