Buffer losses vs. deadline violations for ABR traffic in an ATM switch: A computational approach

The B‐ISDN will carry a variety of traffic types: the Variable Bit Rate traffic (VBR), of which compressed video is an example, Continuous Bit Rate traffic (CBR), of which telemetry is an example, Data traffic, and Available Bit Rate traffic (ABR) that represents aggregate data traffic with very limited guarantees on quality. Of these, VBR and CBR have timing constraints and need synchronous bandwidth; data traffic is relatively delay insensitive. In this paper, we consider the VBR, Data and ABR traffic types and obtain the cumulative distribution function (cdf) of the queueing delay experienced by a burst of ABR traffic in the output buffer of an ATM switch. The cdf is used to trade off buffer loss probabilities against deadline violation probabilities through adjusting the buffer size and (delay) deadline values. Large buffers result in low losses but queueing delays can become excessive and cause a high level of deadline violations. Both losses and violations are detrimental and an operating point must be chosen to achieve a balance. In this paper we study the nature of the trade off. We develop a stochastic Petri net model assuming periodic burst arrivals for VBR and Poisson arrival processes for the Data and ABR traffic types at the burst level, and solve the model analytically (numerically) using a decomposition approach. This decomposition, along with the inherent decomposability of the tagged customer approach for obtaining the cdf opens up a possibility of carrying out fast computations using a parallel machine for selecting the operating point each time that a call is admitted. This revised version was published online in June 2006 with corrections to the Cover Date.     

Wireless data traffic: a decade of change

This article presents an overview of the most significant changes in wireless data traffic and its main driving forces throughout the past decade (1998?2008). The main axes of change are discussed: wireless technology, user population, and applications. Evolution of wireless technology realized a 200-fold increase in data rate, and facilitated a continuous enrichment of the traffic mix traversing legacy and modern wireless networks. New applications emerged, such as peer-to-peer file sharing, online gaming, and multimedia, establishing a trend of significant increase in traffic volume. User population has also increased and even saturated some markets. However, not all benefits of wireless technologies are equally exploited, with only a few users exercising high mobility or regularly enjoying multimedia services. Future indications include a requirement for either integration or interoperability of two mainstream wireless technologies, WiFi and cellular, as well as continuous user demand for more bandwidth, broader coverage, and better mobility support.     

Separation of air traffic by visual means: An estimate of the effectiveness of the see-and-avoid doctrine

Using the 1968 FAA near midair collision data and Howell's flight test data on visual detection of aircraft from other aircraft, an estimate is made of the effectiveness of the see-and-avoid doctrine as a function of closing speed in today's air traffic environment. It is estimated that at present about 95 percent of potential collisions are avoided at low closing speeds; this effectiveness of see and avoid falls to about 50 percent above 400 knot closing speed. Midair collisions are found to be primarily attributable to the failure by pilots to see the other aircraft in time to maneuver, and an estimate is given of the potential reduction in anticipated collision rates achievable with the use of pilot warning indicator systems of various degrees of effectiveness. The probability that a pilot reports an NMAC is found to increase as the closing speed of the encounter increases, but it also appears that pilots tend to underestimate the miss distance at the high closing speeds. The estimates made of the probability of successful maneuvers are in good agreement with the independent results of simulation experiments. The expected number of midair collisions in the various closing speed ranges, as predicted from the NMAC and Howell data, are in reasonable agreement with experience.     

TD-SCDMA网络分流GSM网络数据业务方案

GSM/TD-SCDMA双模终端的数据业务流量"倒流"GSM网络现象严重,使得GSM网络负荷压力加大,而TD-SCDMA网络利用率偏低.本文针对上述问题,提出了网络2G/3G互操作参数调整、网络控制的2G到3GPS小区重选以及新型双模终端的综合解决方案,实现TD-SCDMA分流GSM网络数据业务,均衡2G/3G双网协调...     

空管大数据治理方法研究

文章针对我国民航空中交通管理体系化、信息化、智能化发展对空管大数据深度应用的需求,在对空管关键业务数据、业务流程分析、研究的基础上,利用大数据分析和挖掘等技术,提出空管大数据治理的总体思路、治理框架、治理方法及数据质量管理体系,通过对空管大数据的深刻洞察,为我国民航事业的发展提供有力支撑。     

