Thirty years (and more) of databases

This paper outlines the historical development of data management systems in order to identify the key issues for successful systems. It identifies the need for data independence and the embedding of structural and behavioural semantics in the database as key issues in the development of modern systems. Hierarchical, Network, Relational, Object-oriented and Object-relational data management systems are reviewed. A short summary of related research is given. The paper concludes with some speculation on the future directions that database technology might take.     

Distributed real time database systems: background and literature review

Today’s real-time systems (RTS) are characterized by managing large volumes of dispersed data making real-time distributed data processing a reality. Large business houses need to do distributed processing for many reasons, and they often must do it in order to stay competitive. So, efficient database management algorithms and protocols for accessing and manipulating data are required to satisfy timing constraints of supported applications. Therefore, new research in distributed real-time database systems (DRTDBS) is needed to investigate possible ways of applying database systems technology to real-time systems. This paper first discusses the performance issues that are important to DRTDBS, and then surveys the research that has been done so far on the issues like priority assignment policy, commit protocols and optimizing the use of memory in non-replicated/replicated environment pertaining to distributed real time transaction processing. In fact, this study provides a foundation for addressing performance issues important for the management of very large real time data and pointer to other publications in journals and conference proceedings for further investigation of unanswered research questions.     

Data management issues and trade-offs in CSCW systems

Substantial interest has developed in recent years in building computer systems that support cooperative work among groups without the need for physical proximity. This paper examines some of the difficult data management issues in designing systems for computer-supported cooperative work (CSCW). Specifically, we consider an example CSCW system to support large-scale team science over the Internet: the Collaboratory Builder's Environment. We discuss the issues of managing shared data in such systems, reducing information overload and providing group awareness and access control. We discuss several promising approaches to these issues. We point out where a significant gap remains in addressing the requirements of such systems and where designers have to make design trade-offs that can be difficult to evaluate. Finally, we discuss several open issues for future work     

融合信任关系和用户项目二部图的推荐算法

传统冷启动和数据稀疏性问题是推荐系统面临的两大难题。现有的大多数基于矩阵分解的推荐方法将用户孤立对待,忽略了用户之间的信任关系,从而导致推荐性能低效。提出一种融合信任关系和用户项目二部结构的矩阵分解推荐方法。该方法在对评分矩阵进行分解的基础上,加入用户信任关系和用户项目二部图结构信息,采用梯度下降算法训练模型参数。Epinions数据集上的对比实验表明,该方法有效提高了推荐系统的准确性和可靠性,尤其在冷启动和稀疏数据情况下,其推荐精度明显优于传统的推荐方法。     

Issues in Hypertext Interchange

An important area of hypertext research focuses on the establishment of reference models and standards. In addition to defining the essential elements of hypertext systems, these standards can be elaborated as data structures and used as an intermediate format for hypertext interchange. The resulting interchange format is then used by a set of program modules which perform hypertext interchange between existing hypertext systems. This paper discusses the major issues in static and dynamic interchange of hypertexts. Definitions, methodology and goals of hypertext interchange are given. Static issues discussed include: ideal mappings, node size, node contents, multiple destinations, overlapping anchors, link directionality, partial hypertexts, system attributes and other attributes. Dynamic issues discussed include: system support, access to remote systems, identical remapping and partial hypertexts. Practical solutions to these issues are given where possible. A case study discusses the results of a research project that used the Dexter Hypertext Reference Model as the intermediate format in the transfer of hypertexts from Intermedia to KMS. An overview of the Dexter model is given and the Dexter interchange format, an implementation of the data modelling aspects of the Dexter model, is described. Issues and difficulties with hypertext interchange that arose in this implementation are presented and discussed. A list of open research issues concludes the paper.     

大规模网络存储系统的数据布局策略研究

如何有效地对数据进行布局是大规模网络存储系统面临的重大挑战,需要公平、冗余、自适应、高可靠以及高可用的数据布局策略.根据大规模网络存储系统体系结构的发展,详细介绍了P2P系统、SAN存储系统以及对象存储系统的数据布局策略,最后总结和比较了各种布局策略的优缺点,并指出基于数据重要性以及访问热度的数据布局策略等是未来可能的研究方向.     

融合信任关系和有用性评价的矩阵分解推荐方法

冷启动和数据稀疏性问题是推荐系统面临的两大难题。现有的大多数基于矩阵分解的推荐方法将用户孤立对待,忽略了用户之间的信任关系,导致推荐性能较低。提出一种融合信任关系和有用性评价的矩阵分解推荐方法。该方法在对评分矩阵进行概率分解的基础上,加入有用性评价和用户信任关系,采用交替最小二乘法训练模型参数。Epinions和Ciao数据集上的对比实验表明,所提方法有效提高了推荐系统的准确性和可靠性,尤其存在冷启动用户时,该方法的推荐精度明显优于传统的推荐方法。     

