基于引力场理论的复杂网络路由选择策略研究

利用引力场理论对网络传输过程中节点激发的引力场进行了描述,建立了节点的引力场方程,引入α和γ两个参数,用于调节数据传输对节点畅通程度、节点传输能力和路径长度的依赖程度．基于节点的引力场,提出了一种高效的路由选择算法,该算法下数据包将沿着所受路径引力最大的方向进行传递．为检验算法的有效性,引入有序状态参数卵,利用其由自由流到拥塞态的指标流量相变值度量网络的吞吐量,并通过节点的介中心值B分析网络的传输性能和拥塞分布．针对算法在不同α,γ取值条件下的路由情况进行了仿真．仿真结果显示,与传统最短路由算法相比,本文算法将网络传输能力提高了数倍,有效地均衡了节点的介中心值分布,传输路径平均长度（Lavg）随负载量R的增加表现出先增后减的变化趋势,而参数α与γ值的变化对网络传输能力几乎没有影响,说明本文路由算法的性能不依赖于α与γ,对于可行域内任意的α与γ算法都能保证网络传输能力近似相等．     

基于最短路径长度的空间网络路由

以通信网、电力网、交通网为代表的很多复杂网络以传输负载为基本功能.在这些网络中,网络的吞吐量是衡量网络传输性能的重要指标,如何提升网络的吞吐量是研究热点之一.不少研究人员提出了不同的路由算法,通过调节传输路径来提高网络吞吐量.但之前的研究很少考虑网络中节点的空间位置.本文针对空间网络提出了一种高效的路由策略,通过节点位置得到路径长度;采用该算法,负载从源节点沿着最短长度的路径传输到目标节点.为了检验算法的有效性,采用网络从自由流状态转变成拥塞状态的相变点Rc来衡量网络的吞吐量.在匀质和异质空间网络上的仿真表明,与传统的最少跳数路由策略相比,本文提出的基于最短路径长度的路由算法能有效提高空间网络的吞吐量.     

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     

互联网络数据包传输的一种简单元胞自动机模型

提出了一种描述计算机互联网络数据包传输的简单元胞自动机模型,并研究了沿着网络固定路径中路由节点数据包队列长度和传输时间的统计特性.计算机仿真结果表明,根据数据包输入速率和路由节点平均最大传输速率的不同,系统存在自由流和拥塞两种相态.在自由流状态,路由节点数据包排队长度和传输时间都呈现幂律特性;在拥塞状态,路由节点数据包排队长度呈现白噪声特征,而传输时间在低频段为幂律、高频段为白噪声特征.仿真结果和已有文献和经验数据得到的结论一致. 关键词： 元胞自动机 1//f噪声 幂律 计算机网络     

基于感知流量算法的复杂网络拥塞问题研究

研究了在具有感知流量的路由策略下,复杂网络的拓扑结构对网络中传输流量的影响.为了描述数据包传输过程的有效性,通过引入一个状态参数,利用由稳态到拥塞的指标流量相变值来刻画网络的吞吐量.基于每个节点的数据包处理能力与该节点的度或介数成比例提出两种模型并进行仿真.仿真结果表明,平均度相同的情况下,模型Ⅰ中,WS小世界网络比ER随机网络和BA无标度网络更容易产生拥塞;模型Ⅱ中,所有网络容量都得到较大的提高,尤其是WS小世界网络.但当网络的基本连接参数改变时,哪种模型更利于网络的流量传输,还要依据网络本身的结构特性 关键词： 复杂网络 无标度网络 感知流量 拥塞     

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.     

一种应用于含权无标度网络的全局路由算法

针对含权无标度网络提出了一种全局路由算法.该算法利用网络路径上的节点强度信息构建了一种全局路由代价函数,选择使该代价函数最小的路径来传输信息包,有效避开了网络中易发生拥塞的核心节点.实验结果表明,与最短路径算法相比,该算法以较小的平均路径长度的增加为代价,将网络容量提高了十多倍.     

