Multidimensional data modeling for location-based services

With the recent and continuing advances in areas such as wireless communications and positioning technologies, mobile, location-based services are becoming possible.Such services deliver location-dependent content to their users. More specifically, these services may capture the movements and requests of their users in multidimensional databases, i.e., data warehouses, and content delivery may be based on the results of complex queries on these data warehouses. Such queries aggregate detailed data in order to find useful patterns, e.g., in the interaction of a particular user with the services.The application of multidimensional technology in this context poses a range of new challenges. The specific challenge addressed here concerns the provision of an appropriate multidimensional data model. In particular, the paper extends an existing multidimensional data model and algebraic query language to accommodate spatial values that exhibit partial containment relationships instead of the total containment relationships normally assumed in multidimensional data models. Partial containment introduces imprecision in aggregation paths. The paper proposes a method for evaluating the imprecision of such paths. The paper also offers transformations of dimension hierarchies with partial containment relationships to simple hierarchies, to which existing precomputation techniques are applicable.Received: 28 September 2002, Accepted: 5 April 2003, Published online: 12 August 2003Edited by: J. Veijalainen Correspondence to: I. Timko     

面向智慧城市的3维城市在线可视化

目的 3维城市可视化是智慧城市信息显示的基础,对城市信息的实时准确传递起着重要作用。而现有的3维城市可视化方法和系统存在两点局限性:一是数据模型不适合于海量建筑物显示;二是对整个城市采用单一绘制方式,而建筑物的纹理、结构、高度等特征相似,绘制结果容易引起视觉混淆,为此提出一种基于人类感知理论的3维城市在线可视化技术。方法在预处理阶段,系统采用建筑综合算法建立3维城市建筑物的多分辨率表示;在运行时刻,系统根据用户交互,自适应选择建筑物相应的层次进行显示。结果采用几个3维城市数据对系统进行了测试,实验结果证明,该系统有效地提高了3维城市绘制效率。Leverkusen城市的5 530座建筑物,绘制效率达到19.4帧/s。结论基于感知的3维城市多分辨率表示,有效提高了3维城市系统的显示效率以及用户获取信息的效率,同时提高了用户的交互效率。     

Improving data perturbation testing techniques for Web services

The widespread use of service-oriented architectures (SOAs) and Web services in commercial software requires the adoption of development techniques to ensure the quality of Web services. Testing techniques and tools concern quality and play a critical role in accomplishing quality of SOA based systems. Existing techniques and tools for traditional systems are not appropriate to these new systems, making the development of Web services testing techniques and tools required. This article presents new testing techniques to automatically generate a set of test cases and data for Web services. The techniques presented here explore data perturbation of Web services messages upon data types, integrity and consistency. To support these techniques, a tool (GenAutoWS) was developed and applied to real problems.     

Recommender systems for smart cities

Among other conceptualizations, smart cities have been defined as functional urban areas articulated by the use of Information and Communication Technologies (ICT) and modern infrastructures to face city problems in efficient and sustainable ways. Within ICT, recommender systems are strong tools that filter relevant information, upgrading the relations between stakeholders in the polity and civil society, and assisting in decision making tasks through technological platforms. There are scientific articles covering recommendation approaches in smart city applications, and there are recommendation solutions implemented in real world smart city initiatives. However, to the best of our knowledge, there is not a comprehensive review of the state of the art on recommender systems for smart cities. For this reason, in this paper we present a taxonomy of smart city features, dimensions, actions and goals, and, according to these variables, we survey the existing literature on recommender systems. As a result of our survey, we do not only identify and analyze main research trends, but also show current opportunities and challenges where personalized recommendations could be exploited as solutions for citizens, firms and public administrations.     

A network for digital data services

British Telecom is planning the introduction of an integrated services digital network, designed to carry data, text and voice. The Kilostream services will provide a dedicated data network that will support synchronous data transmission at datarates from 2 400 bit/s to 48 kbit/s, using both X.21 and X.21bis customer interfaces. The paper examines the planning of the system, equipment realization and the network applications being considered. Future developments of the Kilostream concept are also discussed.     

TWC LOGD: A portal for linked open government data ecosystems

International open government initiatives are releasing an increasing volume of raw government datasets directly to citizens via the Web. The transparency resulting from these releases not only creates new application opportunities but also imposes new burdens inherent to large-scale distributed data integration, collaborative data manipulation and transparent data consumption. The Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI) has developed the Semantic Web-based TWC LOGD portal to support the deployment of linked open government data (LOGD). The portal is both an open source infrastructure supporting linked open government data production and consumption and a vibrant community portal that educates and serves the growing international open government community of developers, data curators and end users. This paper motivates and introduces the TWC LOGD Portal and highlights innovative aspects and lessons learned.     

