Addressing the challenges of managing data across distributed networks, this research investigates the problem of data allocation in distributed database systems. The study diverges from traditional file allocation by considering the dynamic nature of data objects and access schedules, aiming to optimize transmission costs and overall system efficiency. This paper introduces a new model for evaluating data allocation strategies, with significant implications for database design and management. Methods are proposed to determine the ideal fragments for allocation from relations in the conceptual schema, considering the queries and updates executed by users. The complexity of the data allocation problem is investigated, and methods for obtaining both optimal and heuristic solutions are presented and compared. The study emphasizes the importance of a cost-effective data allocation strategy for distributed database systems. Ultimately, this research provides insights into managing data in distributed environments, offering approaches to minimize transmission costs and optimize data availability. By addressing the complexities of data allocation, this paper contributes to the development of more efficient and scalable distributed database systems.
Published in ACM Transactions on Database Systems, this paper directly aligns with the journal's focus on theoretical and practical advancements in database management. The research on data allocation strategies and cost optimization is highly relevant to the journal's audience of database researchers and practitioners, contributing to the body of knowledge on distributed database systems.