异质化带宽分配下的复杂网络数据流负载问题研究

研究了带有连接边传输容量(带宽)约束的复杂网络上如何提升网络数据流负载问题. 在网络连接边带宽资源总量固定的条件下, 提出了一种异质化带宽分配方案. 引入 "受控边" 概念, 通过加入适当比例的 "受控边", 重新分配带宽资源, 并结合具有拥塞感知能力路由策略的数据流量模型, 利用带宽分配调节数据流量走向, 提高了带宽利用效率, 最终使得网络整体的负载能力较带宽匀质化分配时有显著提升. 分别在Barabási-Albert无标度网络和Watts-Strogtz (WS)小世界网络平台上仿真, 发现按照本文的带宽分配方案, WS小世界网络中节点连接边带宽与网络负载有较强的相关性, 节点连接边带宽分配最均衡的时候, 网络负载能力达到最大. 关键词： 异质化带宽分配 负载 介数 受控边     

The related congestion failure estimating methodology and model in transportation networks

Previous works about the probability-based transportation networks evaluation method mainly focus on the static reliability evaluation, they ascribe the stochastic of the travel time to the external long time factors (the traffic supply or the traffic demand). Under this situation, the link’s travel time related relationship can be inferred, and it is efficacious for planners or engineers to make a decision for a long time. Even though some evaluation methodologies about transportation networks’ real-time travel time reliability has been presented, these works assume that the link’s travel time is independent. In this paper we relax this assumption. Using the Gauss copula theory, we present a new method to evaluate the transportation networks’ real-time travel time reliability. The results show that it will overestimate the route or the networks’ travel time reliability when not considering the links’ travel time are related. Not only that, we deep the static reliability evaluation model to the dynamic, we also present the link and transportation network congestion failure evaluation model. Estimations from the model are compared to field-measured data. It shows that, under the error interval ±$\pm$2 times, the link congestion failure model accuracy rate is above 90.3%, under the error interval ±$\pm$0.05; the net congestion failure model accuracy rate is above 95%.     

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.     

Bandwidth allocation strategy for traffic systems of scale-free network

In this Letter, the bandwidth resource allocation strategy is considered for traffic systems of complex networks. With a finite resource of bandwidth, an allocation strategy with preference parameter α is proposed considering the links importance. The performance of bandwidth allocation strategy is studied for the local routing protocol and the shortest path protocol. When important links are slightly favored in the bandwidth allocation, the system can achieve the optimal traffic performance for the two routing protocols. For the shortest path protocol, we also give a method to estimate the network traffic capacity theoretically.     

Bandwidth allocation in cooperative wireless networks: Buffer load analysis and fairness evaluation

In modern cooperative wireless networks, the resource allocation is an issue of major significance. The cooperation of source and relay nodes in wireless networks towards improved performance and robustness requires the application of an efficient bandwidth sharing policy. Moreover, user requirements for multimedia content over wireless links necessitate the support of advanced Quality of Service (QoS) features. In this paper, a novel bandwidth allocation technique for cooperative wireless networks is proposed, which is able to satisfy the increased QoS requirements of network users taking into account both traffic priority and packet buffer load. The performance of the proposed scheme is examined by analyzing the impact of buffer load on bandwidth allocation. Moreover, fairness performance in resource sharing is also studied. The results obtained for the cooperative network scenario employed, are validated by simulations. Evidently, the improved performance achieved by the proposed technique indicates that it can be employed for efficient traffic differentiation. The flexible design architecture of the proposed technique indicates its capability to be integrated into Medium Access Control (MAC) protocols for cooperative wireless networks.     

An optimal network for passenger traffic

The optimal solution of an inter-city passenger transport network has been studied using Zipf’s law for the city populations and the Gravity law describing the fluxes of inter-city passenger traffic. Assuming a fixed value for the cost of transport per person per kilometer we observe that while the total traffic cost decreases, the total wiring cost increases with the density of links. As a result the total cost to maintain the traffic distribution is optimal at a certain link density which vanishes on increasing the network size. At a finite link density the network is scale-free. Using this model the air-route network of India has been generated and an one-to-one comparison of the nodal degree values with the real network has been made.     

Personalized recommendation via an improved NBI algorithm and user influence model in a Microblog network

Bipartite network based recommendations have attracted extensive attentions in recent years. Differing from traditional object-oriented recommendations, the recommendation in a Microblog network has two crucial differences. One is high authority users or one’s special friends usually play a very active role in tweet-oriented recommendation. The other is that the object in a Microblog network corresponds to a set of tweets on same topic instead of an actual and single entity, e.g. goods or movies in traditional networks. Thus repeat recommendations of the tweets in one’s collected topics are indispensable. Therefore, this paper improves network based inference (NBI) algorithm by original link matrix and link weight on resource allocation processes. This paper finally proposes the Microblog recommendation model based on the factors of improved network based inference and user influence model. Adjusting the weights of these two factors could generate the best recommendation results in algorithm accuracy and recommendation personalization.     