D-BIND: an accurate traffic model for providing QoS guarantees toVBR traffic

Variable bit-rate traffic that requires a bounded-delay network service is one of the most important types of traffic in future integrated services networks. We introduce a new deterministic traffic model called deterministic bounding interval-length dependent (D-BIND) to capture the important multiplexing properties of bursty streams. With the D-BIND model, clients specify their traffic to the network via multiple rate-interval pairs (R_k, I_k), where a rate R_k is a bounding or worst case rate over every interval of length I_k. The model captures the intuitive property that, over longer interval lengths, a source may be bounded by a rate lower than its peak rate and closer to its long-term average rate. We analyze the new model in the context of a deterministic service, and we quantify its performance benefits using a set of experiments with traces of MPEG-compressed video. We show that D-BIND's more accurate characterization of traffic streams leads to substantial improvements in network utilization as compared to previous traffic models     

一种新颖的面向数据流量特征的片上网络设计

片上网络中处理器核之间、处理器与缓存之间通信具有不同的数据流量特征,因此需要不同的网络带宽和网络拓扑结构。针对上述两种通信流量的差异,设计了一种异构非对称双片上网络,分别用于处理器核之间和处理器与缓存之间的通信,并且每个网络都针对占主导地位的数据流量类型进行了优化。实验结果表明,与传统的单片上网络和同构的双片上网络相比,该设计不仅具有网络延迟低、网络带宽高的优点,而且提升了系统的整体性能。     

基于大数据营销应用体系的流量经营研究

借助标签应用平台等大数据工具,构建“点-线-面-立体”大数据营销应用体系,通过分析客户特征和痛点、匹配个性化营销策略、部署客户偏好渠道,实现流量精准营销,持续刺激客户流量增长,提升市场营销的效率和精准性,培养全员的大数据营销能力。     

基于HBase的交通数据时空分块索引

智能交通领域快速发展带来的海量交通数据已难以通过传统关系型数据库及时处理。针对交通数据的分布特点与查询需求,提出了一种基于分布式数据库HBase的时空分块索引框架(STB-HBase),利用HBase行键设计结合二级索引的方式,解决数据在时空维度分布不均引起的热点问题,并设计出STB-HBase下的移动对象轨迹查询和时空范围查询算法。实验结果表明,STB-HBase对交通数据有良好的存储性能和查询效率。     

Shaping of traffic streams through data spacing

A traffic shaping algorithm, based on suitable spacing of data units, is proposed and validated both theoretically and by simulation. It ensures a “tight” upper bound to the queue-length distribution at subsequent multiplexing stages, being essentially an effective-rate-enforcement mechanism in the asymptotic regime. It does not presume any stationarity, homogeneity or Markovian property of the input streams     

应用数据挖掘技术的土建工程概算平台规划

在吸取工程造价计算实践经验和最新算法研究成果的基础上设计出一套应用数据挖掘技术的工程概算平台规划的总体架构,该平台用以计算土建工程概算,从而有效控制建设项目的投资.主要介绍了数据挖掘中的关键点,概括了建模时选择的算法及实现算法仿真的程序,并重点对基于C/S结构的土建工程的概算平台的规划进行了研究.     

NetCube: a comprehensive network traffic analysis model based on multidimensional OLAP data cube

Network traffic monitoring and analysis are essential for effective network operation and resource management. In particular, multidimensional analysis for long‐term traffic data is necessary for comprehensive understanding of the traffic trend and effective quality‐of‐service provision considering the extremely dynamic behavior of the current Internet, where various types of traffic occur from high‐speed network links and greatly increasing number of applications. However, only limited analysis results are provided, as the existing network traffic analysis tools and systems are developed and deployed focusing on their own specialized analysis purposes. Consequently, it is difficult to understand the network comprehensively and deeply, which increases the necessity for multilateral analysis of long‐term traffic data. In this paper, we propose a novel traffic analysis model for large volumes of Internet traffic accumulated over a long period of time. The NetCube, the proposed network traffic analysis model using online analytical processing (OLAP) on a multidimensional data cube, provides an easy and fast way to construct a multidimensional traffic analysis system for comprehensive and detailed analysis of long‐term traffic data by utilizing simple OLAP operations and powerful data‐mining techniques on various abstraction levels of traffic data to complete the analysis purpose. We validate the feasibility and applicability of the proposed NetCube traffic analysis model by implementing a traffic analysis system and applying it to our campus network. Copyright © 2012 John Wiley & Sons, Ltd.     

