The problem of allocating the data of a database to the sites of a communication network is investigated. This problem deviates from the well-known file allocation problem in several aspects. First, the objects to be allocated are not known a priori; second, these objects are accessed by schedules that contain transmissions between objects to produce the result. A model that makes it possible to compare the cost of allocations is presented, the cost can be computed for different cost functions and for processing schedules produced by arbitrary query processing algorithms. For minimizing the total transmission cost, a method is proposed to determine the fragments to be allocated from the relations in the conceptual schema and the queries and updates executed by the users. For the same cost function, the complexity of the data allocation problem is investigated. Methods for obtaining optimal and heuristic solutions under various ways of computing the cost of an allocation are presented and compared. Two different approaches to the allocation management problem are presented and their merits are discussed.

Distributed database technology is expected to have a significant impact on data processing in the upcoming years. With the introduction of commercial products, expectations are that distributed database management systems will by and large replace centralized ones within the next decade. In this paper, we reflect on the promises of distributed database technology, take stock of where we are, and discuss the issues that remain to be solved. We also present new research issues, such as distributed object-oriented systems, distributed knowledge bases, multiprocessor data servers, and distributed multidatabase systems, that arise with the introduction of new technology and the subsequent relaxation of some of the assumptions underlying current systems. Keywords: distributed database, data distribution, transaction management, distributed query procesing, object-oriented system, knowledge base, multidatabase system. * An abridged version of this paper has appeared as "Distributed Databas...