嵌入式TCP/IP协议栈的简化和优化

嵌入式TCP/IP协议网络是嵌入式系统的典型应用,其网络协议必须进行适当的简化和优化,以适应在可靠性、成本、功耗等方面的严格要求。结合嵌入式系统的一般特点,分析TCP/IP协议栈,提出在特定应用中嵌入式网络中如何选择TCP/IP协议栈的关键协议,进而提出协议栈的简化和优化方法。     

一种新型的基于IPTV网络的视频会话系统

基于IPTV网络的视频会话系统具有广阔的应用前景。研究并实现了一种基于IPTV网络的具有服务质量保证的新型视频会话系统,阐述了该系统的体系架构及业务流程,提出了适用于本视频会话系统的嵌入式IP机顶盒的体系架构,并针对嵌入式系统资源受限的特点进行了性能优化设计,特别提出了一种带宽自适应的QoS机制,充分保证视频会话应用在IPTV网络多业务环境下的用户体验。     

时间触发机制在工业以太网中的应用

本文针对工业以太网时间确定性方面的缺陷,提出了一种时间触发以太网架构,通过改进通信协议栈的结构来改变以太网的媒体访问策略,从而大大提高了整个网络的时间确定性。工业现场的设备使用时间触发以太网互连,不但可以满足各任务时间精确性,而且可以使现场的设备和Internet上的任意主机进行通信。     

远程监护系统中ZigBee网关的设计

ZigBee是一种新兴的无线通信技术,本文介绍了一种基于ZigBee的无线网关设计方法并应用到远程监护系统中。完成后的网关设备能实现数据从ZigBee无线传感器网络到互联网的转换,且有较好的通用性,有着广泛的应用前景。详述了该基于双MCU网关的硬件设计方案和在ZigBee协议与TCP/IP协议传输数据的软件编程思路。     

基于认证的IPv6地址自动分配

IPv6地址的自动配置技术实现了即插即用功能,但也对网络的安全带来了隐患。结合准入控制技术、在IPv6地址自动配置过程中加入认证机制,这既保留了IPv6地址的即插即用特性,又从源头上保证了接入网络的安全性。     

Dominance-based rough set approach and knowledge reductions in incomplete ordered information system

Many methods based on the rough set to deal with incomplete information systems have been proposed in recent years. However, they are only suitable for the incomplete systems with regular attributes whose domains are not preference-ordered. This paper thus attempts to present research focusing on a complex incomplete information system—the incomplete ordered information system. In such incomplete information systems, all attributes are considered as criterions. A criterion indicates an attribute with preference-ordered domain. To conduct classification analysis in the incomplete ordered information system, the concept of similarity dominance relation is first proposed. Two types of knowledge reductions are then formed for preserving two different notions of similarity dominance relations. With introduction of the approximate distribution reduct into the incomplete ordered decision system, the judgment theorems and discernibility matrixes associated with four novel approximate distribution reducts are obtained. A numerical example is employed to substantiate the conceptual arguments.     

HD/SHD still image database system and image distribution in broadband network applications

This paper focuses on a practical design for an efficient scalable image database and retrieval system over broadband networks. It describes a concrete solution for the implementation of HD/SHD (high-definition/super-high-definition) still image retrieval services which can be used in different applications. The structure of the complete system, consisting of a directory server, an image server, and MMI (man-machine interface) devices, has been presented, detailing each element and their corresponding functions. The desired HD/SHD image is displayed on the HD-PDP (plasma display panel) with the aid of image matching. The proposed system generates image index automatically, eliminating special skills in preparing index images and crucially reducing the processing time (from 35 min to 110 s), and does not use keywords. It has been also shown that these indices can be used for quite accurate image retrieval, i.e., the system provides high precision rates (currently up to 98%) to the user, eliminating troubles encountered in the image retrieval operations due to limitation on the user’s age, culture, knowledge, and languages.The broadband IP networks currently have a number of issues from the viewpoint of practical system operations, and so the requirements and issues needed for the networks are discussed from the viewpoint of in-service performance, differentiation among different types of services, secure connections, and so on, focusing on handling of HD/SHD still images.     

Evaluating MODIS data for mapping wildlife habitat distribution

Habitat distribution models have a long history in ecological research. With the development of geospatial information technology, including remote sensing, these models are now applied to an ever-increasing number of species, particularly those located in areas in which it is logistically difficult to collect habitat data in the field. Many habitat studies have used data acquired by multi-spectral sensor systems such as the Landsat Thematic Mapper (TM), due mostly to their availability and relatively high spatial resolution (30 m/pixel). The use of data collected by other sensor systems with lower spatial resolutions but high frequency of acquisitions has largely been neglected, due to the perception that such low spatial resolution data are too coarse for habitat mapping. In this study we compare two models using data from different satellite sensor systems for mapping the spatial distribution of giant panda habitat in Wolong Nature Reserve, China. The first one is a four-category scheme model based on combining forest cover (derived from a digital land cover classification of Landsat TM imagery acquired in June, 2001) with information on elevation and slope (derived from a digital elevation model obtained from topographic maps of the study area). The second model is based on the Ecological Niche Factor Analysis (ENFA) of a time series of weekly composites of WDRVI (Wide Dynamic Range Vegetation Index) images derived from MODIS (Moderate Resolution Imaging Spectroradiometer – 250 m/pixel) for 2001. A series of field plots was established in the reserve during the summer–autumn months of 2001–2003. The locations of the plots with panda feces were used to calibrate the ENFA model and to validate the results of both models. Results showed that the model using the seasonal variability of MODIS-WDRVI had a similar prediction success to that using Landsat TM and digital elevation model data, albeit having a coarser spatial resolution. This suggests that the phenological characterization of the land surface provides an appropriate environmental predictor for giant panda habitat mapping. Therefore, the information contained in remotely sensed data acquired with low spatial resolution but high frequency of acquisitions has considerable potential for mapping the habitat distribution of wildlife species.     

Distributing test cases more evenly in adaptive random testing

Adaptive random testing (ART) has recently been proposed to enhance the failure-detection capability of random testing. In ART, test cases are not only randomly generated, but also evenly spread over the input domain. Various ART algorithms have been developed to evenly spread test cases in different ways. Previous studies have shown that some ART algorithms prefer to select test cases from the edge part of the input domain rather than from the centre part, that is, inputs do not have equal chance to be selected as test cases. Since we do not know where the failure-causing inputs are prior to testing, it is not desirable for inputs to have different chances of being selected as test cases. Therefore, in this paper, we investigate how to enhance some ART algorithms by offsetting the edge preference, and propose a new family of ART algorithms. A series of simulations have been conducted and it is shown that these new algorithms not only select test cases more evenly, but also have better failure detection capabilities.     

Fourier methods for testing multivariate independence

Recently a power study of some popular tests for bivariate independence based on ranks has been conducted. An alternative class of tests appropriate for testing not only bivariate, but also multivariate independence is developed, and their small-sample performance is studied. The test statistics employ the familiar equation between the joint characteristic function and the product of component characteristic functions, and may be written in a closed form convenient for computer implementation. Simulations on a distribution-free version of the new test statistic show that the proposed method compares well to standard methods of testing independence via the empirical distribution function. The methods are applied to multivariate observations incorporating data from several major stock-market indices. Issues pertaining to the theoretical properties of the new test are also addressed.