This research is concerned with improving the performance of asynchronous algorithms. These algorithms involve a number of independent activities which generally access common data. Activities must synchronize with one another to insure that data is kept consistent. Unfortunately, synchronization impairs performance. The overall goal of the research is to develop techniques for reducing synchronization requirements. Much of the research will be concerned with concurrency control in database systems and will focus on optimistic algorithms. Such algorithms are based on the assumption that synchronization is rarely needed. They allow activities to execute in an asynchronous fashion and rely on rollback if situations are detected in which activities should have synchronized. Thus, rollback is the major cost and one goal of the proposed research is to develop techniques for reducing the probability of its occurence. These include the use of semantic information about activities, the use of special techniques for handling heavily accessed regions of the data (hotspots), and the use of information that can be gathered about an activity when it is formulated as a Prolog program. The application of optimistic algorithms to replicated databases is another area of interest. Such databases have been proposed to improved the availability of data in failure situations and can also serve to enhance performance. Finally, research will be done on strategies for performing non-atomic updates on certain shared data structures. The goal is to guarantee that readers, which execute asynchronously, always function correctly.
