A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.

Federated database systems for managing distributed, heterogeneous, and autonomous databases

The widespread distribution and availability of small-scale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such example is a sensor network consisting of a large number of sensor nodes that combine physical sensing capabilities such as temperature, light, or seismic sensors with networking and computation capabilities. Applications range from environmental control, warehouse inventory, and health care to military environments. Existing sensor networks assume that the sensors are preprogrammed and send data to a central frontend where the data is aggregated and stored for offline querying and analysis. This approach has two major drawbacks. First, the user cannot change the behavior of the system on the fly. Second, conservation of battery power is a major design factor, but a central system cannot make use of in-network programming, which trades costly communication for cheap local computation.In this paper, we introduce the Cougar approach to tasking sensor networks through declarative queries. Given a user query, a query optimizer generates an efficient query plan for in-network query processing, which can vastly reduce resource usage and thus extend the lifetime of a sensor network. In addition, since queries are asked in a declarative language, the user is shielded from the physical characteristics of the network. We give a short overview of sensor networks, propose a natural architecture for a data management system for sensor networks, and describe open research problems in this area.

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The cougar approach to in-network query processing in sensor networks

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

/pdf/query-evaluation-techniques-for-large-databases-45td1anbls.pdf

Query evaluation techniques for large databases

The goal of the Tsimmis Project is to develop tools that facilitate the rapid integration of heterogeneous information sources that may include both structured and unstructured data. This paper gives an overview of the project, describing components that extract properties from unstructured objects, that translate information into a common object model, that combine information from several sources, that allow browsing of information, and that manage constraints across heterogeneous sites. Tsimmis is a joint project between Stanford and the IBM Almaden Research Center. 1 Overview A common problem facing many organizations today is that of multiple, disparate information sources and repositories, including databases, object stores, knowledge bases, file systems, digital libraries, information retrieval systems, and electronic mail systems. Decision makers often need information from multiple sources, but are unable to get and fuse the required information in a timely fashion due to the diffculties of accessing the different systems, and due to the fact that the information obtained can be inconsistent and contradictory. Research sponsored by the Wright Laboratory, Aeronautical Systems Center, Air Force Material Command, USAF, under Grant Number F33615-93-1-1339. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the offcial policies or endorsements, either express or implied, of Wright Laboratory or the US Government. This work was also supported by the Reid and Polly Anderson Faculty Scholar Fund, the Center for Integrated Systems at Stanford University, and by Equipment Grants from Digital Equipment Corporation and IBM Corporation. The goal of the TSIMMIS 1 project is to provide tools for accessing, in an integrated fashion, multiple informati

The TSIMMIS project: Integration of heterogeneous information sources

コンピュータ・サイエンス : ACM computing surveys

It is increasingly important for organizations to achieve additional coordination of diverse computerized operations. To do so, it is necessary to have database systems that can operate over a distributed network and can encompass a heterogeneous mix of computers, operating systems, communications links, and local database management systems. This paper outlines approaches to various aspects of heterogeneous distributed data management and describes the characteristics and architectures of seven existing heterogeneous distributed database systems developed for production use. The objective is a survey of the state of the art in systems targeted for production environments as opposed to research prototypes.

/pdf/heterogeneous-distributed-database-systems-for-production-4m6mraf3tf.pdf

Heterogeneous distributed database systems for production use

Introduction This document is a part of the definition of a reference architecture for the integration of manufacturing software applications in the areas of design, fabrication and assembly of discrete electro-mechanical parts. The reference architecture is an element of the Systems Integration of Manufacturing Applications (SIMA) project at NIST (see Appendix A). The scope of the project, and therefore of the reference architecture, is limited to design engineering, manufacturing engineering, production systems engineering and production activities. Other aspects of the manufacturing enterprise, such as product planning, distribution and maintenance , are not within the scope of the project and are not included in the reference architecture. Following the definitiions in the SIMA Background Study [Bark95], we use the term reference architecture to mean: • the identification of types of systems that perform, or support human agents in performing, the activities within a given domain, and • the identification of the nature and content of the interfaces required among those systems. Accordingly, the reference architecture has three parts: • Part 1 — the Activity Model — provides a model of the generic activities involved in the manufacturing process, and the information flows required to support those activities. • Part 2 — the Systems Model — identifies the manufacturing application systems, both human and automated, which perform these activities, and the interfaces required for those systems to support the identified information flows. • Part 3 — the Information Models — define formally and in detail the objects and information which appear in the interfaces. This document is Part 1 — the Activity Model. It represents the first step toward the goal of the SIMA architecture project — to identify the functions and interfaces required of manufacturing applications software systems. It is intended to provide a frame of reference for SIMA projects and similar industrial projects, which are developing " standard interface specifications ". As a frame of reference, it permits such specification projects to name and " locate " the interfaces they intend to specify and assists those projects in defining the scope of those interface specifications, by identifying the functions the interface is intended to support. Companion documents will provide the other parts of the reference architecture and define a corresponding " engineering architecture " specifying for each interface the means of information exchange to be used and the representation forms for the information. Multiple engineering architectures which correspond to the …

SIMA reference architecture, part 1:: activity models

The advent of sophisticated automation equipment and computer hardware and software is changing the way manufacturing is carried out. To be competitive, manufacturing companies must integrate these new technologies into their existing and future factories. In addition, they must integrate the planning, control and data management methodologies needed to make effective use of these technologies. This paper discusses several issues related to the design and implementation of a system architecture which can serve as the basis for integration. The architecture includes separate architectures for production planning and control, data management and data communications.

Edward J. Barkmeyer

Papers

Heterogeneous distributed database systems for production use

SIMA reference architecture, part 1:: activity models

Issues in the design and implementation of a system architecture for computer integrated manufacturing

Concepts for Automating Systems Integration

A Vision System for Real-Time Control of Robots