基于业务感知的增强型小区间干扰协调算法

针对异构密集网络中宏基站对微基站用户干扰严重,用户业务变化剧烈,以及系统边缘频谱效率低下的问题,提出了一种基于业务感知的增强型小区间干扰协调算法。该算法首先利用离散马尔科夫调制过程对用户业务进行建模,然后提出了一种基于部分可观察马尔科夫决策过程的感知算法来感知用户业务变化,最后在感知结果的基础上提出了一种适应用户业务变化的动态ABS调整方案。仿真结果表明,所提方案有效提升了系统边缘频谱效率,同时用户平均丢包率也得到了显著地下降。     

城市群城镇交通网络特性研究

为了研究城市群城镇交通网络特性,本文运用primal approach方法以城镇为节点,以其之间的道路为边构造长沙城镇交通网络、株洲城镇交通网络等城市群城镇交通网络模型,使用Matlab和VC++6.0分别对它们的平均度、网络密度、聚集系数、平均最短路径、随机网络聚集系数、随机网络平均最短路径、网络结构熵、全局系数等网络特性指标进行计算和比较分析,得到以下结论:(1)城市群城镇交通网络都具有小世界性,是小世界网络;(2)城市群城镇交通网络都不存在幂律特征,不存在无标度性,不是无标度网络;(3)城市群城镇交通网络都不存在指数特征,不是随机网络;(4)城市群城镇交通网络中,长株潭城市群市县交通网络整体效率最高、网络密度最大,长株潭城市群城镇交通网结构熵最小,表明其最有序。     

A methodology for the characterization of flow conductivity through the identification of communities in samples of fractured rocks

We present a methodology that characterizes through the topology of a network the capability of flow conductivity in fractures associated to a reservoir under study. This strategy considers the fracture image as a graph, and is focused on two key aspects. The first is to identify communities or sets of nodes that are more conductive, and the second one is to find nodes that form the largest paths and have therefore more possibility of serving as flow channels. The methodology is divided into two stages, the first stage obtains the cross points from fracture networks. The second stage deepens on the community identification. This second stage carries out the process of identifying conductive nodes by using centrality measures (betweenness, eccentricity and closeness) for evaluating each node in the network. Then an optimization modularity method is applied in order to form communities using two different types of weights between cross points or nodes. Finally, each community is associated with the average value of each measure. In this way the maximum values in betweenness and eccentricity are selected for identifying communities with the most important nodes in the network. The results obtained allow us to show regions in the fracture network that are more conductive according to the topology. In addition, this general methodology can be applied to other fracture characteristics.     

基于社区的动态网络节点介数中心度更新算法

随着互联网技术的迅猛发展,社会网络呈现出爆炸增长的趋势,传统的静态网络分析方法越来越难以达到令人满意的效果,于是对网络进行动态分析就成为社会网数据管理领域的一个研究热点。节点介数中心度衡量的是一个节点对图中其他点对最短路径的控制能力,有利于挖掘社会网络中的重要节点。在图结构频繁变化的场合,若每次变化后都重新计算整个图中所有节点的介数中心度,则效率将会很低。针对动态网络中节点介数中心度计算困难的问题,本文提出一种基于社区的节点介数中心度更新算法。通过维护社区与社区、社区与节点的最短距离集合,快速过滤掉那些在网络动态更新中不受影响的点对,从而大大提高节点介数中心度的更新效率。真实数据集和合成数据集上的实验结果表明了论文所提算法的有效性。     

Bounded budget betweenness centrality game for strategic network formations

In computer networks and social networks, the betweenness centrality of a node measures the amount of information passing through the node when all pairs are conducting shortest path exchanges. In this paper, we introduce a strategic network formation game in which nodes build connections subject to a budget constraint in order to maximize their betweenness in the network. To reflect real world scenarios where short paths are more important in information exchange in the network, we generalize the betweenness definition to only count shortest paths with a length limit ? in betweenness calculation. We refer to this game as the bounded budget betweenness centrality game and denote it as ?- B³C game, where ? is the path length constraint parameter.We present both complexity and constructive existence results about Nash equilibria of the game. For the nonuniform version of the game where node budgets, link costs, and pairwise communication weights may vary, we show that Nash equilibria may not exist and it is NP-hard to decide whether Nash equilibria exist in a game instance. For the uniform version of the game where link costs and pairwise communication weights are one and each node can build k links, we construct two families of Nash equilibria based on shift graphs, and study the properties of Nash equilibria. Moreover, we study the complexity of computing best responses and show that the task is polynomial for uniform 2- B³C games and NP-hard for other games (i.e. uniform ?- B³C games with ?≥3 and nonuniform ?- B³C games with ?≥2).     