Proposal of Rip up & Re allocate Algorithm for Optical Layer 2 Switch Network

We are developing an optical layer-2s witch network that uses both wavelength-division multiplexing and time-division multiplexing technologies for efficient traffic aggregation in metro networks.For efficient traffic aggregation,path bandwidth control is key because it strongly affects bandwidth efficiency.For this paper,we propose a dynamic time-slot allocation method that uses periodic information of difference values of traffic variation.This method can derive near-optimal allocation with lower computational cost,which enlarges the maximum available network size compared with conventional time-slot allocation methods.Numerical results show that the proposed method enables dynamic path control in 1K-node-scale optical layer-2s witch network,which leads to cost-effective metro networks.     

A multi-timescale resource allocation algorithm based on self-learning for distributed fog radio access networks

Faced with limited network resources, diverse service requirements and complex network structures, how to efficiently allocate resources and improve network performances is an important issue that needs to be addressed in 5G or future 6G networks. In this paper, we propose a multi-timescale collaboration resource allocation algorithm for distributed fog radio access networks (F-RANs) based on self-learning. This algorithm uses a distributed computing architecture for parallel optimization and each optimization model includes large time-scale resource allocation and small time-scale resource scheduling. First, we establish a large time-scale resource allocation model based on long-term average information such as historical bandwidth requirements for each network slice in F-RAN by long short-term memory network (LSTM) to obtain its next period required bandwidth. Then, based on the allocated bandwidth, we establish a resource scheduling model based on short-term instantaneous information such as channel gain by reinforcement learning (RL) which can interact with the environment to realize adaptive resource scheduling. And the cumulative effects of small time-scale resource scheduling will trigger another round large time-scale resource reallocation. Thus, they constitute a self-learning resource allocation closed loop optimization. Simulation results show that compared with other algorithms, the proposed algorithm can significantly improve resource utilization.     

一种新的应用于弹性分组环的公平算法

为了达到高的带宽利用率,理想的空间重用和带宽分配的公平性.本文提出一种新的应用于弹性分组环网络的带宽分配算法,该算法采用了有限集合中收敛速度最快的二分法,通过对公平速率的逐次逼近来实现带宽的动态分配,适用于分布式网络环境.分析和仿真表明采用基于二分法的带宽分配算法能够给每个节点分配到接近理想的公平带宽,整个环路在实现公平性的同时能够得到最大的空间重用并且收剑迅速.     

Enhancing network transmission capacity by efficiently allocating node capability

A network’s transmission capacity is the maximal rate of traffic inflow that the network can handle without causing congestion. Here we study how to enhance this quantity by allocating resource to individual nodes while preserving the total amount of the resource available. We propose a practical and effective scheme which redistributes node capability based on the local knowledge of node connectivity. We show that our scheme enhances the transmission capacity of networks with heterogeneous structures by up to two orders of magnitude.     

Link prediction based on a semi-local similarity index

Missing link prediction provides significant instruction for both analysis of network structure and mining of unknown links in incomplete networks. Recently, many algorithms have been proposed based on various node-similarity measures. Among these measures, the common neighbour index, the resource allocation index, and the local path index, stemming from different source, have been proved to have relatively high accuracy and low computational effort. In this paper, we propose a similarity index by combining the resource allocation index and the local path index. Simulation results on six unweighted networks show that the accuracy of the proposed index is higher than that of the local path one. Based on the same idea of the present index, we develop its corresponding weighted version and test it on several weighted networks. It is found that, except for the USAir network, the weighted variant also performs better than both the weighted resource allocation index and the weighted local path index. Due to the improved accuracy and the still low computational complexity, the indices may be useful for link prediction.     

