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.

Abstract. The execution process of the queries in distributed databases require accurate estimations and predictions for performance characteristics. The problems of data allocation and query optimization done by means of mobile agents and evolutionary algorithms are considered. These problems still present a challenge because of the dynamic changes in number of components and architectural complexity of nowadays system topologies. The distributed system is modeled as a graph structure on which is de ned a dynamic cost vector. The cost vector remains consistent, relevant, by use of mobile agents performing cost statistics and vector updates. An evolutionary technique for the re-design phase is proposed. Experimental results prove the e ciency of the proposed technique.