IPv6环境下的子网划分

IPv4向IPv6过渡已经是必然的事情。从网络管理者的角度来看,或许网络出口并不是需要关注的重点——因为这一点上会有ISP的介入,内部网络的管理才是工作的重点。IPv6时代依旧离不开子网划分,然而IPv6相对于IPv4的变化绝不仅仅是加长了IP地址这么简单,原本的子网划分理念已经不能完全照搬到IPv6网络中。本文则着重于从IPv6相对于IPv4的革新来谈谈新环境下子网划分的问题,从而为有向IPv6过渡需求的网络管理者提供初步的参考。     

视频网格动态负载加权平滑均衡算法

为实现网格中视频资源服务的动态负载均衡,对一种动态负载加权均衡算法进行改进。利用监测与发现系统收集每台视频服务器的CPU利用率等主要负载参数,运用上述参数加权得到综合负载,对相邻时刻的负载做平滑处理以避免调度抖动。通过比较平滑后的动态负载值与服务器综合负载阈值进行动态调度,改变相应节点的负载,避免视频服务器间的负载失衡。实验结果表明,该算法能有效降低系统平均服务延迟时间并提高吞吐量,从而提升视频资源网格服务的整体性能。     

The Earth System Grid Federation: An open infrastructure for access to distributed geospatial data

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration that aims at developing the software infrastructure needed to facilitate and empower the study of climate change on a global scale. The ESGF’s architecture employs a system of geographically distributed peer nodes, which are independently administered yet united by the adoption of common federation protocols and application programming interfaces (APIs). The cornerstones of its interoperability are the peer-to-peer messaging that is continuously exchanged among all nodes in the federation; a shared architecture and API for search and discovery; and a security infrastructure based on industry standards (OpenID, SSL, GSI and SAML). The ESGF software stack integrates custom components (for data publishing, searching, user interface, security and messaging), developed collaboratively by the team, with popular application engines (Tomcat, Solr) available from the open source community. The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the entire Fifth Coupled Model Intercomparison Project (CMIP5) output used by the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and a suite of satellite observations (obs4MIPs) and reanalysis data sets (ANA4MIPs). This paper presents ESGF as a successful example of integration of disparate open source technologies into a cohesive, wide functional system, and describes our experience in building and operating a distributed and federated infrastructure to serve the needs of the global climate science community.     

Rough Problem Settings for ILP Dealing With Imperfect Data

This paper applies rough set theory to Inductive Logic Programming (ILP, a relatively new method in machine learning) to deal with imperfect data occurring in large real-world applications. We investigate various kinds of imperfect data in ILP and propose rough problem settings to deal with incomplete background knowledge (where essential predicates/clauses are missing), indiscernible data (where some examples belong to both sets of positive and negative training examples), missing classification (where some examples are unclassified) and too strong declarative bias (hence the failure in searching for solutions). The rough problem settings relax the strict requirements in the standard normal problem setting for ILP, so that rough but useful hypotheses can be induced from imperfect data. We give simple measures of learning quality for the rough problem settings. For other kinds of imperfect data (noise data, too sparse data, missing values, real-valued data, etc.), while referring to their traditional handling techniques, we also point out the possibility of new methods based on rough set theory.     

Urban Interactive

Valentina Croci profiles the work of entertainment design office Area/Code which foregrounds urban locations in its games. As Croci explains the approach of this NewYork-based partnership, which delivers sat nav-inspired gaming to the mobile phone, demonstrates an inherent understanding of the importance of the physical in enhancing the imaginary. Copyright © 2010 John Wiley & Sons, Ltd.     

内容网络及其关键技术

随着互联网的蓬勃发展．数据内容也海量增长．同时一些数据的重复分发情况也非常显著。介绍一种新的网络技术——内容网络．其主要目的是将内容分发到离用户尽可能近的地点，用来缩短传输距离、降低骨干网传输开销，提升客户体验。将研究内容网络及其关键技术，同时提出后续的研究方向。     

KDD中知识库智能接口的设计与实现

文章利用面向对象的编程技术,采用Delphi5.0语言,针对由不同数据库系统构成的知识库系统,实现了不同知识库系统的无缝连接,较好地解决了不同知识库系统的接口问题,为KDD中不一致知识的的通用处理奠定了坚实的基础。     

一种基于元数据的分布式数据源定位算法

随着Internet和数字图书馆这两种基础信息资源的大量涌现,用户在检索信息之前,如何选择合适的目标站点来提交查询,从而降低查询代价、提高查询效率,已经成为一个重要任务。这个问题更加一般的说法是“数据源定位”或“数据库发现”。元数据是关于数据的数据,数字图书馆中,每个数据文档由其元数据描述,元数据是数字图书馆管理、检索数据以及在各个层面上实现互操作的重要手段。文章提出了一种基于元数据的数据源发现算法,并在召回率、检索精度等方面对这种算法作了评价。     

模糊聚类分析在KDD中的应用研究

应用模糊聚类算法确定关键条件属性集，探索教师教学质量评估数据库中评估等级同评估项目之间的规则知识。