Conceptual data modeling for realizing context-aware services

Recently, context-aware applications, which provide customized services using personalized contextual information, have gained much attention. However, core IT technologies for realizing context-aware services are not sufficient to support the actual development of context-aware applications. Especially, it is very hard to find studies on context-aware data modeling that can provide different responses even for the same information according to users’ situation. In practice, most context-aware services are managing contextual information in the phase of application development in a rather ad-hoc way. Unfortunately, this approach has an obvious limitation of expansibility when the amount of rapidly increasing contextual information is considered. In this paper, we first define the concept of contextual dependency among data objects. Second, we provide a context-aware data modeling methodology for modeling contextual information into the Entity-Relationship Diagram (ERD, for short) based on contextual dependency. Finally, we design a simple scenario for context-aware services, construct an ERD from the scenario based on the discovered design rules, and implement a prototype of the service.     

Profit-driven scheduling for cloud services with data access awareness

Resource sharing between multiple tenants is a key rationale behind the cost effectiveness in the cloud. While this resource sharing greatly helps service providers improve resource utilization and increase profit, it impacts on the service quality (e.g., the performance of consumer applications). In this paper, we address the reconciliation of these conflicting objectives by scheduling service requests with the dynamic creation of service instances. Specifically, our scheduling algorithms attempt to maximize profit within the satisfactory level of service quality specified by the service consumer. Our contributions include (1) the development of a pricing model using processor-sharing for clouds (i.e., queuing delay is embedded in processing time), (2) the application of this pricing model to composite services with dependency consideration, (3) the development of two sets of service request scheduling algorithms, and (4) the development of a prioritization policy for data service aiming to maximize the profit of data service.     

基于OGC数据服务的空间信息处理服务平台

设计了基于OGC数据服务的空间信息处理服务平台。平台封装了现有的开源GIS软件包含的丰富的空间信息处理功能,对用户提供在线的OGC-WPS服务。较传统处理平台不同的是,平台以符合OWS协议框架的空间数据服务(WFS、WMS和WCS)作为空间数据层,极大方便了开放地理信息在用户之间的共享和互操作。最后,开发了原型系统并利用互联网上的开放地理信息服务作为数据源进行测试,证明了平台及其方案的可行性和实用性。     

Semantics,intelligent processing and services for big data

With the continuous increase of data, scaling up to unprecedented amounts, generated by Internet-based systems, Big Data has emerged as a new research field, coined as “Big Data Science”. The core of Big Data Science is the extraction of knowledge from data as a basis for intelligent services and decision making systems, however, it encompasses many research topics and investigates a variety of techniques and theories from different fields, including data mining and machine learning, information retrieval, analytics, and indexing services, massive processing and high performance computing. Altogether the aim is the development of advanced data-aware knowledge based systems.This special issue presents advances in Semantics, Intelligent Processing and Services for Big Data and their applications to a variety of domains including mobile computing, smart cities, forensics and medicine.     

基于PKI/CA的数据服务安全系统研究

数据服务是获取信息的重要方式,而安全性和可靠性是提供数据服务的重要前提.禁核试北京国家数据中心是我国禁核试核查相关监测数据的收集、存储、分析和处理中心,为实现其数据服务的安全保障,针对该系统进行了安全风险评估;设计和实现了基于PKI/CA技术的用户身份认证、访问控制机制的数据服务安全认证系统,并给出了数据安全服务的实现流程;针对所实现的数据服务安全系统,制定了相应的安全保障策略.     

利用Web Services技术构建开放式数据挖掘系统

提出了一种新颖的数据挖掘系统的体系结构,该结构把SOA与传统的挖掘系统结构相结合.在此体系结构的基础上,实现了一个开放式挖掘系统,能够动态集成挖掘算法.将该系统应用于福州地热资源的数据挖掘中,结果证明通过将WebServices技术引入数据挖掘系统的构建中,能大大增强挖掘系统的功能.     

Mining urban data (part A)

Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens׳ quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new inter-disciplinary field of research. This article introduces the first part of a special issue on the topic ‘Mining Urban Data’ published in the journal Information Systems.     

