The authors describe a simple, yet effective, distributed database model that simulates database usage and buffer management in the distributed data processing environment. The model is table driven such that database access requirements, file location, and other information defining the database environment are set up internally in several tables, and linked lists represent the directory and data blocks. Each database transaction is defined and represented by a transaction flow diagram (TFD), and a sequence of TFDs representing an operational scenario is input to the model. The model `executes' input TFDs by looking up tables, and performs buffer management for directory and file data while logging history and gathering various statistics on database usage and buffer management. The performance data are used for database access overhead measurement, database workload characterization, and buffer allocation. Disk access frequency and response time are used to validate the simulation results.

This paper describes a simple yet effective distributed database model that simulates database utilization in the distributed data processing environment. The model is table driven such that database access requirements, file location, and other information necessary for defining the database environment are set up internally in several tables. Each database transaction is defined and represented by a transaction flow diagram (TFD) and a sequence of TFDs representing a operational scenario is input to the model. The model "executes" input TFDs by looking up tables that specify their data file access requirements. While executing TFDs, the history of database usage is logged and various statistics are gathered. The performance data are used to measure database access overhead, characterize database workload, and fine-tune performance by reallocating files. The model has been implemented in Fortran on the VAX 11/780 and has been used for both measuring the given database performance and analyzing sensitivity to design changes. It has proven to be an effective tool for analyzing design effectiveness of distributed databases.

This paper examines the role of partitioning in the design of distributed data processing (DDP) systems for high technology, data driven, real time applications (e.g., Ballistic Missile Defense - BMD). Partitioning processes are contrasted with allocation processes. An overview of the DDP design process is presented, with emphasis on the virtual design phase. Contemporary partitioning strategies and concepts are reviewed, and related to system design goals. Goal-oriented partitioning considerations are discussed for three typical objectives: growth, reliability, and performance. A candidate sequence of partitioning steps to support DDP virtual design analysis is presented.