A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

I3WSN: Industrial Intelligent Wireless Sensor Networks for indoor environments

Sensor Web Enablement (SWE) technologies have been successfully applied to a great variety of outdoor scenarios but, in practical terms, little effort has been applied for indoor environments, and even less in the field of industrial applications. This article presents an intelligent SWE application for an indoor and industrial scenario, with the aim of improving and increasing the levels of human safety. The base low-level architecture is built on top of wireless sensor networks (WSN) connected to a Sensor Observation Service (SOS). Higher layers in the architecture include services that make real time decisions based on the collected data. Both simulation and experimental results are presented. The paper shows the viability of our approach in terms of performance, scalability, modularity and safety.     

Semantic-based QoS management in cloud systems: Current status and future challenges

Cloud Computing and Service Oriented Architectures have seen a dramatic increase of the amount of applications, services, management platforms, data, etc. gaining momentum for the necessity of new complex methods and techniques to deal with the vast heterogeneity of data sources or services. In this sense Quality of Service (QoS) seeks for providing an intelligent environment of self-management components based on domain knowledge in which cloud components can be optimized easing the transition to an advanced governance environment. On the other hand, semantics and ontologies have emerged to afford a common and standard data model that eases the interoperability, integration and monitoring of knowledge-based systems. Taking into account the necessity of an interoperable and intelligent system to manage QoS in cloud-based systems and the emerging application of semantics in different domains, this paper reviews the main approaches for semantic-based QoS management as well as the principal methods, techniques and standards for processing and exploiting diverse data providing advanced real-time monitoring services. A semantic-based framework for QoS management is also outlined taking advantage of semantic technologies and distributed datastream processing techniques. Finally a discussion of existing efforts and challenges is also provided to suggest future directions.     

A comprehensive approach to evaluating watershed models for predicting river flow regimes critical to downstream ecosystem services

Selection of strategies that help reduce riverine inputs requires numerical models that accurately quantify hydrologic processes. While numerous models exist, information on how to evaluate and select the most robust models is limited. Toward this end, we developed a comprehensive approach that helps evaluate watershed models in their ability to simulate flow regimes critical to downstream ecosystem services. We demonstrated the method using the Soil and Water Assessment Tool (SWAT), the Hydrological Simulation Program–FORTRAN (HSPF) model, and Distributed Large Basin Runoff Model (DLBRM) applied to the Maumee River Basin (USA). The approach helped in identifying that each model simulated flows within acceptable ranges. However, each was limited in its ability to simulate flows triggered by extreme weather events, owing to algorithms not being optimized for such events and mismatched physiographic watershed conditions. Ultimately, we found HSPF to best predict river flow, whereas SWAT offered the most flexibility for evaluating agricultural management practices.     

C#利用Web Service编程接口实现动态天气预报

许多政府或企业网站除展示与本单位密切相关的信息外,往往也集成一些小的功能性的、与用户日常生活密切相关的,类似于提供火车时刻表、天气预报等辅助信息,采用C#利用Web Service提供的编程接口实现了实时天气预报功能,并能根据访问者所在地自动提供其相关的天气信息。     

基于SOA的智能航运数据服务平台研究

为了实现全国范围的内河航运数据共享,提高我国内河航运的管理水平,需要一种稳定可靠、松耦合的数据共享方式。针对当前的内河航运数据共享需求,并根据当前我国各省的内河航运信息化建设的实际情况,参考国内外成熟的理论基础,提出了基于SOA的数据共享体系,从而实现多节点的关键数据实时共享的应用场景。通过这种方式可以实现内河航运数据共享服务,满足航运信息服务的要求,并适应今后不断增长的共享节点及共享压力。     

虚拟化集群技术在消防业务中的应用

通过分析目前消防业务信息系统运维工作现状,将服务器虚拟化集群技术引用到消防业务系统运维工作中,大大提升系统服务器运行性能,更好地实现负载均衡,确保系统稳定可靠运行。     

基于随机网络演算的网络服务质量分析

为了提高网络的服务质量,提出一种基于随机网络演算的网络服务质量分析方法。首先推导出有效的端到端积压和时延边界,使到达流通过的节点数量呈线性增长;然后引入有效带宽和有效容量以延长到达流和服务进程的随机信息保留时间,可以更有效地计算端到端随机性能值;最后采用数据进行仿真实验,测试该方法的性能。结果表明,相对与其他网络服务质量分析方法,随机网络演算方法提高了网络的服务质量。     

Retaining and attracting users in social networking services: An empirical investigation of cyber migration

Users are the most critical strategic resource of any online social networking service (SNS). This paper offers strategic recommendations for SNS providers based on an empirical study exploring why users switch from a primary SNS to others. We first identify important characteristics that combine to distinguish SNSs from conventional information systems, then develop a “cyber migration” research model that includes push, pull and mooring factors which influence user intention to switch from one SNS to another. Findings from a field survey of 180 users reveal four significant factors that promote switching: dissatisfaction with socialization support, dissatisfaction with entertainment value, continuity cost, and peer influence. Strategies grounded in these factors are suggested for SNS providers to better attract and retain users.