虚拟网络行为对互联网整体特性的影响

虚拟网络是一种依赖Internet基础设施所提供的传输能力，但又具有独立拓扑结构和信息传递规则的应用层网络行为逻辑网络.提出了耦合虚拟网络行为与物理节点的抽象模型，对一类典型的虚拟网络逻辑拓扑给互联网整体特性带来的影响进行了分析.研究表明在虚拟网络作用下，节点数据包排队长度存在相变特性，但相变临界点比对规则网络发生了明显左移，网络性能相对恶化.当数据包注入速率小于相变临界速率时，节点数据包排队长度不相关或短程相关；在接近临界速率处，节点数据包排队长度长程相关，幂指数H增大，网络获得更强的长程相关性.同时，在注入速率大于或等于临界速率时，虚拟网络行为使网络呈现出一致的长程相关特性.     

空间网络上的随机游走

本文以一维均匀环为基础, 通过添加有限数量的长程连接构造出了一维有限能量约束下的空间网络, 环上任意节点i与j之间存在一条长程连接的概率满足p_ijα d_ij^-α (α≥ 0),其中d_ij为节点i与j之间的网格距离, 并且所有长程连接长度总和受到总能量∧=cN(c≥ 0)的约束, N为网络节点总数.通过研究该空间网络上的随机游走过程,存在最优幂指数α₀ 使得陷阱问题的平均首达时间最短.进一步研究发现,平均首达时间与网络规模N之间存在着幂律关系, 随着网络规模N和总能量∧的增加,最优幂指数α₀单调增加,并趋近最优值1.5.     

低温胁迫下香蕉叶片Chla荧光动力学参量的变化及其品种差异性

低温胁迫下,广东2号香蕉品种和巴西香蕉品种Williams的叶绿素(Chla)荧光动力学参量F_Ⅴ/F_m、ΔF_Ⅴ/F_T以及williams品种的F_IV/F_Ⅴ均呈下降趋势,两个品种的荧光上升半时间T_1/2及广东2号的F_IV/F_Ⅴ呈上升趋势.其中,Williams的F_Ⅴ/F_m、ΔF_Ⅴ/F_T和T_1/2的变化幅度小于广东2号,表明低温胁迫通过抑制光合电子传递速度和PSⅡ无活性中心含量的提高使香蕉叶片PSⅡ原初光能转换效率下降,相同低温对广东2号的影响大于对Williams的影响.F_Ⅴ/F_m和ΔF_Ⅴ/F_T可以作为评价香蕉幼苗抗冷性的物理指标.     

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.     

The Effect of Queueing Strategy on Network Traffic

In recent years, the transportation system has been faced by increasing challenge in congestion and inefficiency, and research in traffic network has become a significant area of interest. In this paper, we introduce a dynamic-information-based (DIB) queueing strategy into network traffic model under the efficient routing strategy. DIB makes a packet with higher priority to be delivered if there are less packets travelling along its path from the current node to the destination. It is found that, compared with the traditional first-in-first-out (FIFO) queueing strategy, DIB can effectively balance the traffic load of the system via delaying packets to be delivered to congested nodes. Although the network capacity has no obvious changes, some other indexes which reflect transportation efficiency are efficiently improved in the congestion state. Besides, extensive simulation results and discussions are provided to explain the phenomena. The results may provide novel insights for research on traffic systems.     

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.     

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     

The Efect of Queueing Strategy on Network Trafc

In recent years,the transportation system has been faced by increasing challenge in congestion and inefciency,and research in trafc network has become a significant area of interest.In this paper,we introduce a dynamic-information-based(DIB)queueing strategy into network trafc model under the efcient routing strategy.DIB makes a packet with higher priority to be delivered if there are less packets travelling along its path from the current node to the destination.It is found that,compared with the traditional first-in-first-out(FIFO)queueing strategy,DIB can efectively balance the trafc load of the system via delaying packets to be delivered to congested nodes.Although the network capacity has no obvious changes,some other indexes which reflect transportation efciency are efciently improved in the congestion state.Besides,extensive simulation results and discussions are provided to explain the phenomena.The results may provide novel insights for research on trafc systems.     

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.     

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.     

Efficient routing on small complex networks without buffers

In this paper, we are exploring strategies for the reduction of the congestion in the complex networks. The nodes without buffers are considered, so, if the congestion occurs, the information packets will be dropped. The focus is on the efficient routing. The routing strategies are compared using two generic models, i.e., Barabàsi–Albert scale-free network and scale-free network on lattice, and the academic router networks of the Netherlands and France. We propose a dynamic deflection routing algorithm which automatically extends path of the packet before it arrives at congested node. The simulation results indicate that the dynamic routing strategy can further reduce the number of dropped packets in a combination with the efficient path routing proposed by Yan et al. [5].     

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.