A Hybrid Data Sharing - Data Partitioning Architecture for Transaction Processing

Joel L. Wolf, Daniel M. Dias, Balakrishna R. Iyer, Philip S. Yu

Abstract: Proposes and evaluates a hybrid architecture that combines the approaches, and offers the advantages of both data sharing and data partitioning. Some databases are shared between systems, while others are retained private by specific systems. The issue is to determine which databases to share, which to retain private, and how to route transactions and partition the private databases among systems so as to minimize response time or overheads, while balancing the load among systems. A simulated annealing heuristic is used to solve this optimization problem. Trace data from large mainframe systems running IBM's IMS database management system are used to illustrate the methodology and to demonstrate the advantage of the hybrid approach.<>

External IDs:dblp:conf/icde/WolfDIY88