Issues in the design of studies to test the effectiveness of stereoimaging

Recently, there has been a great increase in interest in using three dimensional stereoscopic displays to provide viewers with realistic 3D views of objects of interest. Some applications where stereoscopic displays are becoming popular include medical visualization, visualization of meteorological data, and various virtual reality applications. To quantify the effectiveness of stereoscopic systems over conventional monoscopic systems, well-designed experiments and data analysis methods are necessary. This task requires the combined effort of application scientists and experts in experimental design. Lack of interdisciplinary collaboration is a primary weakness of many stereoscopic display studies, resulting in the neglect of many important but subtle experimental issues. In this paper, we discuss specific issues that arise in the design of studies to determine the effectiveness of digital stereo imagery. Issues concerning statistical analysis of the experimental data are also discussed. References to related literature from engineering, computer graphics, and psychophysics are given. The issues developed herein provide a guideline for the design of studies to compare observer performance when using different imaging modalities     

Spatial Data Handling for ITS: Perspective, Issues and Approaches

This paper studies problems related to spatial data handling in intelligent transportation systems (ITS) and it investigates solution approaches. The discussion focuses on three areas: (1) data management and processing, (2) dynamic data integration, and (3) data exchange and communications. For data management and processing, the paper considers the approach of the combined use of GIS and database management systems (DBMS). The framework under which GIS and DBMS are integrated and the interoperability requirements related to this framework are discussed. Unified location referencing systems, location referencing message specification, and ITS datum are major strategies proposed to address problems arising from dynamic data integration in ITS applications. The paper provides a review on the research associated with the development of these strategies and recommends the use of reference maps in places where data collection or reconciliation efforts can be coordinated. To facilitate data exchange and communications, the paper investigates the use of data dictionaries, data coding, and data models. Key issues related to their development are identified, and potential approaches to address these issues are suggested.     

The models and structure of onboard measurements of three-dimensional physical fields

The airborne measurement systems of geophysical fields are considered. The applicability of such systems in navigation and geophysics is analyzed. The existing gravimetric, magnetometric and electromagnetic systems are briefly overviewed. The structure of the airborne measurement systems of geophysical fields and the associated mathematical models are discussed in detail. Finally, the issues of data processing are studied and the solution approaches to the ill-posed problems are described.     

Aeronautical communication transition from analog to digital data: A network security survey

The objective of this paper is to present a comprehensive survey of security challenges in aeronautical data communication networks. The civil aviation industry is currently going through an evolution of the air traffic management system. The aviation communication technologies are progressively shifting towards the use of digital data instead of analog voice for traffic control, airline business, and passenger onboard entertainment systems. This paper illustrates the cause-to-effect chain link starting from the modernization of the aeronautical communication systems and leading to the network security concern in the civil aviation. The general threats to air–ground communication are depicted and then categorized. The paper gives an overview of the civil aviation industry efforts for securing the future aeronautical data communications. The security mechanisms and protocols proposed for this purpose are discussed. Open research issues and challenges that have to be addressed in the security of current and future aeronautical data communication networks are presented in detail. The paper concludes with some improvement directions which can help to address those security issues. This survey can be used as a reference guide to first understand the factors that urge both the research community and the aviation industry to be concerned about network security in future aeronautical data communications. Also, it can be used as a first reading to have a global overview of network security issues, challenges and potential solutions in air–ground communication networks.     

P2P持久存储研究

P2P（peer-to-peer）的组织模式已经成为新一代互联网应用的重要形式,它为应用带来了更好的扩展性、容错性和高性能.P2P存储系统一直是研究界所关注的热点,被认为是P2P最具前途的应用之一.数据的持久存储是制约P2P存储系统发展的关键问题,也是其研究的难点.综述了P2P存储系统及数据持久存储相关技术的研究现状.首先概述了P2P存储系统的基本技术组成及其在不同应用环境中的优势,并介绍了数据冗余、数据分发、错误检测和冗余数据维护等多种持久存储的基本技术.在一个P2P存储系统研究框架下,介绍了目前知名的P2P存储系统及其使用的持久存储技术.对各种技术进行了详细综述和对比讨论,分析了各种技术的适应环境及优劣,指出了存在的问题和未来研究的方向.     

Consolidated cluster systems for data centers in the cloud age: a survey and analysis

In the cloud age, heterogeneous application modes on large-scale infrastructures bring about the challenges on resource utilization and manageability to data centers. Many resource and runtime management systems are developed or evolved to address these challenges and relevant problems from different perspectives. This paper tries to identify the main motivations, key concerns, common features, and representative solutions of such systems through a survey and analysis. A typical kind of these systems is generalized as the consolidated cluster system, whose design goal is identified as reducing the overall costs under the quality of service premise. A survey on this kind of systems is given, and the critical issues concerned by such systems are summarized as resource consolidation and runtime coordination. These two issues are analyzed and classified according to the design styles and external characteristics abstracted from the surveyed work. Five representative consolidated cluster systems from both academia and industry are illustrated and compared in detail based on the analysis and classifications. We hope this survey and analysis to be conducive to both design implementation and technology selection of this kind of systems, in response to the constantly emerging challenges on infrastructure and application management in data centers.     