Towards a physics of Internet traffic in a geographic network

A set of equations from a biased random walk are shown to describe the time-based Gaussian distributions of Internet traffic relative to the Earth’s time zones. The Internet is an example of a more general physical problem dealing with motion near the speed of light relative to different time frames of reference. The second order differential equation (DE) takes the form of ‘time diffusion’ near the speed of light or alternatively considered as a complex variable with real time and imaginary longitudinal components. Congestion waves are generated by peak global traffic from different time zones following the Earth’s revolution. The DE is divided into space and time operators for discussion and each component solution, including constants, is illustrated using data from a global network compiled by the Stanford Linear Accelerator Centre (SLAC). Indices of global and regional phase congestion for the monitoring sites are calculated from standardised regressions from the Earth’s rotation. There is also a J-curve limit to transferring information by the Internet and this is expressed as an inequality underpinned by the speed of light with examples from US and European traffic. The research returns to an often little known theme of Isaac Newton’s: mixing physics with geography. In our case, the equations define trajectories of information packets travelling near the speed of light, navigating within networks and between longitudes, relative to the Earth’s rotation.     

无标度网络上队列资源分配研究

研究了节点队列资源有限的条件下,无标度网络上的信息流动力学过程,发现了网络由自由流通到拥塞的相变现象,提出了一种基于节点度的队列资源分配模型.模型的核心是使节点i的队列长度与kβi成正比(ki为节点i的度,β为分配参数).仿真结果表明,在网络使用最短路径算法进行信息包传送的条件下,β近似等于1.25时队列资源分配最合理,网络容量最大,且该最佳值与队列总资源多少以及网络的规模无关.     

Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: A brief review

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliably used for control and optimization in traffic networks. It is shown that the generally accepted fundamentals and methodologies of the traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of the traffic and transportation theory belong (i) Lighthill–Whitham–Richards (LWR) theory, (ii) the General Motors (GM) model class (for example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular (fixed or stochastic) value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of the traffic and transportation theory, we discuss the three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.     

Effective usage of shortest paths promotes transportation efficiency on scale-free networks

With rapid economic and social development, the problem of traffic congestion is getting more and more serious. Accordingly, network traffic models have attracted extensive attention. In this paper, we introduce a shortest-remaining-path-first queuing strategy into a network traffic model on Barabási–Albert scale-free networks under efficient routing protocol, where one packet’s delivery priority is related to its current distance to the destination. Compared with the traditional first-in-first-out queuing strategy, although the network capacity has no evident changes, some other indexes reflecting transportation efficiency are significantly improved in the congestion state. Extensive simulation results and discussions are carried out to explain the phenomena. Our work may be helpful for the designing of optimal networked-traffic systems.     

基于正交频分复用无源光网络的动态带宽分配算法研究

介绍了一种应用于未来大容量、多业务接入场景下的称为光正交频分复用无源光网络的下一代接入网技术,并提出了一种基于此结构的称为基于服务质量需求的固定周期流水线轮询动态带宽分配算法.该算法通过应用二级带宽分配机制、带宽预申请机制和最小带宽申请优先原则等方法,有效地保障了在大容量、多业务接入场景下各个业务不同的服务质量需求.为研究其性能,建立了该算法的仿真模型并进行了对比仿真.仿真结果显示该算法以低时延和低抖动有效地支持快速转发业务,同时平衡了确保转发业务和尽力而为业务之间的优先性和相对公平性,并且实现了不同光网络单元间的同优先级业务带宽分配的公平性.与传统的动态带宽分配算法算法相比,基于服务质量需求的固定周期流水线轮询动态带宽分配算法具有执行效率高、算法复杂度低、性能良好等优点,并且能够更好地适应光正交频分复用无源光网络的特性,发挥网络最大的性能.     

基于MPEG-4的视频流式传输系统及动态带宽分配方法

提出了一个基于MPEG 4精细可分级编码技术的视频流式传输系统。介绍了系统中主要模块的作用,并重点研究了速率控制模块。速率控制模块采用了适合视频流式传输的动态带宽分配方法。它可以根据实时的网络通道波动状况来动态调整滑动参数,以适应网络波动和高效地利用网络的有限资源。实验结果表明,动态带宽分配方法在动态带宽波动条件下不仅可以使相邻帧间的视频质量更加平滑,而且可以大大提高解码视频图像的总体质量,也就是说可同时改善解码视频的主客观性能。     

Evolution of Chinese airport network

With the rapid development of the economy and the accelerated globalization process, the aviation industry plays a more and more critical role in today’s world, in both developed and developing countries. As the infrastructure of aviation industry, the airport network is one of the most important indicators of economic growth. In this paper, we investigate the evolution of the Chinese airport network (CAN) via complex network theory. It is found that although the topology of CAN has remained steady during the past few years, there are many dynamic switchings inside the network, which have changed the relative importance of airports and airlines. Moreover, we investigate the evolution of traffic flow (passengers and cargoes) on CAN. It is found that the traffic continues to grow in an exponential form and has evident seasonal fluctuations. We also found that cargo traffic and passenger traffic are positively related but the correlations are quite different for different kinds of cities.