基于SDN的胖树数据中心网络多路径负载均衡算法研究

软件定义网络SDN(Software Defined Network)通过将网络设备的控制层与数据层分离解耦,能够实现网络的集中控制和流量的灵活转发,因此被广泛应用于数据中心等相关领域。在数据中心网络中,为了提高网络的带宽和吞吐量,多采用具有多路径特性的层次型网络拓扑结构,如胖树拓扑结构。然而传统路由算法对多路径的支持非常有限,无法充分利用网络剩余带宽。重点研究基于SDN的胖树数据中心网络多路径负载均衡算法。利用SDN网络集中控制的特点,获取多路径实时状态信息,计算各路径当前可用带宽,根据数据流的带宽需求选择最佳转发路径。实验结果表明,该算法无论在降低网络传播时延还是在提高网络吞吐量等方面都优于传统路由算法,能够实现胖树数据中心网络的多路径负载均衡。     

基于差分进化融合蚁群算法的数据中心流量调度机制

针对数据中心网络的传统流量调度方法容易引起网络拥塞及链路负载不均衡等问题,提出了一种差分进化（DE）融合蚁群（ACO）算法（DE-ACO）的动态流量调度机制,对数据中心网络中的大象流调度进行优化。首先,利用软件定义网络（SDN）技术捕获实时网络状态信息并设定流量调度的优化目标;然后,通过优化目标重定义DE算法,计算出多条可用候选路径,作为ACO算法的初始化全局信息素;最后,结合全局网络状态以求得全局最优路径,并重新路由拥堵链路上的大象流。实验结果表明,以在随机通信模式下为例,与等价多路径路由（ECMP）算法和基于蚁群算法的SDN数据中心网络流量调度（ACO-SDN）算法相比,所提算法的平均对分带宽分别提高了29.42%～36.26%和5%～11.51%,降低了网络的最大链路利用率（MLU）,较好地实现了网络负载均衡。     

数据中心网络中基于蚁群算法的动态多路径负载均衡

针对数据中心网络中等价多路径路由算法（equal-cost multi-path routing,ECMP）无法有效调度大象流而导致流量负载不均衡及易造成网络拥塞的问题,提出了一种基于蚁群算法的动态多路径负载均衡（ant colony algorithm based dynamic multipath load balancing,ADMLB）算法。ADMLB算法首先通过控制器获取网络负载信息,同时检测大象流并标记,然后调用改进的蚁群算法,根据大象流所需带宽选择多路径。实验结果表明,与传统的ECMP和现有流调度算法相比,ADMLB算法降低了链路延迟时间,有效提高了链路带宽利用率。     

基于SDN的数据中心网络流概率路径选择方法

为提高数据中心网络(DCN)的链路带宽利用率和吞吐量,提出一种基于软件定义网络(SDN)的流概率路径选择方法。在最短路径选择方法的基础上,利用SDN控制器对网络流进行分类处理,同时计算每条数据流在调度过程中的带宽占用情况以减少数据链路碎片化,并优化DCN数据流量调度,从而实现网络负载均衡。实验结果表明,该方法能降低网络传输时延,提高链路利用率及负载均衡度。     

基于软件定义网络的数据中心自适应多路径负载均衡算法

针对传统多路径负载均衡算法无法有效地感知网络的运行状态、不能综合考虑链路的实时传输状态以及大多数算法缺少自适应性的问题,基于软件定义网络（SDN）的集中控制和全网管控思想,提出一种基于蜘蛛猴优化的SDN自适应多路径负载均衡算法（SMO-LBA）。首先,利用数据中心网络的感知能力来获取多路径的实时链路状态信息;然后,利用蜘蛛猴算法的全局探索和局部开采能力将链路空闲率作为每条路径的适应度值,并引入自适应权重对路径进行动态评估及更新;最后,寻找数据中心网络中链路占用率最小的路径,确定其为最优转发路径。选用胖树拓扑在Mininet平台上进行仿真实验,实验结果表明SMO-LBA可提高数据中心网络的吞吐量和平均链路利用率,实现网络自适应负载均衡。     

