A wireless multimedia framework for the management of emergency situations in automotive applications: The AIDER system

Automotive applications would greatly benefit of multimedia telematic services for many purposes, from tourism and entertainment, to most important issues such as security and traffic management. Within this context, the AIDER system (AIDER is the acronym of Accident Information and Driver Emergency Rescue) is one of the most advanced multimedia mobile services targeted at emergency situations such as road accidents. The AIDER allows the interactive exchange of multimedia data (and in particular, audio, video and biomedical information) between the vehicle and a remote rescue centre, by using several different narrowband radio channels including cellular networks and satellite. In this paper an overview of the AIDER architecture is provided, focusing on the advanced video communication system.     

A divide-and-conquer recursive approach for scaling up instance selection algorithms

Instance selection is becoming more and more relevant due to the huge amount of data that is being constantly produced. However, although current algorithms are useful for fairly large datasets, scaling problems are found when the number of instances is of hundreds of thousands or millions. In the best case, these algorithms are of efficiency O(n ²), n being the number of instances. When we face huge problems, scalability is an issue, and most algorithms are not applicable. This paper presents a divide-and-conquer recursive approach to the problem of instance selection for instance based learning for very large problems. Our method divides the original training set into small subsets where the instance selection algorithm is applied. Then the selected instances are rejoined in a new training set and the same procedure, partitioning and application of an instance selection algorithm, is repeated. In this way, our approach is based on the philosophy of divide-and-conquer applied in a recursive manner. The proposed method is able to match, and even improve, for the case of storage reduction, the results of well-known standard algorithms with a very significant reduction of execution time. An extensive comparison in 30 datasets form the UCI Machine Learning Repository shows the usefulness of our method. Additionally, the method is applied to 5 huge datasets with from 300,000 to more than a million instances, with very good results and fast execution time.     

HAPPY:一种小型的对等存储系统

对等存储是网格技术的重要组成部分。文章围绕由华中科技大学信息存储系统实验室研制的对等存储系统(Hust dAta storage system lab Peer-to-Peer storage sYstem,HAPPY)，对其系统结构、工作原理、扩展性、容错性进行了介绍。     

Robust learning from bites for data mining

Some methods from statistical machine learning and from robust statistics have two drawbacks. Firstly, they are computer-intensive such that they can hardly be used for massive data sets, say with millions of data points. Secondly, robust and non-parametric confidence intervals for the predictions according to the fitted models are often unknown. A simple but general method is proposed to overcome these problems in the context of huge data sets. An implementation of the method is scalable to the memory of the computer and can be distributed on several processors to reduce the computation time. The method offers distribution-free confidence intervals for the median of the predictions. The main focus is on general support vector machines (SVM) based on minimizing regularized risks. As an example, a combination of two methods from modern statistical machine learning, i.e. kernel logistic regression and ε-support vector regression, is used to model a data set from several insurance companies. The approach can also be helpful to fit robust estimators in parametric models for huge data sets.     

Web应用系统的性能和伸缩性评价

性能和伸缩性是Web工程中的两个重要概念，从不同方面反映了Web应用系统提供响应时间的能力，但一直没有一个有效的评价方法。该文明确了性能和伸缩性的定义，提出了一个基于统计的性能和伸缩性评价模型，并给出了其在J2EE平台上的应用。该模型易于实现，可为Web应用系统的建设、维护以及升级改造提供可靠的决策依据。     

Lotus Domino／Notes与Microsoft Exchange办公自动化开发平台比较

Lotus Domino／Notes和Microsoft Exchange都是目前办公自动化系统的常用开发平台。两者在性能和功能上既有相同点又有一定的差别,这种差别是他们各自对办公自动化的发展策略不同的反映。本文主要论述Lotus与Microsoft在办公自动化发展策略上的差异,比较了各自在集成性、可扩展性及开发能力上的优劣,从中看出Lotus Domino／Notes的竞争优势。     

MPEG-4 FGS架构的视频编码器的研究与应用

文章介绍了一种基于MPEG-4的精细的可伸缩性编码(FGS)架构的视频编码器的软硬件架构。MPEG-4的FGS是为Internet视频流应用的需要最近发展出来的一种有效的视频编码方案。并结合FGS算法的特点,选择FGS算法中最适当的数据存储类型,节省了大量的外存带宽。     

一种新的实现区分服务的可扩展缓存管理算法

目前Internet网络中采用的缓存管理策略大多为丢尾(Drop tail)算法,并不能适应区分服务模型的要求;而RED及其改进算法CHOKe也不能提供公平性和相对优先级的保证。该文简要地分析了目前常见的缓存管理算法RED以及CHOKe所存在的不足,提出了一种基于区分服务模型的新型缓存管理算法D-CHOKe。该算法提供了公平性和相对优先级的保证,并且保持下现有IP网的可扩展性。仿真试验表明,该算法能够较好地满足区分服务的要求,为不同优先级的流分配不同的带宽。     

Fine-grained bulge-chasing kernels for strongly scalable parallel QR algorithms

The bulge-chasing kernel in the small-bulge multi-shift QR algorithm for the non-symmetric dense eigenvalue problem becomes a sequential bottleneck when the QR algorithm is run in parallel on a multicore platform with shared memory. The duration of each kernel invocation is short, but the critical path of the QR algorithm contains a long sequence of calls to the bulge-chasing kernel. We study the problem of parallelizing the bulge-chasing kernel itself across a handful of processor cores in order to reduce the execution time of the critical path. We propose and evaluate a sequence of four algorithms with varying degrees of complexity and verify that a pipelined algorithm with a slowly shifting block column distribution of the Hessenberg matrix is superior. The load-balancing problem is non-trivial and computational experiments show that the load-balancing scheme has a large impact on the overall performance. We propose two heuristics for the load-balancing problem and also an effective optimization method based on local search. Numerical experiments show that speed-ups are obtained for problems as small as 40 × 40 on two different multicore architectures.     

Supporting the Web with an information centric network that routes by name

Information Centric Networking (ICN) is a new paradigm in which the network layer provides users with content, instead of providing communication channels between hosts, and is aware of the name (or identifiers) of the contents. A fundamental ICN operation is the routing of content requests towards a node that is able to provide the requested content. To meet this goal, different routing architectures have been proposed so far.