大数据环境下的网络流量异常检测研究

针对传统模型的网络流量异常检测正确率低,检测时间长的难题,设计了一种大数据环境下的网络流量异常检测模型。首先,对网络流量异常检测的研究现状进行分析,找到引起当前检测模型不足的原因;然后,采用HDOOP平台设计基于最小二乘支持向量机的网络流量异常检测模型;最后,在Maltab 2014平台下进行网络流量异常检测实验。实验结果表明,该模型可以准确对网络流量异常现象进行检测,获得了比其他模型更优的网络流量异常检测结果,具有更高的实际应用价值。     

车联网大数据下的交通信息服务研究

车辆网的发展和部署,以及结合近几年来快速发展的大数据处理技术和云计算技术,必然会持续性获取大量人、车、路、环境等交通参与方的多源基础信息。那么将车联网中获取的有效交通信息运用于交通管理、信息服务和车辆控制等智能交通领域,就可以达到人、车、路和环境之间的和谐统一,从而形成高效、准时、舒适、低碳的城市综合运输系统。文章首先阐述车联网大数据下的交通信息对交通信息特征、研究状况和系统结构;其次对交通服务信息的处理及发布方式进行研究;最后从系统分析设计的角度对大数据环境下车联网信息服务平台的总体解耦、技术架构和大数据应用框架等问题进行研究。     

Buffer and bandwidth allocation for TCP data traffic: experimental results

This paper discusses the dimensioning of buffers and the bandwidth allocation for data traffic in the ATM network. Data traffic is notoriously complex and bursty, making such dimensioning a difficult task. However, the COMBINE project, when dimensioning their InterWorking Units (IWUs), adopted a Poissonian packet arrival model, based upon the argument that burstiness at timescales higher than that of a packet arrival are a problem to be tackled by flow control at higher layers. This paper presents experimental results from the COMBINE testbed that show that this hypothesis was justified and that good TCP goodput was obtained based upon this dimensioning approach, due to TCP's ability to adapt to network congestion. However, it is also shown that it was the TCP algorithm that was ultimately responsible for controlling the packet loss ratio in the network and not the bandwidth allocation or buffer size. The results highlight the importance of taking into account the mutual influence between the ATM layer and the transport layer congestion control algorithms.     

Bayesian estimate of the doppler frequency shift with reduction of the data dimensionality

The paper considers the possibility of reducing the amount of calculations of the Bayesian estimate of the Doppler frequency shift and the initial phase of a quasi-deterministic signal observed in the presence of white-noise distortions due to introduction of the stage of reduction of the dimensionality of the observed data. The minimization of the loss of the Fisher information on the estimated parameter is used to control the correctness of the dimensionality reduction procedure; the estimation accuracy depends on this procedure. The computer simulation using test signals proves the possibility of a considerable reduction in the amount of calculations upon realization of Bayesian procedures for the same estimation accuracy.     

基于卡口数据的城市道路交通空间相关性分析

在短时交通流预测中,道路交通空间相关性是客观存在的.现有研究在度量道路交通空间相关性上,通常采用时间序列数据直接进行统计分析,或是假定一定距离内具有空间相关性等.但这些方式忽略了道路之间交通影响的空间异质性.在卡口数据中,由于车辆牌照的唯一性特性,不仅可以计算出研究路段的交通流时间序列,还能得到每辆车的行驶轨迹.本文通过车辆轨迹,得到流量转移权重矩阵和不同卡口数据量化的网络权重矩阵,构造一个新的网络权重矩阵,度量城市道路之间的空间相关性,然后进行短时交通流预测及效果比较,验证了方法的可行性和有效性.     

Method of data cleaning for network traffic classification

Network traffic classification aims at identifying the application types of network packets. It is important for Internet service providers （ISPs） to manage bandwidth resources and ensure the quality of service for different network applications However, most classification techniques using machine learning only focus on high flow accuracy and ignore byte accuracy. The classifier would obtain low classification performance for elephant flows as the imbalance between elephant flows and mice flows on Internet. The elephant flows, however, consume much more bandwidth than mice flows. When the classifier is deployed for traffic policing, the network management system cannot penalize elephant flows and avoid network congestion effectively. This article explores the factors related to low byte accuracy, and secondly, it presents a new traffic classification method to improve byte accuracy at the aid of data cleaning. Experiments are carried out on three groups of real-world traffic datasets, and the method is compared with existing work on the performance of improving byte accuracy. Experiment shows that byte accuracy increased by about 22.31% on average. The method outperforms the existing one in most cases.     

数据挖掘技术在交通事故分析中的应用

针对交通管理部门积累储存的大量的与交通管理和交通安全相关的数据资源和这些数据资源的使用情况,提出了以驾驶员总量为研究对象,利用数据挖掘技术的发展成果,挖掘这些数据资源的内在联系,服务于相关部门或机构的方法.     

大数据技术在智能交通中的应用分析

文章从大数据时代的优缺点及其给智能交通带来的变化、问题与挑战、智能交通需求与大数据的融合以及智能交通海量数据的平台搭建等方面作了简单阐述,以期对研究该领域的科研人员提供一些建议。