Research on scheduling algorithms adapting to arrival rate changes of stream data

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In this research project, we have studied on scheduling algorithms for stream data with dynamic arrival rates and have also investigated research trends around stream data processingFor handling stream data which arrive continuously at unpredictable rates, scheduling algorithms have to adapt to the changes of arrival rates dynamically. In this research project, dynamic scheduling algorithms for shared window joins over binary stream data have been developed. Unlike previous work on scheduling of continuous queries, our algorithms take account of not only the throughput of queries but also the process rate of each query, while they adapt to the changes of arrival rates of stream data Some experimental results show that our implementation of the algorithms can work well with small scheduling cost.In studies on research trends around stream data processing, we have some results concerning such fields as security and privacy, P2P systems, processing in SMT processors, and web caching systems. In fact, we have discussed privacy preserving count aggregate queries to k-classification, rule-based integrity checks for fine-grained database access control, a P2P protocol for load balancing by using replicas, a thread scheduling method for SMT processor considering program phase, and introducing group framework into P2P networks for constructing web caching systems. We have also clarified several problems in such fields for future work.