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。     

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。     

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.     

基于组件的大数据分析服务平台

随着数据规模的快速增长,单机的数据分析工具已经无法满足需求。针对大数据的分析问题,设计并实现了一种基于组件的大数据分析服务平台Haflow。Haflow自定义了业务流程模型和可扩展的组件接口,组件接口支持各种异构工具的集成。系统接收用户定义的业务流程,将其翻译成执行流程实例,提交到Hadoop分布式集群上执行。Haflow是一个可扩展的、分布式的、支持异构分析工具的、面向服务的大数据分析服务平台。提出该平台有两重意义:一方面平台将与数据分析业务无关的工作封装起来,支持各种异构组件,以加快分析应用的开发速度;另一方面,平台后端使用Hadoop分布式系统来实现多任务的并发,从而提高应用的平均执行速度。     

基于位置范围的道路网skyline查询

随着无线通信和定位技术的发展,道路网skyline查询在基于位置的服务等方面越来越重要。考虑到现今道路网中位置隐私保护和定位设备的精度问题,用户在道路网上的位置通常用一个范围来表示。但是,已有的道路网skyline研究都是基于单一查询点。针对这一问题,研究了一种新的查询——基于位置范围的道路网skyline查询(RNS),提出了一种基于边界点替换的有效查询处理算法。另外,针对已有的道路网skyline查询中复杂的道路网距离计算对查询效率的影响问题,通过计算兴趣点在道路网上的有效skyline路段,将其与道路网信息融合,建立了道路网skyline模型。基于该模型设计了一种能有效支持RNS查询的道路网skyline索引SSR-tree,提出了基于索引的RNS查询处理算法。通过大量实验验证了所提方法的有效性,并比较了基于索引的算法在查询效率和精度上的提高。