数据复制与一致性

数据复制是分布式数据库和数据仓库中常用的方法,以提高数据的可用性和系统的性能。文中介绍了在数据库系统中广泛使用的数据复制方法,分析了其优缺点和适用的范围,重点讨论了异步复制方法中的一致性恢复、一致性偏离的度量和数据存取的限制等问题,给出了数据复制策略的评价目标。     

What are mobile developers asking about? A large scale study using stack overflow

The popularity of mobile devices has been steadily growing in recent years. These devices heavily depend on software from the underlying operating systems to the applications they run. Prior research showed that mobile software is different than traditional, large software systems. However, to date most of our research has been conducted on traditional software systems. Very little work has focused on the issues that mobile developers face. Therefore, in this paper, we use data from the popular online Q&A site, Stack Overflow, and analyze 13,232,821 posts to examine what mobile developers ask about. We employ Latent Dirichlet allocation-based topic models to help us summarize the mobile-related questions. Our findings show that developers are asking about app distribution, mobile APIs, data management, sensors and context, mobile tools, and user interface development. We also determine what popular mobile-related issues are the most difficult, explore platform specific issues, and investigate the types (e.g., what, how, or why) of questions mobile developers ask. Our findings help highlight the challenges facing mobile developers that require more attention from the software engineering research and development communities in the future and establish a novel approach for analyzing questions asked on Q&A forums.     

Trigger inheritance and overriding in an active object databasesystem

An active database is a database in which some operations are automatically executed when specified events happen and particular conditions are met. Several systems supporting active rules in an object oriented data model have been proposed. However, several issues related to the integration of triggers with object oriented modeling concepts have not been satisfactorily addressed. We discuss issues related to trigger inheritance and refinement in the context of the Chimera active object oriented data model. In particular, we introduce a semantics for an active object language that takes into account trigger inheritance and supports trigger overriding. Moreover, we state conditions on trigger overriding ensuring that trigger semantics is preserved in subclasses     

The rise of “big data” on cloud computing: Review and open research issues

Cloud computing is a powerful technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Massive growth in the scale of data or big data generated through cloud computing has been observed. Addressing big data is a challenging and time-demanding task that requires a large computational infrastructure to ensure successful data processing and analysis. The rise of big data in cloud computing is reviewed in this study. The definition, characteristics, and classification of big data along with some discussions on cloud computing are introduced. The relationship between big data and cloud computing, big data storage systems, and Hadoop technology are also discussed. Furthermore, research challenges are investigated, with focus on scalability, availability, data integrity, data transformation, data quality, data heterogeneity, privacy, legal and regulatory issues, and governance. Lastly, open research issues that require substantial research efforts are summarized.     

Federated databases and systems: Part I—A tutorial on their data sharing

The issues and solutions for the interoperability of a class of heterogeneous databases and their database systems are expounded in two parts. Part I presents the data-sharing issues in federated databases and systems. Part II, which will appear in a future issue, explores resource-consolidation issues.Interoperability in this context refers to data sharing among heterogeneous databases, and to resource consolidation of computer hardware, system software, and support personnel.Resource consolidation requires the presence of a database system architecture which supports the heterogeneous system software, thereby eliminating the need for various computer hardware and support personnel. The class of heterogeneous databases and database systems expounded herein is termedfederated, meaning that they are joined in order to meet certain organizational requirements and because they require their respective application specificities, integrity constraints, and security requirements to be upheld. Federated databases and systems are new. While there are no technological solutions, there has been considerable research towards their development. This tutorial is aimed at exposing the need for such solutions. A taxonomy is introduced in our review of existing research undertakings and exploratory developments. With this taxonomy, we contrast and compare various approaches to federating databases and systems.     

A Run-time System for Efficient Execution of Scientific Workflows on Distributed Environments

Scientific workflow systems have been introduced in response to the demand of researchers from several domains of science who need to process and analyze increasingly larger datasets. The design of these systems is largely based on the observation that data analysis applications can be composed as pipelines or networks of computations on data. In this work, we present a run-time support system that is designed to facilitate this type of computation in distributed computing environments. Our system is optimized for data-intensive workflows, in which efficient management and retrieval of data, coordination of data processing and data movement, and check-pointing of intermediate results are critical and challenging issues. Experimental evaluation of our system shows that linear speedups can be achieved for sophisticated applications, which are implemented as a network of multiple data processing components.     

Views for Multilevel Database Security

Because views on relational database systems mathematically define arbitrary sets of stored and derived data, they have been proposed as a way of handling context-and content-dependent classification, dynamic classification, inference, aggregation, and sanitization in multilevel database systems. This paper describes basic view concepts for a multilevel-secure relational database model that addresses the above issues. All data entering the database are labeled according to views called classification constraints, which specify access classes for related data. In addition, views called aggregation constraints restrict access to aggregates of information. All data accesses are confined to a third set of views called access views.