Similarity-based load adjustment for real-time data-intensive applications

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 semantics-based concurrency control algorithms were proposed to provide more flexibility in reordering read and write events. Distinct from the past work, this paper exploits the tradeoff 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 (Peng et al., 1997).