Similarity-based load adjustment for static real-time transaction systems

How to exploit application semantics to improve the performance of a real-time data-intensive application has been an active research topic in the past few years. Weaker correctness criteria and semantica-based concurrency control algorithms were proposed to provide more flexibility in reordering read and write events. Distinct from past work, this paper exploits the trade-off between data consistency and system workload. The definition of similarity is combined with the idea of transaction skipping to provide a theoretical foundation for reducing the workload of a transaction system. We also propose guidelines to adjust the execution frequencies of a static set of transactions and prove their correctness. The strengths of this work were verified by simulation experiments on an air traffic control example.