The role of expert systems in federated distributed multi-database systems/Ince Levent

A shared information system is a series of computer systems interconnected by some kind of communication network. There are data repositories residing on each computer. These data repositories must somehow be integrated. The purpose for using distributed and multi-database systems is to allow users to view collections of data repositories as if they were a single entity. Multidatabase systems, better known as heterogeneous multidatabase systems, are characterized by dissimilar data models, concurrency and optimization strategies and access methods. Unlike homogenous systems, the data models that compose the global database can be based on different types of data models. It is not necessary that all participant databases use the same data model. Federated distributed database systems are a special case of multidatabase systems. They are completely autonomous and do not rely on the global data dictionary to process distributed queries. Processing distributed query requests in federated databases is very difficult since there are multiple independent databases with their own rules for query optimization, deadlock detection, and concurrency. Expert systems can play a role in this type of environment by supplying a knowledge base that contains rules for data object conversion, rules for resolving naming conflicts, and rules for exchanging data.http://archive.org/details/theroleofexperts109459362Turkish Navy author.Approved for public release; distribution is unlimited

An architecture of internet based data processing based on multicast and anycast protocols

Most of the current web-based application systems suffer from poor performance and costly heterogeneous accessing. Distributed or replicated strategies can alleviate the problem in some degree, but there are still some problems of the distributed or replicated model, such as data synchronization, load balance, and so on.&nbsp; In this paper, we propose a novel architecture for Internet-based data processing system based on multicast and anycast protocols. The proposed architecture breaks the functionalities of existing data processing system, in particular, the database functionality, into several agents. These agents communicate with each other using multicast and anycast mechanisms. We show that the proposed architecture provides better scalability, robustness, automatic load balance, and performance than the current distributed architecture of Internet-based dataprocessing.<br /

Executing Multidatabase Transactions

In a multidatabase environment, the traditional transaction model has been found to be too restrictive. Therefore, several extended transaction models have been proposed in which some of the requirements of transaction, such as isolation or atomicity, are optional. The authors describe one of such extensions, the flexible transaction model and discuss the scheduling of transactions involving multiple autonomous database systems managed by heterogeneous DBMS. The scheduling algorithm for flexible transactions is implemented using L.0, a logically parallel language which provides a framework for concisely specifying the multidatabase transactions and for scheduling them. The key aspects of a flexible transaction specification, such as subtransaction execution dependencies and transaction success criteria, can be naturally represented in L.0. Furthermore, scheduling in L.0 achieves maximal parallelism allowed by the specifications of transactions, which results in the improvement of their response times. To provide access to multiple heterogeneous hardware and software systems, they use the Distributed Operation Language (DOL). DOL approach is based on providing a common communication and data exchange protocol and uses local access managers to protect the autonomy of member software systems. When L.0 determines that a subtransaction is ready to execute, it hands it through an interface to the DOL system for execution. The interface between L.0 and DOL provides the former with the execution status of subtransactions

An ontology-based model management architecture for service innovation

Organizations have indicated renewed interest in service innovation, design and management, given the growth of service sector. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as data and models. Given the global nature of service value chains, there have been ever increasing demands on managing, sharing, and reusing these heterogeneous and distributed resources, both within and across organizational boundaries, through DSS consisting of database management systems (DBMS) and model management systems (MMS). Analogous to DBMS, model management systems focus on the management of decision models, dealing with representation, storage, and retrieval of models as well as a variety of applications such as analysis, reuse, sharing, and composition of models. Recent developments in the areas of semantic web and ontologies have provided a rich tool set for computational reasoning about these resources in an intelligent manner. In this chapter, we leverage these advances and apply service-oriented design principles to propose an ontology-based model management architecture supporting service innovation. The architecture is illustrated with case study scenarios and current state of implementation. The role of potential information technologies in supporting the architecture is also discussed. We then provide a roadmap to make advancements in research in this direction

Metadata queries for complex database systems

Federated Database Management Systems (FDBS) are very complex. Component databases can be heterogeneous, autonomous and distributed, accounting for these different characteristics in building a FDBS is a difficult engineering problem. The Common Data Model (CDM) is what is used to represent the data in the FDBS. It must be semantically rich to correctly represent the data from diverse component databases which differ in structure, datamodel, semantics and content. In this research project we look at the complexity of the FDBS and examine which datamodel is most suited for th e CDM. A good metad a ta interface and query language is essential for th e CDM because merging component databases into the FDBS and maintaining and building the FDBS rely on a complete metadata interface and query language. In this research project we analyse the metadata interface and query language of the Object-Relational datamodel with a view to use it as the CDM. Distributed Component databases in a FDBS need to be merged in to the FDBS, current tools can not completely automate this process, we examine these problems and present a mobile solution