Efficient blocking probability computation of complex traffic flows for network dimensioning

Computing or estimating link blocking probabilities is a fundamental ingredient in network design and engineering. While in traditional telephone networks this was easily done by Erlang's formula, it became much harder in today's complex networks that carry very heterogeneous traffic. We present a simple, efficient method to estimate the blocking probability and link utilization for general multirate, heterogeneous traffic, where the individual bandwidth demands may aggregate in complex, nonlinear ways. The estimation is derived without adopting conventional performance modeling assumptions, such as Poisson arrivals or exponential holding times, thus allowing non-standard behaviour patterns, including special phenomena of IP networks, such as self-similarity. Despite its generality, our estimation maintains an optimally tight exponent and is capable of handling apparently very different cases in a unified way. The approach also makes it possible to make estimations under incomplete information. We show that the results are easily applicable for fast, robust link dimensioning, especially in case of complex traffic patterns, under partial information. Moreover, it is very well fitted for embedding into network level optimization tasks, due in part to simplicity and in part to convexity properties.     

对等网络的拥塞研究

对等网络的普遍应用带来了网络拥塞。从对等网络的拓扑属性研究网络拥塞，首先分析真实的Gnutella网络的流量，确定节点介数与网络拥塞之间存在关系。接着根据排队论模型从理论上给出了导致网络拥塞的临界负载与网络拓扑属性介数的公式解。最后设计拥塞控制策略，通过增加具有大介数节点的容量和这些节点间连接的方法来减轻网络拥塞。     

快速自适应流量突变检测算法研究

网络流量突变检测在网络管理中意义重大,针对多下一跳网络的特点,将异常定义为故障后流量的突变,提出了快速自适应流量感知突变检测算法。算法通过改进的直方图技术压缩数据后,利用聚集函数进行上升和下降两种突变的检测,进而根据感知流量变化来分析网络中节点及链路状态,快速准确地掌握网络整体状况。通过仿真平台对算法有效性进行验证,并与现有突变检测算法进行比较,结果表明该算法能使检测灵敏度和精度得到明显提高。     

Passive classification of wireless NICs during active scanning

Computer networks have become increasingly ubiquitous. However, with the increase in networked applications, there has also been an increase in difficulty to manage and secure these networks. The proliferation of 802.11 wireless networks has heightened this problem by extending networks beyond physical boundaries. We present a statistical analysis and propose the use of spectral analysis to identify the type of wireless network interface card (NIC). This mechanism can be applied to support the detection of unauthorized systems that use NICs that are different from that of a legitimate system. We focus on active scanning, a vaguely specified mechanism required by the 802.11 standard that is implemented in the hardware and software of the wireless NIC. We show that the implementation of this function influences the transmission patterns of a wireless stream that are observable through traffic analysis. Our mechanism for NIC identification uses signal processing to analyze the periodicity embedded in the wireless traffic caused by active scanning. A stable spectral profile is created from the periodic components of the traffic and used for the identity of the wireless NIC. We show that we can distinguish between NICs manufactured by different vendors, with zero false positives, using the spectral profile. Finally, we infer where, in the NIC, the active scanning algorithm is implemented.     

Comparison of capacity efficiency of DCS network restoration routing techniques

A crucial issue in the management of telecommunications networks is restoration after a network failure. We compare the capacity efficiency (the amount of traffic restored over fixed capacity) of several types of restoration methods for Digital Crossconnect Systems (DCSs) under both node or link failures in metropolitan networks. These restoration methods can be broadly categorized based on the type of control of the restoration process and the type of procedure for rerouting traffic around the failure. It is easily shown that point-to-point methods (where traffic is rerouted end-to-end) restore a higher percent of traffic than patch methods (where traffic is rerouted only around the failed segment). However, quantification of the difference in efficiency among the methods is important to fully evaluate other trade-offs, such as cost and speed of restoration. To evaluate the efficiency difference, we generated random network traffic distributions by simulation and then failed links and nodes for each simulation sample. Statistics were generated on the expected amount of restored traffic for each restoration method. In particular, we found that the efficiency advantage of point-to-point methods over patch methods is greater for link failure than for node failure. Also, the difference was not statistically significant in low levels of network congestion (i.e., networks with large amounts of excess capacity) and became more significant as network congestion increased.     