基于领域本体的数据挖掘服务发现算法

随着数据库的广泛应用,数据挖掘技术面临数据的海量化、分布化问题。采用面向服务的架构构造数据挖掘系统是解决该问题的方法之一。提出一种基于领域本体的数据挖掘服务发现算法,通过引入领域知识,定义数据挖掘本体,有效地解决了数据挖掘服务发现问题。首先给出了结合领域知识的数据挖掘服务发现框架,提出了数据挖掘方法本体和质量本体的定义,并给出了根据领域知识及用户需求进行数据挖掘服务发现的算法,为数据挖掘服务选择提供了较为完善的方案。     

Visual data security and management for smart cities

This paper proposes a method to manage and utilize image and video data effectively in a smart city. Applying digital watermarking techniques, a framework for visual data security and management for smart cities is presented. In the framework, a reversible fragile or semi-fragile watermark embedded into the visual data is used to ensure trusted acquisition. Moreover, reversible metadata watermarks carrying information such as identification and other properties data is used to assist visual data management. A solution for tracing users on a large scale is presented using reversible watermarking.     

Adaptive and context-aware service composition for IoT-based smart cities

Smart Cities are advancing towards an instrumented, integrated, and intelligent living space, where Internet of Things (IoT), mobile technologies and next generation networks are expected to play a key role. In smart cities, numerous IoT-based services are likely to be available and a key challenge is to allow mobile users perform their daily tasks dynamically, by integrating the services available in their vicinity. Semantic Service Oriented Architectures (SSOA) abstract the environment’s services and their functionalities as Semantic Web Services (SWS). However, existing service composition approaches based on SSOA do not support dynamic reasoning on user tasks and service behaviours to deal with the heterogeneity of IoT domains. In this paper, we present an adaptive service composition framework that supports such dynamic reasoning. The framework is based on wEASEL, an abstract service model representing services and user tasks in terms of their signature, specification (i.e., context-aware pre-conditions, post-conditions and effects) and conversation (i.e., behaviour with related data-flow and context-flow constraints). To evaluate our composition framework, we develop a novel OWLS-TC4-based testbed by combining simple and composite services. The evaluation shows that our wEASEL-based system performs more accurate composition and allows end-users to discover and investigate more composition opportunities than other approaches.     

面向汽车产业链的云服务平台数据交换研究

针对汽车产业链大规模企业群的多源异构数据交换需求,提出了基于第三方云服务平台的数据交换解决方案。在分析数据交换交互关系的基础上,构建了一套通用的第三方 Web 服务数据交换授权认证机制。为解决数据交换内容动态可变的难题,设计了一套柔性化、动态可配置的数据交换规则框架。通过分析数据交换状态转移模型,研究了云服务平台与整车制造企业的数据交换过程体系。分析了交换过程的数据同步性与一致性问题,并采用算法给出了级联耦合关系数据实体的处理方式,保障了关联数据交换的完整性。应用表明研究成果解决了云服务平台与多源异构数据源的数据交换问题,支撑了汽车产业链大规模企业群的多业务协同信息交互。     

A secure re‐encryption scheme for data services in a cloud computing environment

Cloud computing as a promising technology and paradigm can provide various data services, such as data sharing and distribution, which allows users to derive benefits without the need for deep knowledge about them. However, the popular cloud data services also bring forth many new data security and privacy challenges. Cloud service provider untrusted, outsourced data security, hence collusion attacks from cloud service providers and data users become extremely challenging issues. To resolve these issues, we design the basic parts of secure re‐encryption scheme for data services in a cloud computing environment, and further propose an efficient and secure re‐encryption algorithm based on the EIGamal algorithm, to satisfy basic security requirements. The proposed scheme not only makes full use of the powerful processing ability of cloud computing but also can effectively ensure cloud data security. Extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security model. Copyright © 2015 John Wiley & Sons, Ltd.     

基于知识网格服务的分布式数据挖掘研究

广域网中存在地理上分布的海量的各种数据,分析和处理这些数据需要利用高性能的分布式并行处理系统,网格能够满足这种要求.知识网格就是使用基本的网格服务(通信服务、信息服务、授权服务和资源管理服务)去建立特定的分布式并行知识发现工具和服务.结合知识网格特点,讨论了知识网格的体系结构和支持知识挖掘应用的服务集.运用分布式数据挖掘的元学习模型,给出了利用知识网格提供的知识挖掘服务实现分布式数据挖掘的过程.     

m-Brand loyalty and post-adoption variations for the mobile data services: Gender differences

This paper uses the value brand model in an attempt to determine the factors affecting post-adoption intentions through brand loyalty for the mobile data services. Data were collected online from 1266 respondents. The structural equation modeling was used to test the research model. The results show that post-adoption intentions are directly influenced by intangible attributes. Product deliverables and intangible attributes indirectly affect post-adoption intentions via m-brand loyalty. However, the results of current research do not show any effects of price on post-adoption intentions. The results also show genders differences in post-adoption intentions. Practical suggestions are provided. This paper advances our knowledge of post-adoption variations in business–consumer contexts and mobile business from the perspectives of utilitarian and non-utilitarian values of the mobile data services. This paper also contributes to the theory of post-adoption by offering across-gender examination.