基于大流调度的软件定义数据中心网络负载均衡算法

传统负载均衡算法对数据中心网络中的大流进行调度时,会造成部分链路负载过重、网络整体负载不均衡等问题。将负载均衡问题转化为多商品流问题进行求解,结合软件定义网络集中控制的思想和数据中心网络的流量特征,提出一种基于大流调度的软件定义数据中心网络负载均衡算法。根据阈值将数据流划分为大流和小流,结合路径上大流分布度和可用负载度对大流进行重路由,以减小大流对网络负载均衡的影响。仿真实验表明,在流量大小分布不均衡的数据中心网络中,该算法与传统的等价多路径算法和基于全局最先匹配的动态流量调度算法相比,在平均对分带宽上获得了更大的提升,能够更好地实现数据中心网络的负载均衡。     

面向SDN数据中心网络最大概率路径流量调度算法

随着数据中心网络规模的迅速增长,网络带宽利用率低下导致的网络拥塞问题日益突出,通过负载均衡提高数据中心网络链路带宽利用率和吞吐量成为了研究热点.如何结合流量特征、链路状态和应用需求进行流量的合理调度,是实现网络链路负载均衡的关键.针对数据中心突发性强、带宽占用率高的大象流调度问题,提出一种面向SDN数据中心网络最大概率路径流量调度算法,算法首先计算出满足待调度流带宽需求所有路径,然后计算流带宽与路径最小链路带宽之间的带宽比,结合所有路径的带宽比为每一条路径计算路径概率,最后利用概率机制选择路径.算法不仅考虑了流带宽需求和链路带宽使用情况,而且全局地考虑了流调度和链路带宽碎片问题.实验结果表明,最大概率路径调度算法能够有效地缓解网络拥塞,提高带宽利用率和吞吐量,减少网络延迟,从而提高数据中心的整体网络性能和服务质量.     

基于流调度选择的DCN动态负载均衡算法

针对数据中心网络(data center network,DCN)动态调度导致的负载不均衡问题,提出了基于流调度选择的动态负载均衡(dynamic load balancing based on flow scheduling selection,DLBFSS)算法。该算法首先计算拥塞链路上各条大流的等价最短路径,并删除不满足流带宽需求的路径;然后计算剩余路径的可用吞吐量,选择可用吞吐量最大的路径作为最优调度路径;最后根据大流的带宽和最优路径的负载定义调度的拥塞概率,将拥塞概率作为大流调度选择的依据。实验结果表明,与传统ECMP（equal-cost multi-path）路由和现有大流调度算法相比,DLBFSS能够减小网络时延,提高流的带宽利用率,保证了更好的负载均衡。     

基于蚁群算法的SDN数据中心网络大象流调度研究

针对传统方法调度大象流时容易造成数据中心网络拥塞和负载不均衡等问题,提出一种基于蚁群算法的SDN（software defined network）数据中心网络流量调度算法ACO-SDN。对大象流调度问题建立整型线性规划ILP（integral linear programing）模型,优化目标为最小化最大链路利用率。通过重定义蚁群算法的参数和操作求解ILP模型,得到大象流重路由的最优路径。实验结果表明,与ECMP（equal-cost multi-path routing）和GFF（global first fit）流量调度算法相比,ACO-SDN算法降低了网络最大链路利用率,有效地提高了网络对分带宽。     

基于SDN的数据中心动态优先级多路径调度算法

随着云计算技术和分布式业务的发展,数据中心内部“东西向”大象流量激增,这部分大象流在调度不当的情况下容易发生碰撞,造成链路拥塞。本文提出一种基于软件定义网络（SDN）的动态优先级多路径调度算法（DPMS）。该算法根据数据中心流量的特点制定大象流和老鼠流调度模型,充分利用各网络节点间的冗余链路,提高资源利用率;并结合组表优化SDN架构中控制器和交换机的通信模式,降低了数据包处理时延。实验结果表明,相比ECMP和Hedera这2种调度策略,DPMS提高了网络吞吐量和链路利用率,减少了平均流完成时间,网络的整体性能有所提高。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.