小世界网络抗毁性及介-度相关性研究

日常生活中,复杂网络主要面临随机攻击和选择性攻击,网络模型的结构特性使复杂网络在不同攻击方式下的抗毁性有很大的差异.综合考虑复杂网络的抗毁性参数和网络模型的结构特性差异,文章以节点的最大度值、平均度值、最大介数和平均介数为度量参数,通过5种不同攻击方式对WS小世界网络的抗毁性进行了测试,得到了介度关系曲线,随着节点的移除,动态分析了WS小世界网络的抗毁性和攻击下小世界网络的介 度相关性.实验结果表明,WS小世界网络在RD攻击下表现出一定的脆弱性,在其他攻击方式下有很强的鲁棒性,而其介度关系在某些区域呈线性关系,但大部分区域呈现无规律性,其动态相关性需要进一步研究.小世界网络较强的抗毁性对组建网络有重要的影响,鉴于小世界网络的结构特性,组建网络时应尽量不要把网络的功能集中在少数Hub节点上.针对WS小世界网络较强的鲁棒性,结合小世界网络的结构特性,将做进一步研究,以便提出更高效的攻击策略.     

Modeling external network behavior by using internal measurements

Network behavior is the set of observations or measurements that can be made about a network over time. The growth of network-based computing and the Internet have ensured that networks can no longer be considered in isolation, as events external to a particular network increasingly impact its behavior. Network management requires that information be known about these events, a task that is not always possible. We present a modeling strategy that takes partial information about a network and uses it to predict the behavior in unmonitored areas. This implementation is based on a meta-heuristic (genetic algorithm), and uses IP-packet information as well as a limited understanding of the external topology. This is then used to model the full topology, routing tables and traffic for the entire network at periodic intervals. The system was tested using the ns-2 network simulator and a Java implementation on a series of cases. The results showed a reasonable level of accuracy in predicting traffic and topology. Performance increased under system load, and at no point did the system generate any additional network traffic. This provides an efficient and effective strategy for network management.     

小世界网络中的删边扩容效应

不同于无标度网络,小世界网络中体现负载特性的介数分布和体现连接特征的度分布这两种结构差异很大,依据这个差异,我们提出了有效的删边扩容方法并进行了仿真实验,并进一步从容量与最大介数的关系理论分析确证了实验结果.接着,我们分析了小世界网络中介数分布的差异性与删边扩容效果的相关性,把基于介数的基尼系数变化用于度量删边扩容的效果,指出了结构差异是导致删边扩容效应的必要条件.还指出了无论从容量与介数的定义、仿真结果、结构差异与删边扩容效果的关系来看,都应该从介数入手来实现删边扩容方法,这种方法反直觉,有很多变种,并且实现方便、节省成本,作为一类新的路由策略可以广泛地应用于各类通信网络和交通网络等领域.     

Evolving networks： from topology to dynamics

A multi-local-world model is introduced to describe the evolving networks that have a localization property such as the Intemet. Based on this model, we show that the traffic load defined by “betweenness centrality” on the multi-local-world scale-flee networks‘ model also follows a power law form. In this kind of network, a few vertices have heavier loads and so play more important roles than the others in the network.     

Using core-periphery structure to predict high centrality nodes in time-varying networks

Vertices with high betweenness and closeness centrality represent influential entities in a network. An important problem for time varying networks is to know a-priori, using minimal computation, whether the influential vertices of the current time step will retain their high centrality, in the future time steps, as the network evolves. In this paper, based on empirical evidences from several large real world time varying networks, we discover a certain class of networks where the highly central vertices are part of the innermost core of the network and this property is maintained over time. As a key contribution of this work, we propose novel heuristics to identify these networks in an optimal fashion and also develop a two-step algorithm for predicting high centrality vertices. Consequently, we show for the first time that for such networks, expensive shortest path computations in each time step as the network changes can be completely avoided; instead we can use time series models (e.g., ARIMA as used here) to predict the overlap between the high centrality vertices in the current time step to the ones in the future time steps. Moreover, once the new network is available in time, we can find the high centrality vertices in the top core simply based on their high degree. To measure the effectiveness of our framework, we perform prediction task on a large set of diverse time-varying networks. We obtain F1-scores as high as 0.81 and 0.72 in predicting the top m closeness and betweenness centrality vertices respectively for real networks where the highly central vertices mostly reside in the innermost core. For synthetic networks that conform to this property we achieve F1-scores of 0.94 and 0.92 for closeness and betweenness respectively. We validate our results by showing that the practical effects of our predicted vertices match the effects of the actual high centrality vertices. Finally, we also provide a formal sketch demonstrating why our method works.     

