A Decision Support Tool for Distributed Database Design

The efficiency and effectiveness of a distributed database depend primarily on solving two interrelated design problems: data allocation, specifying what data to replicate and where to store it, and operating strategies, specifying where and how retrieval and update processes are performed. We develop a distributed database design approach that comprehensively addresses these problems, explicitly modeling their interdependencies for both retrieval and update processing. We extend earlier distributed database design models to include join order and data reduction by semijoin, in addition to data replication, copy identification, and join node selection. We demonstrate that join ordering and data reduction by semijoin are important distributed database design decisions that must be included in a distributed database design algorithm if it is to determine an overall optimal distributed database design

ALLOCATION OF DATABASES IN A DISTRIBUTED DATABASE SYSTEM

Our research focuses on developing a methodology for designing distributed database systems. This methodology is used to allocate databases across a number of computer sites connected by a communication network. It takes into account the pattern of usage of the databases, the communication costs in the network, delays due to queuing of requests for data, costs for maintaining consistency among the various copies of a database, and storage costs for the databases. The methodology is based on nonlinear integer programming modeling. A Lagrangian relaxation procedure using decomposition is developed to derive near optimal solutions for the problem. A tool has been built to operationalize this methodology, the model, and the solution procedure. The methodology developed in this research makes a significant contribution to the database field because it is one of the first to consider communication costs, costs of maintaining consistency, a,id queuing delays for the database allocation problem. It is applicable to a wide range of organizations which are in the process of moving from a centralized to a distributed computing environment