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Member, IEEE Computer Society AbstractÐIn this paper, we propose and experimentally evaluate the use of the client-server database paradigm for real-time processing. To date, the study of transaction processing with time constraints has mostly been restricted to centralized or ªsingle-nodeº systems. Recently, client-server databases have exploited locality of data accesses in real-world applications to successfully provide reduced transaction response times. Our objective is to investigate the feasibility of real-time processing in a data-shipping clientserver database architecture. We compare the efficiency of the proposed architecture with that of a centralized real-time database system. We discuss transaction scheduling issues in the two architectures and propose a new policy for scheduling transactions in the client-server environment. This policy assigns higher priorities to transactions that have a greater potential for successful completion through the use of locally available data. Through a detailed performance scalability study, we investigate the effects of client dataaccess locality and various updating workloads on transaction completion rates. Our experimental results show that real-time clientserver databases can provide significant performance gains over their centralized counterparts. These gains become evident when large numbers of clients (more than 40) are attached per server, even in the presence of high data contention. Index TermsÐClient-server databases, real-time transaction processing, experimental performance evaluation.

The widespread use of networked environments and the recent availabilityof high network bandwidthshas rekindled interest in the area of automatic data refresh/update mechanisms. In many application areas, the updated information has a limited period of usefulness. Therefore, the development of systems and protocols that can handle such update tasks within predefined deadlines is required. In this paper, we propose and evaluate two real-time update-propagation mechanisms in a client-server environment. The main idea is the transport of update transactions to the location of the cached data rather than the updated data itself. Unlike current push mechanisms, the propagation of update transactions to client sites is neither periodic nor mandatory. Instead, it is based on client-specific criteria which depend on the contents of the database object being updated. We examine real-time push scheduling issues using the popular client-server database model as our underlying framework and carry out a performance scalability study under varying system configurations.

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The sections in this article are Main‐memory Databases Client–Server Databases Parallel Database Systems Summary Acknowledgment