Analysis of bandwidth allocation on end-to-end QoS networks under budget control

This paper considers the problem of bandwidth allocation on communication networks with multiple classes of traffic, where bandwidth is determined under the budget constraint. Due to the limited budget, there is a risk that the network service providers can not assert a 100% guaranteed availability for the stochastic traffic demand at all times. We derive the blocking probabilities of connections as a function of bandwidth, traffic demand and the available number of virtual paths based on the Erlang loss formula for all service classes. A revenue/profit function is studied through the monotonicity and convexity of the blocking probability and expected path occupancy. We present the optimality conditions and develop a solution algorithm for optimal bandwidth of revenue management schemes. The sensitivity analysis and three economic elasticity notions are also proposed to investigate the marginal revenue for a given traffic class by changing bandwidth, traffic demand and the number of virtual paths, respectively. By analysis of those monotone and convex properties, it significantly facilitates the operational process in the efficient design and provision of a core network under the budget constraint.     

Enterprise Network Traffic Monitoring, Analysis, and Reporting Using Web Technology

Today's enterprise networks are composed of multiple types of interconnected networks. Furthermore, organizations use a variety of systems and applications on these networks. Operations and management staff must provide an efficient, reliable and secure operating environment to support an organization's daily activities. Enterprise networks must be monitored for performance, configuration, security, accounting and fault management. Current management practices typically involve the use of complex, hard-to-learn and hard-to-use tools. What is needed desperately is a set of simple, uniform, ubiquitous tools for managing networks. Web-based management promises to provide such solutions. This paper focuses on the use of Web technology and the Multi-Router Traffic Grapher (MRTG) for the purposes of enterprise network traffic monitoring and reporting. In this paper, we first examine the requirements for enterprise network traffic monitoring, analysis and reporting, and then present the design and implementation of a Web-based network traffic monitoring and reporting system that satisfies those requirements. We also present guidelines we have formulated and used for analyzing enterprise network traffic. We then discuss our experiences in using such a system for traffic monitoring on two large enterprise networks.     

Spare capacity provisioning for quasi-static traffic

Resource provisioning has for long been an important area of research in network design. The traffic grooming problem in optical networks is a design problem of aggregating sub-wavelength traffic demands onto lightpaths and lightpaths onto fiber links such that the required electronic switching capability, hence network cost, can be minimized. Because of the reconfiguration cost in optical grooming networks, a reactive resource provisioning approach may become inefficient, and result in revenue loss. In this paper, we propose an over-provisioning scheme, which pre-allocates the spare capacity of lightpaths to dynamic sub-wavelength traffic demands such that the network can be more agile in responding to traffic increment requests. For the single-link case, we formulate the problem as a non-linear programming problem, and for under reasonable assumptions, we prove the objective function is convex. We provide an exact algorithm to find the optimal solution. The problem with general topologies is then studied. We prove the NP-hardness in this case, and propose heuristics. Numerical results show our heuristics perform well.     

Traffic-prediction-assisted dynamic bandwidth assignment for hybrid optical wireless networks

Hybrid optical-wireless networks provide the inexpensive broadband bandwidth, vital for modern applications, as well as mobility, and scalability required for an access network. However, in order to provide satisfactory Quality of Service (QoS) on such a non-homogeneous network, innovative designs are required.This paper proposes a novel scheduling mechanism to significantly improve the delay guarantee, while maintaining high-level throughput, by predicting the incoming traffic to optical network units (ONU). The proposed scheduler managed to exploit the available information in hybrid optical-wireless networks, to enhance the ONU scheduler. This results in accurate prediction of incoming traffic, which leads to intelligent and traffic-aware, scheduling and dynamic bandwidth assignment (DBA).Based on the proposed architecture, two DBA algorithms are proposed and their performance is evaluated by extensive simulations. Moreover, the maximum throughput of such network is analyzed. The results show that by using the proposed algorithms, the delay bound of delay-sensitive traffic classes can be decreased by a factor of two, without any adverse effect on the throughput.     

基于小波的网络流量特征分析

网络流量的特性分析一直是通信网络性能分析的一个极其重要的问题.本文充分利用小波变换具有多分辨率的特点,将时域里的网络流量通过小波分解,分解到不同的频带上,再对各子频带上的细节分量使用不同阀值进行消噪处理,然后采用自回归滑动平均混合模型对小波分解去噪后的不同分量分别进行预测再合成预测流量.对实际流量进行模拟预测,结果表明该模型有效地提高了预测精度,能对网络流量特别是短期流量做出较为准确的预测.